Sustainable Animal Breeding) workshop focusing on post analysis of microarray data. The participating groups were provided with identical lists of microarray probes, including test statistics for three different contrasts, and the normalised log-ratios for each array, to be used as the starting point for interpreting the affected probes. The data originated from a microarray experiment conducted to study the host reactions in broilers occurring shortly after a secondary challenge with either a homologous or heterologous species of Eimeria.The aim of this paper was to describe and compare the methods used and the results obtained by the participants in a joint EADGENE  and SABRE (Cutting Edge Genomics for Several conceptually different analytical approaches, using both commercial and public available software, were applied by the participating groups. The following tools were used: Ingenuity Pathway Analysis, MAPPFinder, LIMMA, GOstats, GOEAST, GOTM, Globaltest, TopGO, ArrayUnlock, Pathway Studio, GIST and AnnotationDbi. The main focus of the approaches was to utilise the relation between probes/genes and their gene ontology and pathways to interpret the affected probes/genes. The lack of a well-annotated chicken genome did though limit the possibilities to fully explore the tools. The main results from these analyses showed that the biological interpretation is highly dependent on the statistical method used but that some common biological conclusions could be reached.It is highly recommended to test different analytical methods on the same data set and compare the results to obtain a reliable biological interpretation of the affected genes in a DNA microarray experiment. Sustainable Animal Breeding, [The previous Microarray Data Analysis Workshop organised by EADGENE  in Novereeding, ) workshoet al [The initial objective of an analysis of a microarray data set is to produce a list of significantly affected probes/genes. This analysis can be relatively challenging, but the major challenge is to interpret the list of hundreds to thousand affected genes and draw some biological conclusions. To assist this process, a large number of statistical methods using quite different approaches have been proposed, which can consequently produce different results if applied to the same data set ,8. Gene-et al  who defiet al . To avoiA common challenge faced during the interpretation of the affected probes is the lack of appropriate annotation of the probes on the microarray. An affected probe without annotation can consequently not contribute to the interpretation of the results and if a major fraction of the probes are without annotation it may have a negative influence on the following analysis, such as GO enrichment analysis. A study of methods to improve the annotation of microarray probes was also a part of this workshop and is described in the adjacent papers -20.In this paper, the methods applied and the results obtained by the participating groups are summarised and some general conclusions are drawn.Eimeria are obligate intracellular protozoan parasites which can affect chickens and continuous exposure to Eimeria can result in protective immunity. The process leading to protective immunity was investigated by studying the host reactions after homologous or heterologous secondary infections. A total of 125 one-day-old Ross 308 male broilers were randomly divided in five groups of 25 broilers each. At 7 days of age, three groups were inoculated with phosphate buffered saline (P) and two groups were inoculated with E. maxima (M). A secondary challenge followed at day 21 of age. This challenge was with PBS (P), E. maxima (M) or with E. acervulina (A), forming five challenge groups PP, PM, PA, MM and MA. Five chickens from each group were killed at 8 and 24 hours after the second challenge and specific regulations of gene expression profiles in the jejunum were monitored using chicken whole genome oligonucleotide microarrays . The obtained microarray data was normalised and analysed and lists of affected genes were obtained for different contrasts. The result of the contrasts MM8-PM8, MM8-MA8 and MM8-MM24 were provided for this workshop as three lists including all microarray probes and test statistics for the three different contrasts. The number of affected probes for each contrast is shown in Table et al.th 2008, based on Ensembl version 50 was used for the workshop. Furthermore, the group from the Wageningen University built a customized annotation utilising chicken-human orthologous gene information and performed separate analyses for each annotation [A proper annotation of the individual probes on a microarray is a prerequisite for establishing a link between the probe and the associated biological knowledge such as gene ontology and pathways. The annotation files used for interpreting the three provided gene lists were the ones obtained as a part of the workshop and described in the adjacent papers -20. The notation , the gronotation  and the notation  for addiThe participating groups applied conceptually different analytical approaches to interpret the three provided gene lists, using both commercial and public available software Table . The maiThe challenge of mapping the probes/genes on the chicken microarray to biological knowledge, such as gene ontology and pathways, was encountered by all groups. In general, half of the probes could be mapped and contribute to the biologically interpretation of the data. The lack of a well-annotated microarray did consequently have a detrimental effect on the results. Improvements were however obtained by using chicken-human orthologous gene annotation in contrast to chicken gene annotation as reported by the group from Wageningen University . The chiThe results of the different analytical approaches applied by the participating groups showed, in general, that the biological interpretation is highly dependent on the statistical method used.The analysis for enrichment of GO-terms based on singular enrichment analysis (SEA), applied by the different groups Table , revealeThe commercial software Ingenuity Pathway Analysis (IPA) was used by the groups from University of Cordoba, Spain  and fromUsing GenMAPP/MAPPFinder, Prickett and Watson identified several biologically relevant pathways being affected, thus demonstrating the usefulness of this tool for microarray analysis, especially with an improved annotation .The analytical methods based on gene set enrichment analysis (GSEA)  class of methods and takes the GO structure into account when testing the gene sets. Comparing the results obtained using topGO with the results from "classical" Fisher's exact test and the Kolmogorov Smirnoff test, both of which ignore the GO structure, showed that fewer significant terms were found with topGO , which mThe majority of the analytical tools provide options for correction for multiple testing using various methods. It is common practice to apply multiple test correction to control the family-wise false-positive rate in the result list, but there is little consensus on how to perform the correction and whether the correction improves the results . SeveralWhere genes are represented by one or more oligonucleotides, it is possible to carry out enrichment tests at the level of the gene or at the oligonucleotide. These two levels could potentially produce different results. However only minor differences were found between enrichment tests at the level of the gene compared to those at the level of the oligonucleotide . It is dE. acervulina infection triggers a similar response as an E. maxima infection. The identity of the affected genes between different time points of a homologous challenge (MM8-MM24) indicates that the secondary immune response increases from 8 to 24 hours.Despite differences in the specific GO-terms and pathways found to be affected by the groups, some common biological conclusions could though be reached for the three contrasts. Specific details of the biological conclusion can found in the papers from the participating groups -28. The Different analytical methods were applied by the teams of the joint EADGENE and SABRE workshop focusing on the extraction of biological meaning from lists of significantly affected genes. The analyses were in general negatively affected by the lack of a well annotated microarray. However, the use of chicken-human orthologous gene annotation was found to improve the analyses. The results showed that the biological interpretation is highly dependent on the statistical method used but that some common biological conclusions could be reached. It is hence recommended to test different analytical methods on the same data set and compare the results to obtain a reliable biological interpretation of the affected genes in a DNA microarray experiment.The authors declare that they have no competing interests.JH drafted the manuscript and all authors read and approved the final version of the manuscript.Microsoft Excel spreadsheet file including the output from the statistical tests of the three contrasts MM8-PM8, MM8-MA8 and MM8-MM24 on separate worksheets. Each worksheet contains 13158 rows and the following columns: Block, Row and Column: block number and row-column number in block; Gene.Name: 384 well source plate number and well and reporter name from the annotation version 1.0 for ARK-Genomics G.gallus Oligo Probe set; Name.descr: reporter ID from the annotation version 1.0 for ARK-Genomics G.gallus Oligo Probe set; logFC: estimate of the log2-fold-change corresponding to the effect or contrast; AveExpr: average log2-expression for the probe over all arrays and channels; t: moderated t-statistic; P.Value: raw p-value; adj.P.Value: p-value adjusted for multiple testing (FDR); B: log odds that the gene is differentially expressed.Click here for file


Young individuals are the age group with the highest risk of car accidents. One of main explanations relies on the use of psychoactive substances , which are known to be major risk factors of road accidents, and whose consumption is almost universally more common among younger drivers. Although the correlation between psychoactive substances use and decrease in driving performance has been established in controlled experimental or laboratory settings, few studies were conducted in naturalistic circumstances. The TEND by Night project has been designed to evaluate the relationship between driving performance and psychoactive substances assumption in young drivers enrolled at typical places of consumption.The TEND by Night project, endorsed by the European Commission, is a multidisciplinary, multi-centric, cross-sectional study conducted in six European countries . The study population consists of 5000 young drivers aged 16-34 years, attending recreational sites during weekend nights. The intervention is based on the portal survey technique and includes several steps at the entrance and exit of selected sites, including the administration of semi-structured questionnaires, breath alcohol test, several drug assumption test, and measurement of the reaction time using a driving simulator. The main outcome is the difference in reaction time between the entrance and exit of the recreation site, and its correlation with psychoactive substances use. As a secondary outcome it will be explored the relationship between reaction time difference and the amount of consumption of each substance. All analyses will be multivariate.The project methodology should provide some relevant advantages over traditional survey systems. The main strengths of the study include the large and multicentric sample, the objective measurement of substance assumption , the application of a portal survey technique and the simultaneous evaluation of several psychoactive substances. Young individuals are the age group with the highest risk of car accidents, as documented by crash and injury statistics in all high-income countries -3, in whOne of main explanations relies on the use of psychoactive substances , which are known to be major risk factors of road accidents -12, and Although it is well known that psychoactive substances impair driving performance in controlled experimental or laboratory settings -21, onlyWe designed an international multicentric cross-sectional survey - the TEND  by Night project - in order to evaluate the relationship between driving performance and alcohol or other psychoactive substances  assumption in young drivers enrolled at typical places of consumption. The secondary aim of the project is to contribute at increasing young peoples' awareness on the potential influence of alcohol and psychoactive substances on their driving capacity through the dissemination of correct and effective information.The present paper describes the research protocol of the project, which is