A protein complex consists of two or more proteins that are linked together through protein–protein interactions. The proteins show stable/transient and direct/indirect interactions within the protein complex or between the protein complexes. Protein complexes are involved in regulation of most of the cellular processes and molecular functions. The delineation of protein complexes is important to expand our knowledge on proteins functional roles in physiological and pathological conditions. The genetic yeast-2-hybrid method has been extensively used to characterize protein-protein interactions. Alternatively, a biochemical-based affinity purification coupled with mass spectrometry (AP-MS) approach has been widely used to characterize the protein complexes. In the AP-MS method, a protein complex of a target protein of interest is purified using a specific antibody or an affinity tag  and polyhistidine (His)) and is subsequently analyzed by means of MS. Tandem affinity purification, a two-step purification system, coupled with MS has been widely used mainly to reduce the contaminants. We review here a general principle for AP-MS-based characterization of protein complexes and we explore several protein complexes identified in pluripotent stem cell biology and cancer biology as examples. Ti.e., affinity-tagged protein). The affinity captured target protein is subjected to stringent washing to remove possible nonspecific protein interactions, and then purified by using elution buffer. The affinity purified sample is digested and desalted ahead of MS-based identification of interaction partners of target protein . In this approach, the endogenously expressed target protein along with its interaction partners is purified using a specific antibody and a matrix such as protein A/G beads ( protein . HoweverS-transferase (GST), hemagglutinin (HA), polyhistidine (His), maltose-binding protein (MBP), Myc, and streptavidin (Strep) [i.e., healthy and diseased tissues). The purified complexes are generally eluted by changing the pH or salt condition, or by binding competition with a tag-specific matrix based on the experimental conditions [A variety of tags are available for affinity purification and the most popular tags are DYKDDDDK peptide (FLAG), glutathione- (Strep) ,13,14,20 (Strep) . The affnditions ,13,14.MW of 1012.98 kDa) hydrophilic peptide with amino acid sequence DYKDDDDK. The FLAG-tagged target protein along with its interacting partners is purified by using anti-FLAG antibody specific to the FLAG epitope. The competitive elution could be performed using FLAG peptide. The FLAG tag can be removed from the purified target protein using the specific protease, enterokinase for further use of the target protein  [Here we describe two examples of tags (FLAG and His) used in single step affinity purification . The FLAnalysis) . On the nalysis) . In anotnalysis) .MW of 20.7 kDa) is a combination of calmodulin-binding peptide (CBP) and IgG-binding protein A tags, which were separated by a TEV (tobacco etch virus) protease cleavage site [et al. [MW 18.8 kDa), which is a combination of protein G and streptavidin-binding peptide (SBP) tags, with 10-fold increase in yield when compared with demonstrated TAP procedure. Tagging proteins with high molecular weight tags may affect the proper folding ability, functional activity, and binding capacity [The methodological development of single step tag-based purification resulted in an approach known as tandem affinity purification (TAP) . This apage site . This isage site . Howeverage site ,25. Burc [et al.  have shocapacity ,26. Theret al. [The original TAP approach has been demonstrated in the yeast system . The yeaet al.  have demet al. . The AP-et al. .The next step is identification of interactors within the purified protein complex by MS analysis . Althougi.e., sheath gas) assists in droplet evaporation and ejection of peptide ions at high voltage. The peptide ions were then transferred to the mass analyzer , orbitrap, ion trap, or hybrid type) that is placed in high vacuum. The analyzed ions were subsequently recorded as mass spectra by the ion detector. The raw data obtained from the MALDI- or ESI-MS instrument is searched against the database and proteins of the protein complexes were identified [Although a variety of commercial mass spectrometers are available, the basic principle is similar for MS-based protein analysis. We recommend to readers other excellent reviews on basic principles of MS instrumentation ,43,44, w18O, ICAT approaches) can be performed by using the commercially available labeling reagents. However, recent advances in MS analysis and software development for data analysis has made the label-free quantitation (LQ) a powerful technique in quantitative proteomics [In addition to the identification of interactors within the protein complex, their relative expression levels can be quantified between two or more biological conditions by using quantitative MS analysis. Two types of MS-based quantitative approaches are available: labeling and label-free methods. Labeling can be performed at three levels to achieve accurate protein quantitation ,45. Metaoteomics . The LQ Labeling and label-free quantitation approaches have been widely used for the identification of contaminants within the protein complex ,20,31. Iet al. [et al. [In addition, labeling or label-free quantitation is useful for comparison of interactors of the protein complex between two or more biological conditions. In label-free approach  by prepaet al.  have shoet al. . In anot [et al.  have com [et al. .in vitro/in vivo experimental data and/or in silico-based predictions [The improvements in purification methods and developments in MS analysis tremendously increased the information related to protein interactions and their protein complexes. The experimental data related to protein complexes has been stored in a database known as the comprehensive resource of mammalian protein complexes (CORUM) ,57. In aComputational approaches are necessary to extract the biological significance by systematic analysis of information stored in the protein interaction databases. The data obtained from protein interaction databases could be analyzed and comprehended by using a variety of tools such as Cytoscape ,13. For The main types of pluripotent stem cells are embryonic stem cells (ESCs), and ESCs derived by somatic cell nuclear transfer (NT-ESCs), and induced pluripotent stem cells (iPSCs) generated by somatic cell reprograming ,70,71,72In addition to the above described protein interactions of core pluripotency genes, a recent study has demonstrated an interactome of RNA binding protein, L1TD1 (LINE-1 type transposase domain-containing protein 1) in human ESCs. The high levels of L1TD1 has been identified in ESCs and is involved in maintenance of human ES cells pluripotency. The AP-MS approach identified 306 proteins in the interactome of L1TD1 and several of them were known to be shared with Oct4, Sox2 and Nanog interactomes . This stTo gain further insight into pluripotency, the protein interaction data of Oct4 and Nanog from the above mentioned four studies ,75,78,79Identification of disease-associated genes  is critical for drug development, diagnosis, and therapy. The genes present in cancers but absent or expressed at lower levels in their corresponding healthy normal samples are known as cancer-associated genes. Typically, the cancer-associated genes/proteins were identified by conventional methods or omics approaches by looking into the fold-changes of gene expression levels between cancer and normal samples. However, the cancer-associated proteins interact with other proteins to initiate oncogenic signal transduction, which deregulates normal cellular functions and leads to cancer pathogenesis. Therefore, studying the protein complexes in cancers is important to understand the mechanisms associated with cancer pathogenesis.i.e., degradation of extracellular matrix) to promote tumor progression as well as in non-proteolytic functions  [n = 264) were identified in the nuclei of human breast cancer cells (MCF-7) [Here, we attempt to highlight some of the receptor protein complexes identified in cancer cells. Epidermal growth factor receptor (EGFR) is a well-known oncogene that plays a key role in multiple cancers. A recent study characterized its interactome in epidermal carcinoma cells by AP-MS analysis . This steration) . The interation) . This steration) . Ligand- (MCF-7) . Another (MCF-7) . Moreove (MCF-7) . The intBy reviewing the literature, we tried to emphasize the protein complexes identified in several cancer proteomics studies as follows: (i) the protein arginine methyltransferases (PRMTs) are deregulated in multiple cancers. It is known that more than 90% of the methylation of arginine residues is controlled by the activity of PRMT1, which is linked with transcription regulation . PRMT1 iin vivo/in vitro), computational analysis (in silico), and resource interaction databases are necessary to map direct and indirect protein interactions identified through the AP-MS approach. The quantitative AP-MS analysis has been used to identify the contaminants, which show non-specific interactions with the target protein. We believe that the major applications of quantitative AP-MS approach are to compare the interactors of the protein complex under different biological conditions and to study the protein interaction dynamics. However, a relatively large number of studies have demonstrated the static interactions of target proteins  but not the differential interactions and protein interaction dynamics of target proteins  [AP-MS is the most widely accepted approach to characterize protein complexes of target proteins due to the robustness and sensitivity of the MS analysis. Experimental or computational approaches have linked several protein complexes with cellular processes and molecular functions by using Gene Ontology annotations ,57,98. Tndition) ,48. It ii.e., protein localization-specific), cell condition-specific , and tissue-specific protein-protein interactions in databases. In addition, it is important to store the protein interaction dynamics and differential interactomes in databases. Moreover, the databases should include options to look into the above information for each gene and its variants. This may further enhance our understanding of the protein functional roles in pathogenesis as well as physiological conditions.The Encyclopedia of DNA Elements (ENCODE) project revealed 20,687 protein-coding genes in the human genome . In gene


A facile synthesis of a styrylpyridinium salt (SbQ)/montmorillonite (MMT) via cationic exchange interactions between styrylpyridinium species  and MMT platelets is reported in this work. The SbQ-MMT solutions were irradiated under ultraviolet (UV) light for a specific time to obtain the cross-linked SbQ-MMT materials. Scanning electron microscopy and atomic force microscopy analyses revealed the structures and morphologies of MMT and modified MMT. X-ray diffraction and transmission electron microscope analyses indicated that the basal spacing increased from 1.24 to 1.53 nm compared with the pristine MMT, which proved that SbQ had interacted with MMT. Thermal gravimetric analysis curves showed that the amount of SbQ in the MMT interlayers was 35.71 meq/100 g. Fourier transform infrared spectroscopy also confirmed the intercalation of SbQ species into MMT interlayers, and UV spectroscopy was used to follow up the cross-linking of SbQ-MMT. This novel material has potential applications in drug delivery, and it can also be used as an additive to improve the mechanical properties of polymers. SbQ , similar to surfactants, is an amphiphilic sensitizer of the styrylpyridinium family , and it In recent years, modified MMTs have been extensively used as drug delivery carriers and for protein adsorption -13. Bani2 groups of proteins and this interaction could be used for drug delivery applications. More importantly, after UV light irradiation, the cross-linked SbQ may have potential applications such as hydrophobic drug delivery -pyridiniummethosulphate (SbQ) was purchased from Shanghai Guangyi Printing Equipment Technology Co. Ltd . Sodium montmorillonite (Na-MMT) was a kind gift from Zhejiang Fenghong Chemical Co. Ltd. . Deionized water was used for the preparation of all solutions.+ in MMT galleries and SbQ cations in aqueous solution according to a modified literature method. Na-MMT (1 g) dispersed in 50 mL of deionized water was vigorously stirred for 3 h . In the FTIR spectrum of cross-linked SbQ-MMT, characteristic bands belonging to MMT and SbQ appeared, indicating that the cross-linked SbQ had interacted with MMT. The band which appeared at 1,650 cm−1 indicated the aldehydic (−CHO) group of SbQ which could interact with the − NH2 groups present in protein for drug delivery.Figure UV-vis spectroscopy was utilized to trace the photo-cross-linking process of SbQ-MMT solution Figure . When thIn summary, SbQ was successfully intercalated into MMT via cationic exchange interactions and were irradiated under UV light to get the cross-linked SbQ-MMT. The present study was the first to our knowledge to use SbQ to intercalate into MMT layers. The results showed that the layered basal spacing of MMT was increased and the morphology of MMT was changed after the intercalation of SbQ. It was found that SbQ was cross-linked after UV irradiation as designed. The existence of aldehyde (−CHO) group, the hydrophobic character of cross-linked SbQ molecules and the natural properties of MMT make these novel materials to be potentially used in drug delivery or as an additive into polymeric composites to improve their mechanical properties.SbQ: a styrylpyridinium salt; MMT: montmorillonite; SEM: scanning electron microscopy; AFM: atomic force microscopy; XRD: X-ray diffraction; TEM: transmission electron microscopy; TGA: thermal gravimetric analysis; FTIR: Fourier transform infrared spectroscopy.The authors declare that they have no competing interests.QW and QW gave the guidance, and JC did the experiments. QW, XC, and JC analyzed the data and gave the final approval of the version of the manuscript to be published. All authors read and approved the final manuscript.JC, female, current master student, has a research direction of functional nanofibers. QW, male, professor, has a research field of functional nanofibers.