currently on course.The TEND by Night project is a multidisciplinary, multicentric, cross-sectional study that is performed in six European countries - Italy, Belgium/Netherlands, Bulgaria, Poland, Spain and Latvia - the last of which, however participated in the study design but not in the intervention. The project, which is endorsed by the European Commission - Public Health Executive Agency "see Additional file The study population consists of subjects aged 16 to 34 years, who own a driving license and attend recreational sites during weekend nights. The required sample size was calculated using the Schlesselmann formula  for knowIn each nation, a map of the recreational meeting places  was realized on the basis of official regional lists. After a drawing up of a first selection, the final choice was made according to the willingness of the clubs' owners.The TEND by Night intervention  is basedIn each country, the survey staff is composed of at least six operators that have been specifically trained, including a survey manager , one technician for the reaction time evaluation, two interviewers (responsible for questionnaires and test administration) and two hostesses for approaching young people. Prior to conducting interventions, staff members from each country attended a two-day training session with the study coordinator.Precautions are taken to guarantee data confidentiality. To maintain a rigorously anonymous management of the data while keeping the link between biological tests and survey responses for each respondent, a unique identifier is generated that specified the individual participant. The adopted method involves disposable, non-transferable bracelets  that posThe study is conducted according to the European Commission Ethical Code . The TENAn information letter (containing contacts) and an informed consent to be signed are given to the participant at the time of enrolment. The informed consent sheet is written in a language as plain as possible , so thatThe entrance and exit questionnaires were developed based on validated questionnaires -34, test1) Demographic data and socioeconomic status ;2) Medications consumption (medication consumption in the last seven days);3) Driving habits ;4) Alcohol and drug use ;5) Driving and substance use .The entrance questionnaire is estimated to take five to ten minutes to be compiled.The anonymous exit questionnaire, composed of nine closed- and open-ended questions, consists of three sections that investigate the following topics:6) Alcohol and drug consumption during the event;7) Intention to drive upon exit;8) Opinion about the intervention.The exit questionnaire is estimated to take less than five minutes to be compiled.The full questionnaire is available at the project website .The Dräger Alcotest 6510  was chosWe collect the saliva samples with the Oratect III Oral Fluid Drug Screen Device manufactured by the Branan Medical Corporation, which is a recent member of the devices available for that purpose . The colWe measure the reaction time through a driving simulator: the SimuNomad3 Ecrans provided with the Software SCAM 03 and manufactured by the Ediser . The driDuring the first entrance test, the technician invites the participant to accelerate and drive along the road and to brake when obstacles appear on the roadway without steering the wheel. This test is only a demo for the participant to understand what to do. The driver is then invited to repeat the test: in this test, the reaction time value is noted. During the exit test, the driver performs the test only once.Prior to the main study, pilot studies are on course in every country involved. Approximately 250 young drivers of both sexes are being recruited to evaluate the feasibility of the project and to ensure the quality of procedures. Similarly, the validity and acceptability of study instruments is on evaluation.Initial descriptive statistics will be used to describe the sample: continuous variables will be expressed in terms of means and standard deviations if normally distributed (Shapiro-Wilk test), or medians and interquartile ranges; percentages will be used to describe categorical variables. All the results will be provided for the overall sample and stratified according to alcohol and the various drugs evaluated consumption .The main outcome will be the difference in reaction time (RTD) between the entrance and exit test, and its correlation with alcohol and other drugs use, treating each consumption as a dichotomous variable . For each psychoactive substance, the RTD of individuals consuming the substance will be compared with that of individuals not consuming the same substance, using Kruskal-Wallis test and two-way ANOVA. The potential confounding effect by other variables such as age or gender (or other psychoactive substances) will be accounted using multivariate regression.As a secondary outcome it will be explored the relationship between reaction time difference and the amount of alcohol/drug consumption (as a continuous variable), separately for each psychoactive substance. After an initial evaluation using Spearman test, a linear regression model will also be developed. Indeed, such an outcome is of crucial importance, and it will be secondary only for drug consumptions, because their amount is only self-reported, whereas for alcohol consumption, the amount of which is more precisely estimated by the study sensor, it will be the main outcome.Finally, the potential existence of threshold(s) for reaction time difference will also be explored attempting several cutoffs and testing their relationship with the amount of consumption of the various substances in univariate analysis. In case of promising cutoff values, binomial and/or ordinal multivariate logistic regression will be set to evaluate the independent predictors of each cutoff value of reaction time difference.2 or >20% OR change, interaction - especially among various types of consumption - and higher power terms evaluation, multicollinearity and influential observation/residuals analysis - studentized, Cook's D influence, Hat diagonal matrix, Welsh distance, etc.) and logistic regression . In the linear regression for the secondary outcome only, the non-linear effect of covariates will be modeled using a restrictive cubic-spline function and its significance and will be assessed by the Wald's chi-square test. Interaction among variables will be checked using the same lines. Model fit will be considered as significantly improved for the latter on the basis of the Akaike Information Criterion (AIC) applied backwards for each model , at a significance level of 0.10.Standard procedures for model building and subsequent validity assessment will be adopted for both linear .The TEND by Night project is a large, multi-centric European survey that has been primarily designed to evaluate the association between alcohol and psychoactive substance consumption and driving ability in young people.The project methodology should provide some relevant advantages over more traditional survey systems. On one side, most of the studies that have examined the patterns of consumption of alcohol and drugs in recreational places or in social settings used only self-reported measurements -42. On tAs mentioned, two naturalistic studies have prospectively evaluated the potential relationship between alcohol and other psychoactive substances consumption with driving impairment indicators in recreational places ,23. ThesThe study has some limitations that must be mentioned. First, the voluntary recruitment of the participants and the opportunistic selection of the recreational venues could introduce an important selection bias, limiting the representativeness of the sample and the generalization of the final results on the prevalence of alcohol and drug consumption. However, such an issue does not impair in any way the main outcomes of the study, which is the relationship between consumption and driving ability. Second, the findings from a driving simulation do not perfectly correspond to on-road circumstances, and our results may not be perfectly applied towards on-road circumstances. However, in direct comparison studies, simulator results correlated well with real driving performances ,46. FinaAlthough the role of psychoactive substances in impairing driving ability is documented, the precise relationship between consumption and degree of driving impairment is not fully ascertained for several substances. The TEND by Night project has been designed to meet this challenge adopting an up-to-date methodology on a large sample of young individuals from recreational or social sites in five European countries.The authors declare that they have no competing interests.All the authors contributed to the conception, design and are currently carrying out the TEND by Night study. RS, SCP and LM wrote the present manuscript. All authors read and approved the final manuscript.The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1471-2458/10/205/prepubFunding proof.Click here for fileInternal Central Ethics Committee approval proof.Click here for fileCentral Ethics Committee of the Catholic University of the Sacred Heart in Rome approval proof.Click here for file


Kulldorff's spatial scan statistic and its software implementation – SaTScan – are widely used for detecting and evaluating geographic clusters. However, two issues make using the method and interpreting its results non-trivial: (1) the method lacks cartographic support for understanding the clusters in geographic context and (2) results from the method are sensitive to parameter choices related to cluster scaling , but the system provides no direct support for making these choices. We employ both established and novel geovisual analytics methods to address these issues and to enhance the interpretation of SaTScan results. We demonstrate our geovisual analytics approach in a case study analysis of cervical cancer mortality in the U.S.We address the first issue by providing an interactive visual interface to support the interpretation of SaTScan results. Our research to address the second issue prompted a broader discussion about the sensitivity of SaTScan results to parameter choices. Sensitivity has two components: (1) the method can identify clusters that, while being statistically significant, have heterogeneous contents comprised of both high-risk and low-risk locations and (2) the method can identify clusters that are unstable in location and size as the spatial scan scaling parameter is varied. To investigate cluster result stability, we conducted multiple SaTScan runs with systematically selected parameters. The results, when scanning a large spatial dataset , demonstrate that no single spatial scan scaling value is known to be optimal to identify clusters that exist at different scales; instead, multiple scans that vary the parameters are necessary. We introduce a novel method of measuring and visualizing reliability that facilitates identification of homogeneous clusters that are stable across analysis scales. Finally, we propose a logical approach to proceed through the analysis of SaTScan results.The geovisual analytics approach described in this manuscript facilitates the interpretation of spatial cluster detection methods by providing cartographic representation of SaTScan results and by providing visualization methods and tools that support selection of SaTScan parameters. Our methods distinguish between heterogeneous and homogeneous clusters and assess the stability of clusters across analytic scales.We analyzed the cervical cancer mortality data for the United States aggregated by county between 2000 and 2004. We ran SaTScan on the dataset fifty times with different parameter choices. Our geovisual analytics approach couples SaTScan with our visual analytic platform, allowing users to interactively explore and compare SaTScan results produced by different parameter choices. The Standardized Mortality Ratio and reliability scores are visualized for all the counties to identify stable, homogeneous clusters. We evaluated our analysis result by comparing it to that produced by other independent techniques including the Empirical Bayes Smoothing and Kafadar spatial smoother methods. The geovisual analytics approach introduced here is developed and implemented in our Java-based Visual Inquiry Toolkit. The scan statistic is a method for detecting non-random clustering in multi-dimensional point or near-point datasets . Althougmaximum-size. The maximum-size parameter sets an upper bound on the circle radius in one of two ways: (1) by specifying the maximum percentage of the total population at risk within the circle or (2) by specifying the geographic extent of the circle. The former is the default and is used in the research reported here. When setting the