Up to 60% of practicing physicians report symptoms of burnout, which often peak during residency. Residency is also a relevant time for habits of self-care and resiliency to be emphasized. A growing literature underscores the importance of this; however, evidence about effective burnout prevention curriculum during residency remains limited.The purpose of this project is to evaluate the impact of a new, 1-month wellness curriculum for 12 second-year family medicine residents on burnout, empathy, stress, and self-compassion.The pilot program, introduced during a new rotation emphasizing competencies around leadership, focused on teaching skills to cultivate mindfulness and self-compassion in order to enhance empathy and reduce stress. Pre-assessments and 3-month follow-up assessments on measures of burnout, empathy, self-compassion, and perceived stress were collected to evaluate the impact of the curriculum. It was hypothesized that this curriculum would enhance empathy and self-compassion as well as reduce stress and burnout among family medicine residents.Descriptive statistics revealed positive trends on the mean scores of all the measures, particularly the Mindfulness Scale of the Self-Compassion Inventory and the Jefferson Empathy Scale. However, the small sample size and lack of sufficient power to detect meaningful differences limited the use of inferential statistics.This feasibility study demonstrates how a residency wellness curriculum can be developed, implemented, and evaluated with promising results, including high participant satisfaction. In fprevention or offer clear evidence of effectiveness  has three health centers serving socioeconomically diverse patient populations . All 12 PGY-II family medicine residents  participate in a 4-week Physician as Leader (PAL) rotation. The PAL curriculum  began inThe PAL curriculum was scheduled by rotation block, with a different rollout date for each health center, so it was done three times total. A behavioral science faculty member (CR) implemented the wellness curriculum every Friday afternoon for 2 h during the 4-week rotation with four residents per cycle. For 3 months following the curriculum, residents were sent monthly emails with reminders about implementing self-reflection skills, journaling, gratitude, and mindful breathing.The study was a pre–post within subjects design, with a 3-month follow-up on the same set of four assessment measures. The pre-assessments occurred at the start of the PAL rotation for each site and the 3-month post-assessment occurred at three different times when PGY-IIs gathered for required didactics. Residents were informed of the confidential and non-evaluative nature of these matched pre–post assessments collected by a trained research assistant. Using paper/pencil administration, the measures included: 1) Maslach Burnout Inventory ; 2) Selft-tests were calculated to determine statistically significant changes. Because of the small sample size and non-normal data distributions, the non-parametric equivalent of the paired t-test was used. As results were identical, descriptive data from the paired t-tests are reported for ease of interpreting mean scores. A power analysis revealed insufficient power to find pre–post differences on all four measures so inferential statistics are not reported in the tables.Statistical analysis was primarily descriptive. Paired This project was granted exemption status by the University of Massachusetts Medical School's Institutional Review Board.t=−3.51; p=0.008).Of the 12 PGY-II residents, only 9 completed the pre measures while 12 completed the post measures. As shown in Among other subscales, residents’ scores improved; that is, increases in reported self-kindness and compassion with concomitant decreases in reported self-judgment. Similar trends were seen in other measures; that is, residents reported less perceived stress at follow-up, improved efficacy, decreased exhaustion, as well as higher scores in empathy . Interestingly, the range of scores on the Jefferson Empathy Scale shifted from pre- (71–130) to post- (115–134) measurement suggesting a more narrow range of scores toward increased empathy.prevent burnout among residents has been evaluated (Reducing burnout among primary care providers is essential to achieving the IHI Triple Aim , but a pvaluated . Preventall PAL rotations as well as monthly sessions throughout the year with PGYIIs and IIIs. This will permit an enhanced evaluation with follow-up. Further research in both curricular development and program evaluation is needed to determine whether introducing resiliency skills during residency impacts downstream outcomes such as burnout prevention, productivity, quality of care, expressed empathy, and patient satisfaction.The strengths of this project include the use of validated instruments as well as development of a defined curriculum in modules that can be easily modified and implemented. The challenges of implementation include engendering leadership support, finding curriculum time, and engaging a well-trained faculty member. This specific curriculum required about 40 h of faculty time over the course of the year, including curriculum development time. The positive feedback from residents has led to a curriculum expansion, which is now embedded in Residency programs are increasingly implementing wellness initiatives to improve resident health, prevent burnout, and improve patient outcomes . The lon


A diagnosis of diabetes mellitus types 1 or 2 doubles the odds of a comorbid depressive disorder. The combined diseases have a wide range of adverse outcomes, such as a lower quality of life, poorer diabetes outcomes and increased healthcare utilisation. Diabetes patients with depression can be treated effectively with psychotherapy, but access to psychological care is limited. In this study we will examine the efficacy and cost-effectiveness of a newly developed web-based intervention (GET.ON Mood Enhancer Diabetes) for people with diabetes and comorbid depressive symptoms.A two-arm randomised controlled trial will be conducted. Adults with diabetes (type 1 or type 2) with increased depression scores ) will be included. Eligible participants will be recruited through advertisement in diabetes patient journals and via a large-scale German health insurance company. The participants will be randomly assigned to either a 6-week minimally guided web-based self-help program or an online psychoeducation program on depression. The study will include 260 participants, which will enable us to detect a statistically significant difference with a group effect size of d = 0.35 at a power of 80% and a significance level of p = 0.05. The primary outcome measure will be the level of depression as assessed by the CES-D. The secondary outcome measures will be: diabetes-specific emotional distress, glycaemic control, self-management behaviour and the participants’ satisfaction with the intervention. Online self-assessments will be collected at baseline and after a 2 months period, with additional follow-up measurements 6 and 12 months after randomisation. The data will be analysed on an intention-to-treat basis and per protocol. In addition, we will conduct an economic evaluation from a societal perspective.If this intervention is shown to be cost-effective, it has considerable potential for implementing psychological care for large numbers of people with diabetes and comorbid depression in routine practice and improve health outcomes.DRKS00004748.German Clinical Trial Register (DRKS):  Diabetes is highly prevalent. The International Diabetes Federation (IDF) estimates that in 2012, more than 371 million people worldwide were adversely affected by diabetes. It is estimated that 5.2 million people in Germany suffer from diabetes , poorer Psychotherapy has been demonstrated to be as effective for people with diabetes and co-morbid depression as for those without diabetes ,15. HoweMeta-analyses have shown that web-based interventions are effective for treating mental disorders such as depression, anxiety or problem drinking -29 and mNon-compliance and low adherence to physical treatments or medication regiments are common problems among people with diabetes , people After considering the findings of van Bastelaar et al. ,34,39,40Web-based depression interventions appear to be cost-effective for the general population as shown in a small number of studies -44. AlthThis study is designed as a randomised controlled trial with two parallel groups. The IG will receive access to the diabetes-specific, web-based online program (GET.ON M.D.). The CG will receive general online psychoeducation about depression. Moreover, the CG will have the opportunity to work with an unguided version of the online program 12 months after baseline assessment. The participants in both conditions will have unrestricted access to treatment as usual during the study.Measurement points are scheduled equally for both groups, at baseline and 8 weeks after randomisation. In addition, there will be follow-up measurements 6 and 12 months after randomisation  to help reduce depression. Recruitment is still ongoing (start March 2013) with a total recruitment time of 8 months.https://geton-training.de) contains detailed information about the study. Interested visitors may leave their email addresses on this website. Afterwards, they will be registered in a secured web-based platform and invited for an online screening. The people who do not pass the screening will receive an explanation for their exclusion along with the German patient guidelines for depression )We will collect socio-demographic data ; lifestyle data ; data on diabetes ; Patient Questionnaire on Therapy Expectation and Evaluation (PATHEV ); data oWe will use the Dutch Cost Questionnaire “Trimbos Institute and Institute of Medical Technology Questionnaire for Costs Associated with Psychiatric Illness” (TiC-P)  adapted Quality-adjusted life years (QALYs) will be calculated based on the EuroQol (EQ-5D)  and the The SF-12 is based on the 36-item Short Form Health Survey (SF-36), a health-related quality-of-life questionnaire . The SF-The analysis will be performed according to the Consolidated Standards of Reporting Trials (CONSORT) statement regarding eHealth . The datWe will also conduct clinical significance change analyses as described by Jacobson and Truax ,96. In tAs secondary analyses, we will also conduct per-protocol (PP) and completers-only analyses.To show the long-term effect on the primary outcome after 6 months and 12 months, we will use mixed models.The economic analysis will be performed from a societal perspective. We will conduct a cost-effectiveness analysis (CEA) and a cost-utility analysis (CUA). Using the incremental cost-effectiveness ratio (ICER), we will show the differences in the costs and benefits between the two groups. The robustness of the ICER will be determined using non-parametric bootstrapping. Furthermore, we will also use bootstrapping to quantify the uncertainty around the ICER, which will be shown on the cost-effectiveness plane  and as aIn the present study, we aim to compare a web-based program with mobile phone support and minimal guidance with a control group, receiving psychoeducation only. We expect the depression level of the participants in the intervention group to be significantly lower immediately after the intervention and also after 6 and 12 months compared with the control group. Our planned analyses will enable us to assess whether the outcomes are sustained over time.Depressive symptoms in people with diabetes have an adverse impact on mental health, quality of life and on medical outcomes such as blood glucose -7. CompaDepression treatments for adults with diabetes produce economic benefits . Until nBecause adherence to recommendations involving treatment recommendations and lifestyle changes is often a problem with diabetes patients , depressOne limitation of this study design is that many diabetes patients are elderly, especially those with diabetes type 2 and may have limited access to the Internet. In 2002, only 8% of the Germans 60 or older had access to the Internet: this number increased to 39% ten years later . The resFurthermore, it is known that lower social status and lower education are associated with an increased risk for diabetes  and thatGiven the high prevalence of comorbid diabetes and depression, web-based interventions may have great potential to lower the threshold and increase access to the treatment of these co-morbid disorders. If GET.ON M.D. is shown to be cost- effective, it has great potential to be integrated into routine care and so to improve the well-being of people with diabetes and comorbid depression. This is of high importance given the negative impact of co-occurrence of diabetes and depression on psychological and medical outcomes, as well as on the health care system ,14,100.Further research is necessary to establish whether interventions that integrate diabetes and depression are more effective in the long term compared with conventional depression interventions.AADQ: Acceptance and action diabetes questionnaire; ANCOVAs: Analyses of covariance; ATSPHS: Attitudes toward seeking psychological help scale; BADS: Behavioural activation depression scale; BDI II: Beck depression inventory II; CBT: Cognitive behavioural therapy; CEA: Cost-effectiveness analysis; CES-D: Center for epidemiological studies depression scale; CG: Control group; CONSORT: Consolidated standards for reporting trials; CUA: Cost-utility analysis; DRKS: Deutsches register für klinische studien ; DSM-IV: Diagnostic and statistical manual of mental disorders IV; DSMQ: Diabetes self-management questionnaire; EQ-5D: EuroQol; GET.ON M.D.: GET.ON mood enhancer diabetes; HADS: Hospital anxiety and depression scale; HbA1c: Haemoglobin A1c; ICER: Incremental cost-effectiveness ratio; IDF: International diabetes federation; IG: Intervention group; ITT: Intention-to-treat; K10: Kessler psychological distress scale; PAID: Problem areas in diabetes; PASS 12: Power analysis and sample size software; PP: Per-protocol; PSWQ: Penn state worry questionnaire; PATHEV: Patient questionnaire on therapy expectation and evaluation; QALYS: Quality adjusted life years; RCI: reliable change index; SCID: Structured clinical interview for DSM IV; SF-12: Short form health survey 12; SF-36: Short form health survey 36; SPSI-R: Social problem solving inventory-revised; TIC-P: Trimbos institute and institute of medical technology questionnaire for costs associated with psychiatric illness; VAS: Visual analogue scale.Professor Berking is minority shareholder of Minddistrict GmbH which provides the online platform for the training.MB obtained funding for this study. All authors contributed to the design of the study. SN, DL, DDE, MB, EH, FS and HR developed the intervention content. HB and AB contributed to the intervention content. SN wrote the draft of the manuscript. HR supervised the writing process. All authors contributed to the further writing of the manuscript and approved the final manuscript.The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1471-244X/13/306/prepub


In the functional annotation field, Sifter v2.0 is regarded as one of the best when it comes to annotation quality. Recently, it has been considered one of the best tools for functional annotation according to the initiative “Critical Assessment of Protein Function Annotation” (CAFA), an open collaborative experiment designed for large-scale assessment of protein function prediction tools. Sifter combines two powerful ideas: phylogenomics and bayesian graphical models. Nevertheless, it is still not widely used. This contradictory observation is probably due to issues with usability and suitability of the framework to a high throughput scale.Although powerful in terms of approach, it can be considered prototype level in terms of software. The current Sifter version does not allow nucleotide or amino acid sequences input directly, nor accepts current standards in gene annotation formats. Moreover, several parameters are still hardcoded and difficult to be tuned by the end user. Finally, its relationship to third party dependence software is cumbersome, along with its output.In this study, we had two goals: (i) enhance the tool’s usability, through local implementa- tions or a web-based front end; and (ii) optimize the original source-code for better performance, allowing it to be used in genome-wide scale.Among the implemented strategies we have: parallel threads; CPU load balancing; best use of disk access, memory usage and runtime; adaptation to the currently used biological databases formats; improved user accessibility; expansion of accepted input types; automation of the reconciliation process; new output format; detailed documentation; and other minor implementations.The increased performance allowed, for example, the reannotation of 419,029 Saccharum officinarum (sugarcane) ESTs to be performed by Sifter-T in 5 days, while BLAST took 49 days in a standard bioinformatics laboratory machine.http://labpib.fmrp.usp.br/methods/sifter-t/.This implementation result is presented as Sifter-T (Sifter Throughput-optimized), an open source tool with better usability and performance when compared to the original Sifter workflow implementation. The new Sifter-T features allow researchers to have easy and quick access to the Sifter’s powerful annotation mathematical method, now with enhanced experiment customization and keeping the inference engine intact. Sifter-T, and its online interface, is freely available at


Moreover, we developed a pipeline named lncSeeker to identify 176 680 high-confidence lncRNAs from 14 species. Temporal and spatial expression patterns of various ncRNAs were profiled. We identified approximately 24 280 primate-specific, 5193 rodent-specific lncRNAs, and 55 highly conserved lncRNA orthologs between human and zebrafish. We annotated 14 867 human circRNAs, 1260 of which are orthologous to mouse circRNAs. By combining expression profiles and functional genomic annotations, we developed lncFunction web-server to predict the function of lncRNAs based on protein-lncRNA co-expression networks. This study is expected to provide considerable resources to facilitate future experimental studies and to uncover ncRNA functions.Small non-coding RNAs (e.g. miRNAs) and long non-coding RNAs (e.g. lincRNAs and circRNAs) are emerging as key regulators of various cellular processes. However, only a very small fraction of these enigmatic RNAs have been well functionally characterized. In this study, we describe deepBase v2.0 ( Eukaryotic genomes encode thousands of small and large non-coding RNAs (ncRNAs) ,2, such To better understand the functions of these ncRNAs, a systematic catalog of ncRNA transcripts and their expressions across tissues and evolutional conservation across species is necessary ,2. To daRecent advances in high-throughput next-sequencing technology have produced large numbers of short and long RNA sequences, and enable the detection and profiling of known and novel ncRNAs at unprecedented sensitivity and depth . Many stTo meet above-mentioned needs, we have updated deepBase  to versiCiona intestinalis (JGI v2.0) genome sequences were downloaded from the UCSC Bioinformatics website. Chimp , Gorilla , Rhesus , Rat , Cow , Opossum , Platypus , X. tropicalis , Zebrafish  and C. elegans  genome sequences were downloaded from the UCSC Bioinformatics website. The Caenorhabditis remanei and Caenorhabditis briggsae genome sequences were downloaded from WormBase  between lncRNAs and protein-coding genes was estimated using coexpression program (the program is available from the authors upon request), which was written in C language and ALGLIB library, and p-value was adjusted with the False Discovery Rate (FDR) correction . GO ontodeepBase provides genome-wide identification of small RNAs in multiple types, including microRNAs, snoRNAs, rRNA-derived small RNAs. In total, there are 18 508 small RNAs are identified in 51 studies of 10 species Table . After oIn the Browse page, we also provide integration of lncRNAs identified by RNA-seq, organized by different species and corresponding studies Table . About hOne of the most important features of miRNAs is their special expressions in different stages, tissues or cells. deepBase v2.0 provides the expression profiles of small RNAs in each sample. Users can find their interested miRNA name in the small RNA ‘Expression’ page. The heatmap will display the normalized expression number of miRNA in each sample. Click the name of the miRNA will link to the detail expression result page. Users can find that hsa-mir-122 is especially highly expressed in normal liver tissues compared to other samples.Spatial and temporal specific expression is one of the well-characterized properties of lncRNAs . In the We conducted evolution conservation analysis of lncRNAs in 14 species. Many studies show that most lncRNAs are lineage-specific and in fast phylogenetic evolution . Out of We provide a web-based tool named IncSeeker to implement our filtering pipeline of finding lncRNAs transcriptome assembled from RNA-seq data. Users can upload their transcriptome data in BED12 or GTF format, and our web-server will process the file by a series of tunable criterion and filter steps, including transcript length, exon number, coding ability and potential coding domain. A strict set of lncRNAs will then be displayed on the result page. To evaluate the performance of lncSeeker, we used lncSeeker to predict lncRNAs in GENCODE gene sets. There are 11 324 high-confidence lincRNA transcripts and 95 309 protein-coding transcripts in GENCODE Release 19 (GRCh37.p13). The result showed that the accuracy of lncSeeker was 96.82%, the sensitivity and specificity were 70.08% and 100% (Supplementary Table S3), respectively. We further compared lncSeeker with other four tools related with lncRNAs identification, getorf , txCdsPrA web-based tool, lncFunction, was also developed to predict lncRNA functions from coding and non-coding co-expression networks. There are six options on the query page, and the option ‘Input the Target LncRNA’ is required. The running parameters, expression values from selected study and every outcome in the three categories of function prediction are available for users to download.Although a few dozen of lncRNAs and circRNAs have been characterized to some extent and reported to function in important cellular processes –4, such Currently, there is an increasing amount of databases developed for ncRNAs, including NONCODE , lncRNAdNext-generation sequencing technologies play vital roles in improving our understanding of functional genomics. As sRNA-Seq and RNA-Seq technology is applied to a broader set of species, cell lines, tissues and conditions, we will continually maintain and update the database. The integration of transcriptome datasets from the deepBase database, and the cancer genomics data and clinical information from the Gene Expression Omnibus (GEO), The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC), will improve our understanding of expression and function of ncRNAs in diseases.http://deepbase.sysu.edu.cn/ or http://biocenter.sysu.edu.cn/deepBase/. The deepBase data files can be downloaded and used in accordance with the GNU Public License and the license of primary data sources.deepBase v2.0 is freely available at