maximum-size based upon population at risk, the default maximum-size value, as recommended in the SaTScan user guide . Isecondary clusters that have a significantly large likelihood ratio but are not the primary cluster . ThIn the following Results section, we introduce our novel geovisual analytics methods and discuss how they can be applied to SaTScan results to alleviate the two issues with SaTScan described in the previous session. In the Conclusion section, we summarize the method, describe its limitations, and recommend a procedure for investigating geographic clusters of disease. The final Methods section is reserved for the technical details of data processing, SaTScan application, cartographic mapping, and analysis design.The geovisual analytics methods implemented in VIT directly address the lack of cartographic support for interpreting SaTScan results and the implications of selection of scaling parameters. In our approach, a tabular interface enables loading of multiple SaTScan results without any data manipulation in GIS or other software. This interface is linked dynamically to a choropleth map, a map matrix, and related information visualization tools so that an analyst can select, visualize, and compare SaTScan results produced by different maximum-size values. In the remainder of this section, we describe the sensitivity of SaTScan results to the maximum-size parameter, which is reflected in two ways: (1) heterogeneous contents and (2) instability of clusters in location and size. Although static results from our mapping/visualization tools are used to support this discussion; the tools derive much of their power to support analysis and interpretation from their capabilities for flexible user interaction and dynamic linking among views.heterogeneous clusters.When analyzing county-level cervical cancer mortality data for the U.S., we found that SaTScan reports many statistically significant clusters that contain a relatively high proportion of low-risk counties. We describe these regions as core clusters. The phenomenon is caused by the tendency of SaTScan "to identify large areas with large populations but small elevations in risk, since such areas have the highest statistical power. Smaller clusters contained within these areas that have higher elevations in risk but lower, though statistically significant, likelihood ratios, are ignored" . The existence of heterogeneous clusters can be demonstrated by applying SaTScan to the cervical cancer dataset. The SMR map in Figure To facilitate identification of core clusters and avoid potentially misleading heterogeneous clusters, it is necessary to avoid selection of an excessive maximum-size value. For example, the core cluster B  in Figure On the other hand, when the maximum-size parameter is too small, SaTScan may report only the smallest core clusters, missing regional-level core clusters of homogenous high-risk contents. This occurs when a core cluster has a percentage of the total population at risk above the maximum-size value. For example, we ran scans with a maximum-size of 1%, 2%, and 3%. No cluster is reported in the area where cluster A occupies. This finding suggests that cluster B is the only core cluster in cluster A. We also examined the LLR values of clusters A and B; a LLR value provides a cluster the statistical power to reject the null hypothesis. With a maximum-size of 6%, Cluster B has an LLR value of '25.30' . The value is much higher than other significant clusters  and is close to the LLR of cluster A . It suggests that the statistical power of cluster A is contributed primarily by core cluster B.map matrix [In order to obtain core clusters, it is necessary to run SaTScan multiple times using different maximum-size values, particularly for relatively large datasets . To examine this issue, we ran fifty scans, increasing the maximum-size parameter in 1 percentage point increments from 1% to the default 50%. We then interactively compared the fifty SaTScan runs using the p matrix  componenHowever, we noticed that as we reduced the maximum-size, the location and size of the core clusters varied significantly, producing a new problem of core cluster instability in both location and size. For example, cluster J is reported at the maximum-sizes of 4%, 6% and 10%; however, it expands into cluster J2 at a maximum-size of 8% and then disappears when the maximum-size is above 10%. Such a finding suggests that a unique maximum-size value might be necessary for identifying the correct bounds of each core cluster, and that the clusters are scale-dependent. Hence, it is unlikely that there is a single, optimal maximum-size value for the entire study extent when scanning a large spatial dataset . Therefore, we recommend running multiple scans, systematically increasing the maximum-size parameter with each run. The above issue of core cluster instability still raises several important questions: First, how reliable are the clusters reported by a single scan, as compared to those by multiple scans? Second, how do we cope with the sensitivity of SaTScan results to the maximum-size parameter? Lastly, can we identify more stable, homogeneous clusters by running multiple scans, and how? We address these questions in the following sections.reliability visualization. The method visualizes the reliability that a county is reported within a cluster when SaTScan is run multiple times with a systematically varying maximum-size parameter. In epidemiology, reliability is defined as the capacity of a test to give the same result – positive or negative – on repeated applications [To assist discrimination of stable, core clusters from heterogeneous and/or unstable ones, we have developed a method that we term ications . ReliabiRi is the reliability value for location i, S is the total number of scans, and Ci is the number of scans for which that location i is within a significant cluster. The reliability measure has a value range from '0' to '1,' where '0' means that the location is not found in a significant cluster in any of the scans and '1' means that the location is within a significant cluster in all scans. The reliability score measures the stability of clusters reported by multiple scans. Reliability is distinct from the concept of validity, which is a measure of the probability that the cluster represents a true high-risk region. Therefore, the goal of reliability visualization