In vitro and in vivo  experimental studies performed so far have provided evidence for the biological effects of resveratrol on numerous pathways including oxidative stress, inflammation, mitochondrial dysfunction, apoptosis, pro-survival or angiogenesis that are implicated in the pathogenesis of these age-related ocular disorders. In this review, we provide a brief overview of current scientific literature on resveratrol, its plausible mechanism(s) of action, its potential use and current limitations as a nutritional therapeutic intervention in the eye and its related disorders.Resveratrol, a naturally occurring plant polyphenol found in grapes, is the principal biologically active component in red wine. Clinical studies have shown that resveratrol due to its potent anti-oxidant and anti-inflammatory properties are cardio-protective, chemotherapeutic, neuroprotective, and display anti-aging effects. Oxidative stress and inflammation play a critical role in the initiation and progression of age-related ocular diseases  that lead to progressive loss of vision and blindness.  Oxidative stress and inflammation play critical roles in the initiation and progression of age-related ocular diseases, including glaucoma, cataract, diabetic retinopathy, and macular degeneration that lead to progressive loss of vision and blindness if untreated ,2,3. Thetrans-stilbene) is a stilbenoid, a type of natural phenol, and a phytoalexin produced naturally by several plants in response to injury or when the plant is under attack by pathogens, such as bacteria or fungi [Resveratrol  of action, its potential use and current limitations as a nutritional therapeutic intervention in the eye and its related disorders. A literature search was performed using PubMed, Web of Knowledge and Google for articles published up to 2015. Specific keywords, such as resveratrol, eye, eye disease, ocular, ocular disease, glaucoma, cataract, macular degeneration, diabetes, anti-oxidant, anti-inflammatory were used in combination(s) to filter the searches. Relevant information pertaining to the focus of this review was included.Vaccinum species, including blueberries, bilberries, and cranberries are particularly rich sources [cis- and trans-resveratrol. The predominant form of resveratrol in grapes and grape juice is trans-resveratrol-3-O-β-glucoside (trans-piceid). Many wines also contain significant amounts of cis-resveratrol [Resveratrol is a polyphenol that is found in plants. Grapes, red wine, grape juice, peanuts, cocoa, and berries of  sources . Althoug sources . A myria sources . These c sources ,14. Resvveratrol . Estimatveratrol .Polygonum cuspidatum , red wine and grape extracts (from Vitis vinifera) are readily available on the market as dietary supplements. These supplements may contain anywhere from less than 1 milligram (mg) to 500 mg of resveratrol per tablet or capsule, but its safety and efficacy in the prevention of chronic disease in humans are unknown.Resveratrol from root extracts of trans-resveratrol in humans found that the serum level of unmetabolized resveratrol is very low after oral or intraperitoneal administration of the drug. Recently, Beaudeux and colleagues have published an excellent review providing insights into the metabolism, biological effects and toxicity of the use of resveratrol to treat pathological and metabolic diseases in humans [trans-resveratrol-3-O-glucoronide and trans-resveratrol-resveratrol-3-sulfate, respectively, and elimination of these metabolites [trans-resveratrol to healthy volunteers resulted in peak/maximal blood concentrations (Cmax) of total resveratrol  around 60 minutes later, at about 1.8-2 μmoles/L, depending on whether resveratrol was administered in wine, vegetable juice, or grape juice [Cmax, from 538 ng/mL (2.36 μmoles/L) to 1942 ng/mL (8.51 μmoles/L) in almost double the time, from 1.5 h to 2.8 h after intake, indicating a much slower absorption of the micronized form of resveratrol [in vitro experiments to elicit sustained biological effects raising substantial concern that the concentrations used in vitro and in animal models are not reasonably attainable in vivo.Pharmacokinetic studies of n humans . Althougabolites ,17. Prelpe juice ,17. The pe juice ,17. Conspe juice . Adminisveratrol ,19. Howeet al. [trans- and/or cis- forms of mono- and diglucuronides, mono- and disulfates and sulfoglucuronides from parent resveratrol, as well as equivalent conjugations of the microbiota-derived metabolite dihydro-resveratrol (DHRES). The activity of any specific resveratrol circulating metabolite is still unclear. Although DHRES has been reported to be the most abundant resveratrol-derived metabolite in colon from rats [Resveratrol bioavailability exhibits a high inter-individual variability independent of age and gender . Similaret al.  concludeet al.  and humaet al. ,24. Amonrom rats  and pigsrom rats , little The possible effect of the food matrix on resveratrol bioavailability has also been investigated. The main outcome has been that resveratrol-containing liquid formulations (either added or endogenous resveratrol) such as grape juice, vegetable juice, wine  show similar absorption figures; high-fat foods delayed absorption; and neither alcohol nor the flavonol quercetin affected resveratrol bioavailability .Cmax), time to Cmax, half-life and exposure measured by area under curve. These outputs can be dose and time dependent. Considering the fact that rapid absorption and metabolism of resveratrol is often believed to be a potential limitation of its activity and biological effects, it remains to be seen whether maximizing any of these parameters is important for the clinical efficacy of resveratrol. Nevertheless, with continued efforts in this direction numerous strategies have been described to improve the bioavailability of resveratrol, including use of micronized powders , combining resveratrol with other polyphenols targeted by key enzymes, such as cytochrome P450 (CYP), UDP-glucuronosyltransferase (UGT), and sulfotransferase (SULT) which conjugate resveratrol, use of resveratrol precursors or pro-drugs to maximize the bioavailability of free trans-resveratrol, use of alternative delivery routes beyond traditional oral administration or controlled release devices  to bypass gastrointestinal and hepatic metabolism, and nanotechnological formulations that have been reviewed elsewhere [The basic parameters associated with any drug activity are its maximal plasma concentration , and later by Nonomura in the 1960s from the Japanese knotweed Polygonumcuspidatum, had historically been used for remedial purposes in the traditional oriental medicine against various diseases including gonorrhea, athlete’s foot, suppurative dermatitis, and fungal skin diseases for its anti-microbial activity [Science publication by Jang et al. [Resveratrol, originally isolated by Takaoka in the 1940s from hellebore roots  and human intervention studies published in the most recent decades, highlighting the different biological significance and plausible mechanisms of action of resveratrol.A critical first step to delineate the mechanisms of drug action is to determine whether resveratrol mediates its effect by cell surface receptors or intracellular targets. Resveratrol is a hydrophobic compound, and has been demonstrated to be taken up by intestinal epithelium cells, hepatocytes and breast tumor cell lines ,36,37. A sulfate . Resverao cancer ,40,41, co cancer ,45,46,47o cancer ,49 disea in vivo ,51. An iongevity . Howeverongevity  and in fongevity . To esta of AMPK . It is eneficial ,57. Resvneficial . The myrneficial . In addi [et al.  has thortrans-) resveratrol [Studies in animal model have shown no apparent adverse effects on administration of high doses of  could increase the risk of bruising and bleeding when taken with anticoagulant drugs, such as warfarin and heparin; antiplatelet drugs, such as clopidogrel and dipyridamole; and non-steroidal anti-inflammatory drugs, including aspirin, ibuprofen, diclofenac, naproxen, and others.Resveratrol can inhibit human platelet aggregation in vitro . Therefoin vitro [Caraganachamlagu, a trimer of resveratrol, strongly inhibited CYP2C19-mediated omeprazole 5-hydroxylation and CYP3A4-catalyzed midazolam 1-hydroxylation with IC50 values of 0.93 and 1.2 μM, respectively [Cytochrome P450 3A4 (CYP3A4) is one of the most abundant CYP isoform enzymes, which catalyzes metabolism of most of the drugs available in the market affecting clearance and toxicity of the drug. Resveratrol has been shown to inhibit CYP3A4 activity in vitro  and in hin vitro . In a veectively . These tectively .Many studies have investigated the effects of resveratrol within the eye and its related disorders. Similar to the effects observed in other diseases, such as cancer, heart and neurodegenerative diseases (discussed above) the major biological actions on the eye include: anti-oxidative, anti-apoptotic, anti-tumorogenic, anti-inflammatory, anti-angiogenic and vasodilator. Studies investigating these effects and their potential role in the progression of eye diseases including glaucoma, cataract, age-related macular degeneration and diabetic retinopathy have been described in this section.Glaucomas are a group of progressive optic neuropathies characterized pathologically by apoptosis of retinal ganglion cells (RGCs) and resulting changes in the optic nerve head. Loss of RGCs, at least in part, is related to the level of intraocular pressure (IOP) as a consequence of blockage of aqueous outflow pathway through the trabecular meshwork. There may also be mitochondrial dysfunction in the RGCs, as a result of high levels of energy demand that may be difficult to meet during periods of intraocular pressure-induced metabolic stress. Although reduction of IOP is the only proven effective method to treat the disease, ocular hypotensive drops, laser trabeculoplasty and surgery may also be used to slow disease progression. Pathways involving oxidative stress, inflammation, mitochondrial dysfunction, glial cell dysfunction, and activation of apoptosis and cell survival are active areas of research to identify new potential drug targets ,64.et al. investigated the therapeutic effects of administration of the dietary supplement resveratrol on the expression of glaucoma markers in trabecular meshwork cells subjected to chronic oxidative stress [Luna e stress . The stue stress . The stuet al. [There is progressive loss of retinal ganglion cells (RGCs) in glaucoma and therefore neuroprotection of RGCs may have an impact on management of glaucoma. A recent study by Prihan and colleagues  investiget al.  investiget al.  emphasizet al. .2A and A3 AR antagonists [1 AR, at least in part. Treatment with topical steroids is known to increase IOP by increasing the resistance in the aqueous humor outflow pathways, which is also observed in POAG eyes [et al. has shown that resveratrol may be able to protect against retinal ischemia/reperfusion injury induced by high intraocular pressure (namely 120 mmHg for 60 min) by downregulation of MMP-9 and iNOS, and upregulation of HO-1 [Steroid-induced ocular hypertension (SIOH) and glaucoma is associated with increased extracellular deposition in trabecular meshwork and are treated in the same way. Two studies were recently published by Razali and group, evaluating the use of topical trans-resveratrol-induced intraocular pressure (IOP) reduction in rats with SIOH . The firagonists . The stuagonists . These sOAG eyes . Therefo of HO-1 .in vivo in experimental glaucoma models.The role of mitochondrial dysfunction in the pathogenesis of glaucomatous neurodegeneration has been of considerable interest in the recent past. Chen and colleagues have evaluated the role of resveratrol-triggered mitochondrial biogenesis for preventing apoptosis in a retinal ganglion cell line RGC-5 . Serum dAge-related macular degeneration (AMD) is closely associated with choroid-Bruch’s membrane (BM)-retinal pigment epithelium (RPE)-neuroretina (NR) component in the posterior part of the eye in the aging population . “Dry” Ain vitro [in vitro, which is highly relevant in autoimmune-associated retinopathies [2+ ion concentration; and up-regulated SIRT1 and Ku70 anti-apoptotic proteins leading to suppression of BAX translocation within the mitochondria [et al. reported a protective effect of resveratrol against light-induced retinal degeneration, a model used to investigate visual cell apoptosis, by reversing the activation of retinal activating protein-1 (AP-1) and inhibition of SIRT1 activation up-regulated by light exposure [Resveratrol prevents oxidative stress-induced and sodium iodate-induced apoptosis of human RPE cells in vitro . Moreovein vitro ,80. Resvopathies . It was chondria ,82. In aexposure . AP-1 reexposure . The antin vitro studies, there is a limited evidence for the anti-oxidative effect of resveratrol in vivo that may be relevant to AMD. Resveratrol was reported to exhibit a dose-dependent protective effect against hydrogen peroxide-induced cytoxicity in human retinal D407 RPE cells by increasing superoxide dismutase, glutathione peroxidase, and catalase activities that inhibited the levels of intracellular ROS [et al. in human lens epithelial cells [Unlike many ular ROS . A similal cells . Althouget al. reported broad bilateral improvements in ocular structure and function in three patients with AMD over a long-term follow-up of two to three years suggesting its efficacy in AMD [Pathogenic late stages of AMD are often characterized by choroidal angiogenesis. The anti-inflammatory and anti-oxidative properties of resveratrol are believed to reduce the incidence of CNV. Nagineni and colleagues investigated the inhibitory actions of resveratrol on inflammatory cytokine, transforming growth factor-beta (TGF-β) and hypoxia induced VEGF secretion by human RPE cells to demonstrate utility of resveratrol as nutraceutical supplement in controlling CNV processes in AMD . The stuy in AMD .Resveratrol positively affects mitochondrial biogenesis and has been shown to protect RPE cells against acrolein-induced oxidative cytotoxicity by increasing mitochondrial bioenergetics .et al. investigated the ability of resveratrol to inhibit RPE cell inflammation caused by hyperglycemia in vitro [Diabetic retinopathy (DR) is a diabetes-induced microangiopathy affecting the retinal vasculature due to poor metabolic control of circulating blood glucose levels characterized by increased inflammatory response, ischemia, progressive RPE cell degeneration leading to malfunction of blood-retinal barrier and loss of vision . Supplemin vitro . The stuin vitro .et al. demonstrated a role for resveratrol in rat against selenite-induced cataract formation by stimulating an increase in the levels of reduced glutathione (GSH) and reduced concentrations of malondialdehyde (MDA), a marker of lipid peroxidation, in rat lenses and erythrocytes [et al. have demonstrated effectiveness of resveratrol as a potential treatment in in vivo and in vitro rat models of oxygen-induced retinopathy via nitric oxide- (NO) mediated pathways, suggesting a protective role in retinopathy of prematurity (ROP) in prematurely born infants [Few studies have also indicated the potential preventative role of resveratrol in other eye related diseases. Doganay hrocytes . Adminishrocytes . Resverahrocytes . Similarhrocytes . In anot infants . Resvera infants .in vitro and animal experimental studies conducted so far have provided evidence for the biological effects of resveratrol on several pathways including oxidative stress, inflammation, mitochondrial dysfunction, apoptosis, pro-survival or angiogenesis that are implicated in the pathogenesis of various eye diseases discussed above. These studies have also suggested many possible direct or indirect molecular targets and mechanisms of action mediating them.The numerous Although a wide variety of pharmacologic activities of resveratrol has been documented, it is still unclear how the same drug causes different or even opposite effects in different cell types and in different diseases. For example, resveratrol causes cell death in tumor cells but is effective as an anti-apoptotic or protective agent in nerve cells . Similari.e., “resveratrol cannot exert benefits because it is rapidly metabolized and its presence in the bloodstream is negligible to justify any effect”. Goldberg et al. [in vitro effects of free resveratrol could not be relevant as it was absorbed as conjugates. Azorín-Ortuño et al. [i.e., in vitro, exposing cells to high doses of resveratrol (and short follow-ups to maximize effects in a short time), which are up to 100 times higher than peak plasma concentrations observed in humans, and in animal models given very high (non-dietary) doses of resveratrol [actual metabolite” responsible for the diverse effects exerted by resveratrol and provide knowledge on the optimal effective concentrations of resveratrol that could be beneficial and yet safe to the subject.The poor bioavailability of resveratrol is another major drawback for this molecule and even a recurrent criticism used by some physicians or pharmacologists, g et al. , in 2003o et al.  coined tveratrol . At presveratrol . The “acveratrol ,100. Thein vitro experiments and animal models of several ocular diseases. However, data in human research is lacking and it is essential to carry out comprehensive randomized clinical trials on both the preventive potential, efficacy and safety of resveratrol in different diseases before such claims can be validated. There are a number of ongoing clinical trials dealing with resveratrol [Based on current literature, it would seem that resveratrol may have the potential to ameliorate secondary conditions even as it is used to treat a primary disease via the plausible biological mechanisms demonstrated using veratrol  that wil


Initial success of inhibitors targeting oncogenes is often followed by tumor relapse due to acquired resistance. In addition to mutations in targeted oncogenes, signaling cross-talks among pathways play a vital role in such drug inefficacy. These include activation of compensatory pathways and altered activities of key effectors in other cell survival and growth-associated pathways.p1-model to infer posterior probabilities of gene-pairs in networks derived from the gene expression datasets of ErbB2-positive breast cancer cell-lines . Using this computational framework, we searched for cross-talks between EGFR/ErbB and other signaling pathways from Reactome, KEGG and WikiPathway databases that contribute to lapatinib resistance. We identified 104, 188 and 299 gene-pairs as putative drug-resistant cross-talks, respectively, each comprised of a gene in the EGFR/ErbB signaling pathway and a gene from another signaling pathway, that appear to be interacting in resistant cells but not in parental cells. In 168 of these (distinct) gene-pairs, both of the interacting partners are up-regulated in resistant conditions relative to parental conditions. These gene-pairs are prime candidates for novel cross-talks contributing to lapatinib resistance. They associate EGFR/ErbB signaling with six other signaling pathways: Notch, Wnt, GPCR, hedgehog, insulin receptor/IGF1R and TGF- β receptor signaling. We conducted a literature survey to validate these cross-talks, and found evidence supporting a role for many of them in contributing to drug resistance. We also analyzed an independent study of lapatinib resistance in the BT474 breast cancer cell-line and found the same signaling pathways making cross-talks with the EGFR/ErbB signaling pathway as in the primary dataset.We propose a computational framework using Bayesian modeling to systematically characterize potential cross-talks among breast cancer signaling pathways. We employed a fully Bayesian approach known as the Our results indicate that the activation of compensatory pathways can potentially cause up-regulation of EGFR/ErbB pathway genes (counteracting the inhibiting effect of lapatinib) via signaling cross-talk. Thus, the up-regulated members of these compensatory pathways along with the members of the EGFR/ErbB signaling pathway are interesting as potential targets for designing novel anti-cancer therapeutics.The online version of this article (doi:10.1186/s12918-014-0135-x) contains supplementary material, which is available to authorized users. Cancer development involves a series of events, ranging from tumorigenesis to metastasis, each of which may be caused by perturbations in crucial signal transduction pathways. Recently, drugs (inhibitors) specifically targeting critical components of signaling pathways known to be up-regulated in specific cancers have been used in the clinic. However, success of these inhibitors is limited by the intrinsic potential of cancer cells to acquire drug resistance. Recent advances in both clinical and laboratory research have reported that cancer cells may adopt several mechanisms against particular treatments including adjusting the signaling circuitry, activation of alternative pathways and cross-talks among various pathways to overcome the effects of inhibitors ,2. Resisde novo and acquired  possibilities, we found 10,811 gene-pairs  in our primary dataset, have some overlap with our secondary dataset.To further illustrate our method, we analysed a second dataset GSE16179) containing gene expression profiles of breast cancer cell-line BT474 under two conditions  [179 contae Census , there wThere were 78 genes involved in these sets of 83, 133 and 277 putative cross-talks. We performed a similar Netwalker analyses with these 78 genes as we did for the dataset GSE38376, and found 37 genes  resistance. We hypothesized that gene-pairs  that can potentially cause drug-resistance have a high probability of occurring in the resistant condition(s) but a low probability in parental conditions. We employed a fully Bayesian statistical model: a special class of Exponential Random Graph Model known as the n values  of resisling see .Our results primarily focus on compensatory signaling pathways i.e. Notch signaling, Wnt signaling, GPCR signaling, and IR/IGF1R signaling, which cross-talk with EGFR/ErbB signaling to reduce the inhibiting effect of lapatinib. We present additional literature evidence that the identified cross-talks of the above compensatory signaling pathways with EGFR/ErbB signaling may contribute to drug-resistance by maintaining key cell survival and/or proliferation signals in common down-stream pathways, including PI3K/Akt signaling [et al. [MDM2:STK11 cross-talk between EGFR/ErbB and IGF1R signaling, where STK11  phosphorylates and activates AMPK in absence of glucose [et al. by finding signaling cross-talks between EGFR/ErbB and IGF1R pathways.Komurov et al.  hypotheset al. . Here, b glucose . Again,  glucose . Thus ouμM and 1.0 μM) with those of all the samples in resistant conditions . However, we conducted another experiment on both of our primary  and secondary datasets  in which we first identified genes dysregulated in treatment vs basal conditions in parental samples and then checked if those genes were reversely changed in treatment conditions in resistant samples. To that end, for each sample, first we calculated the fold-change(s) of parental treatment condition(s) compared to parental basal condition, and then we calculated the fold-changes of resistant basal and resistant treatment conditions compared to parental basal condition , and for that particular sample, expressions were reversely changed  in all the resistant treatment conditions , we compared the expression changes of all the samples in parental conditions (basal, 0.1 et al. [Currently, our network modeling only considers undirected edges among genes. In future we would like to generalise the approach to identify directed and indirect interactions among genes. In network modeling, a combination of both direct and indirect relationships among gene-pairs was found to provide better insights into biological systems in our previous studies . The ratet al. . Other hOur proposed computational framework is able to predict putative cross-talks among signaling pathways that play a role in drug resistance in two breast cancer cell-lines, SKBR3 and BT474. Our framework could also be useful for other types of cancer to enhance understanding of the role of signaling cross-talks in drug resistance. Most importantly, we believe our method can be used to find a range of compensatory pathways that nullify/reduce the inhibiting effects of drugs via cross-talk with targeted pathways. These novel compensatory pathways can be further considered as novel targets for single or combination therapies.