is to identify stable core clusters rather than to evaluate the validity of the core clusters. Since we are applying it to the results of an analysis that measures validity, the end result is to identify the locations that are reliable within a significant high risk cluster.where Using VIT, reliability scores for each county were calculated using the eight scans in Figure Interpreted with the SMR map, the reliability visualization facilitates initial visual discrimination of core clusters from heterogeneous ones. The task involves two steps: (1) interpreting the reliability scores with SMR values and (2) comparing the reliability score of a cluster with the places neighbouring or inside the cluster.When interpreting the reliability visualization in tandem with SMR values step #1 above), a heterogeneous cluster can be identified if it exhibits heterogeneity in both reliability scores and SMR values. Examples are clusters C and H in Figure  above, aWhen interpreting the reliability score, an analyst must compare both sub-regions of high risk within the cluster to adjacent areas within the cluster  and the cluster as a whole to adjacent areas out of the cluster . This is particularly important for the clusters that have high a heterogeneity measure (Pct_NH). For example, cluster A in Figure 1, r2, ..., rn}, where ri represents the reliability score of county i in the map, and county i in one map matches the county i in the other map. The similarity between the two vectors R1 and R2 is measured in terms of Euclidean distance [To evaluate whether the reliability visualization technique is consistent enough to help users understand and cope with the sensitivity of SaTScan results to the choices of maximum-size, we generated another reliability visualization Figure  based ondistance ; and theFor further evaluation, we compared our reliability visualization with the maps generated by the Empirical Bayes Smoothing method Figure  and the There are several limitations to Empirical Bayes Smoothing and the Kafadar spatial smoother that may be causing the discrepancies with the reliability visualization. First, through smoothing, isolated groupings of high rate values are averaged into the surrounding low rate values, missing the smaller core clusters . Second, although the method smoothes the rates in small population areas, it does not eliminate the small number problem. For example, the smoothed map suggests a high risk region that has sparse population  identification of spatially small, yet important and stable high risk core clusters  that can otherwise be easily hidden in the reported SaTScan clusters and (2) for improving the understanding of heterogeneous clusters and their formation. Such discrimination is difficult when interpreting a single scan using traditional visualization methods. The reliability visualization method can be used in any situation where a method's parameter sensitivity is a concern and when analysis of multiple outcomes is needed, thus allowing application beyond the maximum-size parameter of the Kulldorff spatial scan statistic.The Kulldorff spatial scan statistic and the SaTScan software represent an important first step to cluster identification and interpretation. However, two issues make using the method and interpreting its results non-trivial: (1) SaTScan lacks cartographic support for understanding the clusters in geographic context, and (2) results from the method are sensitive to the selection of scaling parameters. The system provides neither direct support for making these choices, nor methods to evaluate the results from selection of various parameters.The VIT addresses the first issue by providing a tabular interface Figure  for loadIt is important to note that our geovisual analytics methods, as they are currently proposed, have limitations. A primary limitation is that the methods are contingent upon the quality of the incoming SaTScan results. It is possible that the incoming SaTScan results can be flawed themselves due to limited user guidance, arbitrary parameter selections, the miss-match between any geometric shape scan  and some real-world geographic clusters, or general misuse of the software. Because of this, we recommend comparison of SaTScan outcomes with other, independent clustering techniques . At present, VIT is not equipped with sufficient methods  for appropriate comparisons. Secondly, visual interpretation can be more difficult than statistical interpretation, particularly when the analyst is not accustomed to using visual methods of analysis. Therefore, it is extremely important that visual evidence is used to complement statistical evidence, and not to replace it. Further, we recommend consultation with multiple epidemiologists and other domain experts prior to the development and implementation of health care policy.Figure The cervical cancer mortality data for the United States between 2000 and 2004 were obtained from the National Cancer Institute using the Surveillance, Epidemiology, and End Results (SEER) program via the SEER*Stat software. The data are aggregated into 3,105 county and county-like enumeration units in the forty-eight contiguous states of the U.S., including the District of Columbia. We removed Alaska and Hawaii to ensure geographic continuity for the cluster analysis. The mortality data were originally grouped into nineteen age groups by county of residence at the time of death; the first two age groupings (age 0 and age 1–4) were combined to produce eighteen 5-year intervals through age 85. The U.S. female population, estimated by the U.S. Census for each year in the study period, was summed to produce the population at risk.SaTScan evaluates disease risk in terms of relative risk, reporting the ratio of observed to expected cases for both the total cluster and individual enumeration units within the cluster. This ratio, when applied to mortality rates, is formally known as the Standardized Mortality Ratio (SMR) in epidemiology, expressed as the ratio of observed to expected deaths. An SMR of '1' suggests no difference in risk, lower than '1' suggests low-risk, and larger than '1' suggests high-risk. To calculate SMR, we obtained age-specific observed deaths from SEER*Stat. We calculated the number of expected deaths using Equation 3:n age groups, pi is the population of a county in an age group, Ci is the sum of the mortality count for all the counties in the age