Resting-state fMRI (R-fMRI) has shown considerable promise in providing potential biomarkers for diagnosis, prognosis and drug response across a range of diseases. Incorporating R-fMRI into multi-center studies is becoming increasingly popular, imposing technical challenges on data acquisition and analysis, as fMRI data is particularly sensitive to structured noise resulting from hardware, software, and environmental differences. Here, we investigated whether a novel clean up tool for structured noise was capable of reducing center-related R-fMRI differences between healthy subjects. We analyzed three Tesla R-fMRI data from 72 subjects, half of whom were scanned with eyes closed in a Philips Achieva system in The Netherlands, and half of whom were scanned with eyes open in a Siemens Trio system in the UK. After pre-statistical processing and individual Independent Component Analysis (ICA), FMRIB's ICA-based X-noiseifier (FIX) was used to remove noise components from the data. GICA and dual regression were run and non-parametric statistics were used to compare spatial maps between groups before and after applying FIX. Large significant differences were found in all resting-state networks between study sites before using FIX, most of which were reduced to non-significant after applying FIX. The between-center difference in the medial/primary visual network, presumably reflecting a between-center difference in protocol, remained statistically significant. FIX helps facilitate multi-center R-fMRI research by diminishing structured noise from R-fMRI data. In doing so, it improves combination of existing data from different centers in new settings and comparison of rare diseases and risk genes for which adequate sample size remains a challenge. Resting-state functional Magnetic Resonance Imaging (R-fMRI) has become an important tool in neuroimaging research to examine Resting-State Networks (RSNs) in normal brains, during the aging process and in various neurological disorders FMRI research has certain challenges, such as problems regarding sample size in clinical and at-risk populations. Multi-center analysis may help to solve these limitations, but has been shown to be difficult to perform for (R-)fMRI. Specifically, differences between groups may not always be attributable to the feature of interest, such as disease or gene carrier status, but may also be secondary to scanner hardware differences , software differences , and environmental differences (radio-frequency noise)  ICA-based X-noiseifier (FIX) is a plug-in to FMRIB's Software Library (FSL) that is able to automatically classify and remove structured noise-components  physiological noise, etc.) from R-fMRI data, once it has been trained through hand-classifications  and progranulin (GRN), risk genes for Frontotemporal Dementia (FTD), on the brain , a risk gene for Alzheimer's Disease (AD), on the brain  and from subjects scanned at the University of Oxford Centre for Clinical Magnetic Resonance Research (OCMR). The LUMC data (referred to in this article as the “Dutch” sample) consisted of 36 subjects from the control group of an earlier R-fMRI study investigating the effect of The English subjects were selected from a larger cohort in order to match the Dutch subjects in age, gender and sample size.MAPT- and GRN-non-carriers were selected from a pool of 160 healthy first-degree relatives of FTD patients with either a MAPT- or GRN-mutation. It is assumed that the non-carriers from these families have the same risk for dementia as the general population. Thirty-six APOE ε4-non-carriers, scanned at the OCMR, were selected from the general population and the data from most (30/36) were reported in previous studies , corticosteroid therapy, youth diabetes therapy, memory complaints, and current or past neurologic or psychiatric disorders for the English sample.All participants provided written informed consent, and ethical approval for data acquisition was obtained from National Research Ethics Service Committee South Central—Oxford C (Oxford data) and the Medical Ethical Committees in Rotterdam and Leiden (Leiden data).LUMC scans were acquired using a Philips 3.0T Achieva MRI scanner with an 8-channel SENSE head coil. OCMR scans were acquired using a Siemens 3.0T Trio scanner with a 12-channel head coil. Participants were instructed to keep their eyes closed (LUMC) or open (OCMR), to think of nothing in particular (OCMR) and to remain awake. The scan parameters used for the high-resolution 3D anatomical T1-weighted and for the R-fMRI T2*-weighted images are shown in Table http://www.fmrib.ox.ac.uk/fsl) tools were used for all data analyses  > 2.3), then at the temporal power spectrum and lastly at their time-series. Unthresholded spatial maps were examined when necessary , a true-negative rate (TNR) and a composite measure ((3 · TPR + TNR)/4) for a range of thresholds (used to determine the binary classification of components since FIX's output is probabilistic). After checking the TPR, TNR and the composite measure, the optimal threshold  was chosen and the classifier was applied to all subjects' data using this threshold in order to classify and remove the structured noise components from the data  analyses were run using MELODIC. In order to qualitatively compare FIX's effect on GICA components, GICA was run on combined English and Dutch data before application of FIX (GICA-1) and on combined English and Dutch data after application of FIX (GICA-2). For statistical analysis of FIX's effect on the multi-center differences, GICA was carried out on all data combined (GICA-3). Consequently, the data used for this analysis (GICA-3) contained four subgroups: Dutch subjects with and without use of FIX, and English subjects with and without use of FIX. R-fMRI data were temporally concatenated across individuals to create a single 4D data set. The data were whitened and principle component analysis was used to project the data into a 25-dimensional subspace, matching many previous R-fMRI studies . Age and years of education were added to the analysis as confound regressors. Non-paramatric permutation-based testing was done by running 5000 random permutations using the randomize algorithm, a tool based on the Freedman-Lane methods within FSL . Demographic variables were tested using independent samples Demographic information for the Dutch and English subjects is shown in Table Table 1A: numbers 6, 22, 23] and brain stem/vascular artifacts , sagittal sinus artifact ) and others are “pushed back” . Both observations rely on the same mechanism: FIX removes variance explained by noise components from the data. As MELODIC shows components in order of decreasing explained variance, the removal of variance explained by noise components results in higher component numbers or even exclusion.Figure Spatial maps that were used as spatial regressors for dual regression (GICA-3) are shown in Figure All RSNs' combined results based on PE-driven spatial maps are shown for family-wise error-corrected group differences before the use of FIX Figure , group dBefore the use of FIX, large areas of statistically significant differences were shown in all (15) RSNs. After applying FIX, the size, and number of areas with significant differences between groups was strongly reduced: only 7/15 RSNs showed statistically significant differences and the number of significantly different voxels was reduced by 98%. The RSN with the largest area of significant differences after using FIX was the primary/medial visual network (PVN), containing 85% of all significantly different voxels after applying FIX. This network is associated with a difference in scan protocol (eyes open vs. closed) and showed greater activation in English than in Dutch subjects.The interaction between the use of FIX and site-differences was significant in 13/15 RSNs.Dual regression results based on Z-stat-driven spatial maps were similar on visual inspection.Additionally, for a more qualitative view of the results, Supplemental Figure In this study, FIX was found to be helpful in the comparison of multi-center R-fMRI data. FIX significantly reduces structured noise resulting from hardware, software, and environmental differences in a multi-center group comparison, as demonstrated by Figure Dual regression is usually run using PE-driven spatial maps; alternatively, Z-stat-driven spatial maps can be used. Our results using PE- and Z-stat-driven spatial maps were similar on visual inspection, suggesting that the use of FIX is of value for both types of analysis. However, in order to assess whether FIX works better for either one, a more specific analysis is required.Structured noise in fMRI has various origins: hardware differences , software differences  and radio-frequency noise (Casey et al., Although eyes-open and eyes-closed differences cannot be mathematically disentangled from site/scanner differences, we suggest that the remaining differences in the PVN after using FIX are a manifestation of this protocol discrepancy since the differences in all other networks are substantially reduced. Recently, a number of studies have investigated the effect of eyes-open vs. eyes-closed conditions on functional connectivity without yet reaching a clear consensus. For example, reduced activation (Feige et al., Whilst groups were matched for age and sex, there was a significant difference in level of education. This may be attributable to the recruitment protocols. The English recruitment protocol selected subjects from the general population near Oxford, a relatively highly educated region (Filippini et al., Previous studies on multi-center fMRI primarily focused on data collected using standardized protocols. Glover et al.  argue thPrevious studies using FIX have considered the theoretical and practical use of spatial ICA, classifier training and noise detection (Salimi-Khorshidi et al., The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


It consists of selected microarray and RNA-sequencing studies from ArrayExpress, which have been manually curated, annotated with ontology terms, checked for high quality and processed using standardised analysis methods. Since the last update, Atlas has grown seven-fold (1572 studies as of August 2015), and incorporates baseline expression profiles of tissues from Human Protein Atlas, GTEx and FANTOM5, and of cancer cell lines from ENCODE, CCLE and Genentech projects. Plant studies constitute a quarter of Atlas data. For genes of interest, the user can view baseline expression in tissues, and differential expression for biologically meaningful pairwise comparisons—estimated using consistent methodology across all of Atlas. Our first proteomics study in human tissues is now displayed alongside transcriptomics data in the same tissues. Novel analyses and visualisations include: ‘enrichment’ in each differential comparison of GO terms, Reactome, Plant Reactome pathways and InterPro domains; hierarchical clustering (by baseline expression) of most variable genes and experimental conditions; and, for a given gene-condition, distribution of baseline expression across biological replicates.Expression Atlas ( Expression Atlas  is a furHigh-quality microarray and RNA-sequencing (RNA-seq) data in Expression Atlas continue to come from ArrayExpress , which ahttp://www.ebi.ac.uk/gxa/baseline/experiments), reporting transcript abundance estimates for each gene in healthy or untreated tissues, cell types or cellular components from carefully selected large RNA-seq experiments and (ii) information about the changes in transcript abundance between two different conditions, such as normal and disease.Expression Atlas consists of two components—(i) a large baseline expression component (http://www.ebi.ac.uk/gxa/plant/experiments), e.g. rice, wheat, maize and Arabidopsis, including 7 baseline studies reporting expression in tissues, strains and cultivars. 97 differential and 3 baseline experiments in Atlas study cancer.Since the last update, we have included in the baseline Atlas a number of important projects such as Human Protein Atlas  and The Atlas’ ability to display expression across all tissues and all baseline studies next to each other in a single, intuitive interface makes it easy for the user to spot corroborating patterns of expression across multiple ‘omics studies. All differential expression data are now also available for further analysis as R objects.Annotations reported by expression studies may become defunct due to addition of new transcribed loci or dropping invalid entries in updated genomic references. To address this, Atlas release cycle is synchronised with that of Ensembl , Ensemblhttp://www.ebi.ac.uk/gxa/baseline/experiments, 36376 assays) in tissues from Human Protein Atlas (http://www.ebi.ac.uk/gxa/experiments/E-MTAB-2836), GTEx (http://www.ebi.ac.uk/gxa/experiments/E-MTAB-2919), FANTOM5 (http://www.ebi.ac.uk/gxa/experiments/E-MTAB-3358), in cancer cell lines from ENCODE (http://www.ebi.ac.uk/gxa/experiments/E-GEOD-26284), Cancer Cell Line Encyclopaedia  and Genentech (http://www.ebi.ac.uk/gxa/experiments/E-MTAB-2706) projects, as well as differential expression for manually curated comparisons (4287 as of August 2015). Table Oryza sativa japonica cv. Nipponbare  variety: http://www.ebi.ac.uk/gxa/experiments/E-MTAB-1625 (RNA-seq) and http://www.ebi.ac.uk/gxa/experiments/E-MTAB-1624 (microarray), allowing for comparison of expression obtained from the same physical samples using different technologies. This line was chosen because the reference rice genome was also sequenced from it. Users can also view the baseline expression profile of genes from a gene family or a given pathway from Plant Reactome Wikipathways. For example, Figure PIN) and auxin influx (AUX) gene family members participating in Auxin (IAA) transport pathway in a plant cell.At the time of writing, Expression Atlas contains highly curated data from 1572 studies (69239 assays), incorporating RNA-seq based baseline expression (http://www.ebi.ac.uk/gxa/experiments/E-PROT-1) as additional information to the transcriptomics data in the baseline component of Expression Atlas only, shown side by side for the corresponding tissues. This proteomics study consists of re-analysed mass spectrometry raw data from the draft map of the human proteome  set and a ‘test’ set (e.g. ‘diseased’ or ‘mutant’). The differential analysis is now performed using DESeq2  with indUsers now have more tools at their disposal to assess the accuracy of expression data reported by Atlas: (i) the number of biological replicates is now reported for a given baseline condition, or on either side of a differential comparison; (ii) for a given baseline condition, quantile normalisation is used to make distributions of expressions in each biological replicate the same—prior to averaging gene expression levels across biological replicates; (iii) for a given gene-condition, users can view a box plot of variability of baseline expression across biological replicates, providing them with an impression of how representative the reported median expression level is.Expression Atlas remains committed to the stringent quality control of raw experimental data and design, reported in the previous update. Since then we have automated quality control of RNA-seq data, that involves exclusion of corrupted FASTQ files and those with an insufficient number of reads after filtering for poor quality and contamination. As in the case of microarray outlier array removal, removing poor quality data files may lead to the exclusion of affected differential comparisons, baseline conditions or even whole experiments from Atlas.The proteomics data analysis methods are described in the Human Proteome Label Free Analysis section of the supporting material.Expression Atlas search interface allows for querying one or more genes or proteins from a selected species. The user can also add search filters for sample attributes and experimental factors, taking full advantage of ontology-driven query expansion. For example, searching for disease lymphoma will return expression data from samples of not only lymphoma itself, but also from its subtypes and closely related diseases, e.g. Hodgkin's lymphoma or acute myelogenic leukemia. Using the same interface, both baseline and differential components of Expression Atlas are queried by default. The Atlas interface displays search results from all tissues and all baseline studies making it possible to find patterns of expression across a wide variety of studies Figure . We are Various novel analyses and visualisations have been implemented in Atlas. For example, the overlap between the set of differentially expressed genes in each Atlas comparison, and Reactome and Plant Reactome pathways, GO terms and InterPro domains is now assessed using Fisher's test with multiple testing correction . The reshttps://github.com/gxa/atlas/blob/master/web/src/main/javascript/heatmap/README.md) and can be integrated in any third-party site, provided the bioentity identifiers match those of the Atlas.Expression data from Atlas are now viewable as tracks on Ensembl, Ensembl Genomes and Gramene genome browsers. Baseline expression data from Atlas are also automatically included in Ensembl, Ensembl Genomes, Gramene Ensembl Plants, Reactome and Plant Reactome, via javascript-based widgets. The widgets are easily accessible (http://dcc.blueprint-epigenome.eu/), NIH Epigenomic Roadmap (http://www.hipsci.org/).We plan to include in Atlas the latest data from ENCODE, GTEx version 5, Blueprint  list of comparisons in which the user provided gene set is ‘enriched’.For a given gene within a single study, we will enable the user to find other genes of similar expression profile across experimental conditions or differential comparisons.We plan to make available baseline expression of orthologues in tissues.We plan to provide exon quantifications for all RNA-seq experiments. We will also re-visit the topic of splice-variant expression quantification by benchmarking several splice-variant expression quantification methods , with tWe plan to extend our analysis pipelines and visualisation methods to adequately annotate, quality control and visualise gene expression data from single-cell RNA-seq studies.We plan to enable handling of additional factors or blocking effects for baseline expression in the near future.We plan to make baseline expression data available for download as R objects. We will also create an R package in Bioconductor  for acceWe are always listening to the feedback from our users, and the future plans will be adjusted according to the user requirements.Supplementary Data are available at NAR Online.


Under the optimistic assumption of high-prophylactic HPV vaccine coverage, a significant reduction of cancer incidence can only be expected after decades. Thus, immune therapeutic strategies are needed for persistently infected individuals who do not benefit from the prophylactic vaccines. However, the therapeutic strategies inducing immunity to the E6 and/or E7 oncoprotein of HPV16 are more effective for curing HPV-expressing tumours in animal models than for treating human cancers. New strategies/technologies have been developed to improve these therapeutic vaccines. Our studies focussed on preparing therapeutic vaccines with low-cost technologies by DNA preparation fused to either plant-virus or plant-toxin genes, such as saporin, and by plant-produced antigens. In particular, plant-derived antigens possess an intrinsic adjuvant activity that makes these preparations especially attractive for future development. Additionally, discrepancy in vaccine effectiveness between animals and humans may be due to non-orthotopic localization of animal models. Orthotopic transplantation leads to tumours giving a more accurate representation of the parent tumour. Since HPV can cause cancer in two main localizations, anogenital and oropharynx area, we developed two orthotopic tumour mouse models in these two sites. Both models are bioluminescent in order to follow up the tumour growth by imaging and are induced by cell injection without the need to intervene surgically. These models were utilized for immunotherapies with genetic or plant-derived therapeutic vaccines. In particular, the head/neck orthotopic model appears to be very promising for studies combining chemo-radio-immune therapy that seems to be very effective in patients. All cervical cancers and precancerous lesions (CIN III) are caused by HPV infection. Since the early findings in the 1970s of HPV in cervical cancer by zur Hausen’s group, HPV has been linked to other anogenital cancers including vulvar, penile, and anal neoplasia. Recently, high-risk HPV (HR-HPV) infection has been detected in head and neck cancers (HNCs), with high frequency in oropharynx and tonsils, unveiling another aetiological factor in addition to tobacco and alcohol 55]. ThisAlthough this preliminary work regarding AT-84 E7 model for immunotherapy was not designed to assess immunological responses, the results provided information on the efficacy of heterologous prime-boost regimens compared with homologous prime-boost regimens, as reported in previous studies , 56. MicHowever, several aspects need to be improved in order to have a completely reliable model. For instance, information on the biological significance of the E7 expression in these tumours is lacking, but preliminary data indicate that the presence of E7 can improve cell growth rate. Nevertheless, our model holds a valid place in monitoring responses to immunotherapy, as it is orthotopic and derives from naturally occurring OSCC.In conclusion, we strongly believe that our oral HPV-associated mouse tumour represents an innovative, realistic, and new pre-clinical model for HPV-related OSCC. Moreover, the possibility of applying chemo-radiotherapy to this model together with easy surgical removal of tumour masses offers new perspectives to test current available patient therapy in a pre-clinical model. It is well known that the better prognosis of HPV-positive OSCC could allow less aggressive chemo-radiotherapy, and in this regard, our model will be very useful, and we are performing several protocols of combined therapy (chemo/radio and immunotherapy). Furthermore, the localization of this tumour permits easy access to intratumoural therapy. Preliminary interesting results of E7GGG/SAP DNA intratumoural injection are shown in Fig. Our studies are aimed at the development of low-cost technologies, such as DNA vaccines as well as plant-produced vaccines, and have proven that these immunotherapies are ready for clinical use. The oral pre-clinical model of HPV-associated cancer will have a pivotal role in designing new combined intervention in HPV-positive OSCC. Ongoing works is aimed at the development of new DNA/plant-derived vaccines against other HPV targets like the E5 oncogene of HR-HPV  in assoc


A huge amount of associations among different biological entities  are scattered in millions of biomedical articles. Systematic analysis of such heterogeneous data can infer novel associations among different biological entities in the context of personalized medicine and translational research. Recently, network-based computational approaches have gained popularity in investigating such heterogeneous data, proposing novel therapeutic targets and deciphering disease mechanisms. However, little effort has been devoted to investigating associations among drugs, diseases, and genes in an integrative manner.We propose a novel network-based computational framework to identify statistically over-expressed subnetwork patterns, called network motifs, in an integrated disease-drug-gene network extracted from Semantic MEDLINE. The framework consists of two steps. The first step is to construct an association network by extracting pair-wise associations between diseases, drugs and genes in Semantic MEDLINE using a domain pattern driven strategy. A Resource Description Framework (RDF)-linked data approach is used to re-organize the data to increase the flexibility of data integration, the interoperability within domain ontologies, and the efficiency of data storage. Unique associations among drugs, diseases, and genes are extracted for downstream network-based analysis. The second step is to apply a network-based approach to mine the local network structure of this heterogeneous network. Significant network motifs are then identified as the backbone of the network. A simplified network based on those significant motifs is then constructed to facilitate discovery. We implemented our computational framework and identified five network motifs, each of which corresponds to specific biological meanings. Three case studies demonstrate that novel associations are derived from the network topology analysis of reconstructed networks of significant network motifs, further validated by expert knowledge and functional enrichment analyses.We have developed a novel network-based computational approach to investigate the heterogeneous drug-gene-disease network extracted from Semantic MEDLINE. We demonstrate the power of this approach by prioritizing candidate disease genes, inferring potential disease relationships, and proposing novel drug targets, within the context of the entire knowledge. The results indicate that such approach will facilitate the formulization of novel research hypotheses, which is critical for translational medicine research and personalized medicine. Semantic MEDLINE is a knowledge base consisting of associations automatically extracted from MEDLINE by integrating document retrieval, advanced natural language processing (NLP), and automatic summarization and visualization [A large amount of associations among biomedical entities are scattered in biomedical literature. Systematic analysis of such heterogeneous data provides biomedical scientists with unprecedented opportunities to infer novel associations among different biological entities in the context of personalized medicine and translational research studies. MEDLINE  . The semhttp://www.ncbi.nlm.nih.gov/geo/). In total, 170,027 interactions between diseases and drugs were considered significant, including 645 disease-disease, 5,008 disease-drug, and 164,374 drug-drug associations. These expression-based associations among diseases and drugs could serve as a backend knowledge base to facilitate discovery. Bauer-Mehren et al. [In the last decade, network-based computational approaches have gained popularity and become a new paradigm to investigate associations among drugs, diseases, and genes. Applications of these approaches include disease gene prioritization -5, identn et al.  developen et al.  proposedNetwork-based computational approaches enable us to analyze heterogeneous networks such as drug-disease-gene networks by decomposing them into small subnetworks, called network motifs (NMs) . NMs areIn this paper, we propose a network-based computational framework to analyze the complex network formed by a large amount of associations. We focus on a heterogeneous drug-disease-gene network derived from Semantic MEDLINE and investigated underlying associations using network-based systems biology approaches. Three case studies demonstrate that our approach has potential to facilitate formulization of novel research hypotheses, which is critical for translational medicine research. In the following, we first present Materials and methods. We then describe the results and case studies in detail.To comprehensively investigate the integrated drug-disease-gene network formed by associations available in Semantic MEDLINE, we propose the following two-step computational framework: 1) extraction and optimization of drug-disease-gene network in Semantic MEDLINE; (2) network topology analysis of this heterogeneous network at two levels: statistics and degree distribution of high-confidence association networks, and distinct pattern detection at NM level. In this section, we first describe the steps to extract association network data from MEDLINE database, followed by a description of the proposed network-based approach to investigate this heterogeneous drug-disease-gene association network. Figure  extractiSemantic MEDLINE currently contains more than 56 million associations extracted from MEDLINE citations and consists of eight tables, including concepts, concept semantic types, concept translations, predication, predication arguments, and sentences. Data from different tables need to be joined in order to obtain information for a particular association between two entities. The database contains an all-embracing joined table that provides information about associations , and their source PubMed IDs (PMIDs).http://d2rq.org/d2r-server). This mapping file specifies the mappings between those six relational database table schemas and the output RDF graphs [We optimize and reorganize the relevant data in Semantic MEDLINE into the Resource Description Framework (RDF) format. Based on the UMLS semantic types and groups , we extrF graphs . A detaiF graphs . These sSince the extraction accuracy of associations in Semantic MEDLINE is about 77%  , a filteNetwork motifs are topologically distinct subnetwork patterns that are present more frequently in true networks than in random networks . They arz score is calculated using the following equation:In this study, we extend network motif analysis to the disease-drug-gene network. Six different types of associations among drugs, diseases, and genes are integrated into a heterogeneous disease-drug-gene network. In this network, nodes represent biomedical entities stored in the RDF triples , and edges represent associations between two biomedical entities . For simplicity, we consider all associations as undirectional association relationships in this study, discarding the directionality and types in the original RDF graph. In other words, as long as there is an association between two nodes, we consider there is an edge between these two nodes. We hypothesize that even within such simplified disease-drug-gene association network, network motifs in the network can (1) represent basic inter-relationships among diseases, drugs, and genes; (2) reflect a framework in which particular functions are achieved efficiently. Specifically, we focus on three-node network motifs in this disease-drug-gene network since they are the building blocks for larger size network motifs (number of nodes > 3) . All conNreal is the number of times one three-node subnetwork is detected in the real network, Nrand is the mean number of times this subnetwork is detected in 1000 randomized networks, and σrand is the standard deviation of the number of times this subnetwork is detected in randomized networks. The p value of a motif is the number of random networks in which it occurs more often than in the original networks, divided by the total number of random networks. A pattern with p ≤ 0.05 is considered statistically significant. This network motif discovery procedure is performed using the FANMOD tool [where MOD tool .It has been shown that in gene regulatory networks, for each network motif, the majority of matches overlap and aggregate into homologous motif clusters . Many ofWe constructed a drug-disease-gene network with the following two steps:First, we extracted unique association data from Semantic MEDLINE. Using a use-case driven database optimization approach developed in our previous work , we extrSecond, we constructed association related data involving FDA-approved drugs. We applied the filtering strategy discribed in the Materials and methods section to extract association data involving FDA-approved drugs from the unique association data set. As shown in the “Associations Involving FDA-approved Drugs” column in Table The network motif analysis was performed on the integrated disease-drug-gene network obtained in Section An integrated drug-disease-gene network reconstructed from Semantic MEDLINE. Since the network contains thousands of associations among 865 drugs, 2791 genes, and 3578 diseases  in Figure http://www.ingenuity.com/). These genes are enriched in kidney-related disease categories . The only difference between NM 1 and NM 4 is that NM 4 doesn’t have the associations between two diseases themselves. We extracted all associations among 2,664 diseases and 1,122 genes in NM 4. In total, there are 860 disease-disease, 17,242 disease-gene, and 310 gene-gene associations in this subnetwork  suggests another association pattern between diseases and drugs, in which two diseases associated with each other are targets for the same drug. It has been shown by Suthram et al.  that disThree-gene network motif (NM 3) was also identified in this heterogeneous network. This NM is a very common motif pattern in the protein-protein interaction network or gene regulatory network ,38, indiSince all five network motifs identified involve only two out of three node types, we further investigated whether the networks involving only two node types can generate the same NMs. To accomplish that, we performed NM analysis on disease-gene, disease-drug and gene networks respectively. Not all NMs detected in the complete network can be detected in disease-gene, disease-drug and gene networks respectively , significant NMs, or clustered subnetworks/modules. In this work, we focus on identifying statistically significant three-node NM patterns that can help infer novel disease-drug-gene relationships. The NM analysis can decompose the whole heterogeneous network into smallest network patterns that recurrently discovered in the network, considered as the backbone associations of diseases, drugs, and genes. For instance, in NM 1 instances in Figure From our preliminary study , we founIn this paper, we proposed a network-based computational framework to investigate integrated heterogeneous network extracted from MEDLINE literature, including associations among three major entity categories: drug, gene, and disease. Five significant NMs were identified and considered as the backbone of the entire network. The potential biological meanings of each network motif were further investigated. The results demonstrated that the proposed approach holds the potential to 1) prioritize candidate disease genes, 2) identify potential disease relationships, and 3) propose novel drug targets, within the context of the entire knowledge. We believe that such analyses can facilitate the process of inferring novel relationships between drugs, genes, and diseases. One future direction is to develop module-based approaches to understand associations between different biomedical entities. Modules are condensed subnetworks in a network. Modules identified in heterogeneous networks are a group of related diseases, drugs and genes, which gives researchers a focused network view of the association relationships among these entities. Topology analysis of heterogeneous networks using graphic theory can also be applied in future studies, which can lead to the identification of diseases/drugs/genes in the context of association networks. Pathway level information could also be integrated in future analyses to extend current association network.The authors declare that they have no competing interests.YZ and CT led the study design and analysis, and drafted the manuscript. GJ contributed to the manuscript preparation and use case discussions. JS and AAN contributed to the association data extraction and reorganization, CGC and HL participated the design, provided support and manuscript editing. All authors read and approved the final manuscript.Detailed network information derived from NM 1 .1 Figure .Click here for fileDetailed network information derived from NM 4 .4 Figure .Click here for fileDetailed network information derived from NM 2 .2 Figure .Click here for fileNM analysis of drug-gene, disease-drug, and gene-drug networks.Click here for file