group, Pi is the sum of the population of all counties in the age group.where the population is categorized in We chose to visualize indirectly adjusted relative risk rather than a directly adjusted mortality rate because it is less subject to bias than the directly adjusted rate in areas with small populations. Furthermore, SaTScan evaluates and reports clusters in terms of relative risk, which is comparable to SMR. Therefore it is easier to analyze SaTScan results by visualizing SMR.The choropleth mapping technique is commonly applied to aggregated disease data and Brewer and Pickle contend it is well suited to this application . ChoroplThe first concern with choropleth mapping is the classification strategy imposed on the dataset. There are two forms of choropleth maps: (1) classed and (2) unclassed. Classed choropleth maps divide the attribute space into a set of intervals, filling all enumeration units in the same interval with a single colour, while unclassed or n-classed choropleth maps mathematically relate each attribute value to a position on a colour ramp, pairing every unique value with a unique colour . We chosThe second concern with choropleth mapping is the choice of colour scheme used to symbolize the determined classes. Improper colour selection inhibits map users from retrieving both general patterns and specific details from the map display . SMR is The third concern with choropleth mapping is the small numbers problem. Disease rates tend to be unstable for enumeration units that have a small population at risk or for diseases that are rare . For sucFinally, choropleth mapping suffers problem visual bias . An area-based cartogram ,47 wouldA primary objective of this research was to determine the sensitivity of SaTScan results to the maximum-size parameter. It is important to reiterate that the maximum-size parameter can be either the percentage of the total population at risk or the geographic size of the circle. We use the former because it is the default setting in SaTScan. To understand the sensitivity of SaTScan results to the maximum-size parameter, we ran the SaTScan spatial scan statistic on the cervical cancer dataset fifty times, starting with a maximum-size of 1% and increasing the parameter by an interval of 1 percentage point with each run until reaching the default value maximum-size value of 50%. For each run, we set the number of Monte Carlo replications to 999. The SaTScan software allows users to set the maximum-size in two ways: (1) through restriction of the upper limits of the maximum-size parameter before running the scan or (2) through retention of the default maximum-size of 50%, but selecting for the software to report only circles with a maximum-size value below the desired value. We adopted the second method to avoid pre-selection bias, as recommended by Kulldorff . The outFIPS code: Federal Information Processing Standards code; HPV: human papillomavirus; LLR: logarithm of the likelihood ratio; maximum-size: the maximum radius size of a scan circle; Pop: the population at risk of a cluster; Pct_NH: the percentage of the counties in a cluster that are not in high risk; Pct_Pop: the percentage of the total population at risk; SaTScan: Kulldorff's spatial scan statistic and its software implementation; SMR: Standardized Mortality Ratio; VIT: Visual Inquiry Toolkit.The authors declare that they have no competing interests.The study was conceived by EJL and AMM. JC analyzed the spatial scan statistics method and the SaTScan results. JC developed and implemented the novel geovisual analytics methods presented in the text, evaluated the methods, and compared that to the other techniques. The cervical cancer mortality dataset was compiled by AN. SaTScan runs were completed by JC and AN. The visualization of cervical cancer mortality clusters was interpreted by JC, RER, EJL, and AMM. The manuscript was prepared by JC and RER and reviewed by AMM and EJL. EJL assisted in drafting the section on reliability and AN assisted in drafting the section on data. EJL provided epidemiological guidance and AMM provided cartographic and visualization guidance during revisions of the manuscript. All authors read and approved the final manuscript.


Global cardiovascular risk is a new approach which allows the physicians to quantitate the prognosis of the patients. It is therefore possible that a score, based on the major cardiovascular risk factors, is correlated with some degree of cardiovascular anatomic damage. Since this hypothesis has been demonstrated with the Framingham risk score, we decided to verify it using another score (Progetto Cuore risk score), which is probably more precise in a european low-risk population, such as the italian one.We studied 84 italian caucasian subjects  with elevated blood pressure and/or dyslipidemia plus other possible cardiovascular risk factors.The subjects have never been treated for these reasons. The following evaluations were performed: history, clinical and laboratory determinations, echocardiogram, carotid echodoppler.The recruited people were on the whole characterized by a low cardiovascular risk, as confirmed by the low scores of the Progetto Cuore. Simple linear regression analysis showed significant associations between some parameters of early cardiovascular damage  and some predictors. The highest significance was found between the cardiovascular structural results and the Progetto Cuore score. In a multivariate regression analysis our model, which included factors potentially linked to the cardiovascular anatomic changes, demonstrated that the Carotid score was significantly associated with age, sex and pulse pressure; intima-media thickness with the same factors and, in addition, with the body mass index; left ventricular mass with sex, pulse pressure and body mass index.Our paper confirms previous studies about the association between a comprehensive risk score and signs of early cardiovascular damage. A temporally limited exposure to cardiovascular risk factors, in particular to blood pressure, is already able to induce significant changes in both the heart structure and the vascular wall. Also in a european low-risk population the use of a cardiovascular risk score program, such as the Progetto Cuore in Italy, allows a quite precise estimation of the possible cardiovascular damage. The concept of global cardiovascular risk has been widely accepted in medicine: the patient is no more considered as a carrier of single cardiovascular risk factors, to be tackled one by one by the physician, but as a subject potentially affected by their interactions. This approach was proposed in 2003 by the guidelines of the European Society of Hypertension and the European Society of Cardiology , in partIn support of this new approach in the last few years many projects were developed  in order to provide the practising physician a quantification of the cardiovascular risk of the single patient through a computerized procedure based on the acquisition of clinical parameters, such as age, sex, blood pressure values, lipid status, and smoking habits.In order to evaluate the impact of different risk factors on target organs and the possible correlations with the italian risk score Progetto Cuore, we decided to study subjects sent to our outpatient clinic by the general practitioners. Our outpatient clinic is devoted to patients with dyslipidemia and hypertension: we could therefore choose to evaluate subjects with two important cardiovascular risk factors, such as high blood pressure and/or abnormal lipid values, but without previous or concomitant therapies.Since February 2007 through September 2007 we studied 84 caucasian subjects  affected by blood pressure above normal levels  and/or dyslipidemia, sent to our outpatient clinic by the general practitioners in a local survey of the prevalence of the metabolic syndrome.The inclusion criteria are shown in Table : this score is calculated taking into account some variables such as sex, age, smoking habits, systolic and diastolic blood pressure, total cholesterol levels, HDL-cholesterol levels, and possible anti-hypertensive therapy.Global cardiovascular risk at 10 years was evaluated using the Progetto Cuore program of the Istituto Superiore di Sanità The metabolic syndrome was defined using the criteria of the National Cholesterol Education Program – Adult Treatment Panel III (NCEP-ATP III) .All the echocardiogram examinations were performed by the same experienced cardiologist using an ATL model HDI 5000 B-mode echocardiograph with a 3.5 MHz sectorial probe. Registrations were performed along the long axis parasternal projection with the M-mode measurement of the left atrium, aortic root, and left ventricle . The doppler registration of the transmitralic profile was performed in the apical projection. Left ventricle mass (LVM) was determined calculating the left ventricle mass (according to the formula of the American Society of Echocardiography) . The relAll the carotid echodopplers were performed by the same physician using ESAOTE model AU5 with a 7.5 MHz linear probe. The examination of the subjects, in supine position and with the extrarotated head contralaterally by 45°C, evaluated the common carotid artery, the carotid bifurcation and the extracranial tracts of both the internal and external carotids with a longitudinal and transverse approach. Intima-media thickness was determined in telediastole at the level of the far wall of the common carotid artery at a distance of 20-10-5 mm from the bifurcation. For statistical analysis the mean of the three measurements in both common carotid arteries  was used. According to the ESH/ESC guidelines an intima-media thickness lower than 0.9 mm was considered normal; a thickness higher than 0.9 mm but lower than 1.3 was considered increased; a thickness higher than 1.3 mm was defined as a plaque [Statistical analysis was carried out using Statistica 8.0 package . For statistical purposes the Progetto Cuore scores were log-transformed to reduce skewness.The clinical characteristics of the subjects studied are shown in Tables These characteristics were confirmed by the cardiovascular risk scores calculated for our subjects: mean value was 5.16 ± 5.3 SD, and only 2 of them (2%) were above 20% risk of cardiovascular events at 10 years (i.e. high cardiovascular risk according to the Progetto Cuore score).Simple linear regression analysis showed significant associations between some responses  and some predictors Table . InsteadWe also divided the subjects according to the sex: in both male Table  and femaIn a multivariate regression analysis Table , we usedIn addition m-IMT was significantly associated with LVM when we considered all the subjects; this association was confirmed in female subjects, instead it was not seen in male subjects Table .As a final point, the presence of the metabolic syndrome was not able to induce a higher level of damage at the cardiovascular sites (data not shown).Our results show that, in a population with some cardiovascular risk factors but, as a whole, not at particularly high risk, it is possible to demonstrate a significant correlation between a simple risk score, used in clinical practice by italian physicians, and some parameters of target organ damage. This was something already demonstrated with the Framingham risk score and confirmed by recent papers -7. HowevIn addition, the absence of the effects of any anti-hypertensive and hypolipemic therapy allows us to exclude possible drug effects in terms of reversal of the anatomic damage: this is something the other studies, although with more subjects, had to take into account.Our population can be considered at not very long exposure of traditional risk factors: this can be inferred by the absence of drug therapy for hypertension or dyslipidemia. In fact all the subjects studied in this study were regularly evaluated by their family physicians and, at the appearance of an increase of blood pressure or blood lipids, rapidly sent to our clinic. In addition the age and the absolute levels of those parameters put our subjects on average at low risk of cardiovascular events; again in other studies all the categories of risk were included.Our clinical evaluations allow to find interesting associations. The most significant is the association between Progetto Cuore score and the Carotid score: the associations with m-IMT and LVM were less significant. The reason we used the Carotid score in order to define the damage of the vascular wall was related to the possible different meanings of the intima-media thickness and the plaques ,11: in fWhen we performed the simple regression analysis, as a first step we evaluated the all subjects finding the significant associations shown in Table The multiple regression analysis was carried out defining a model with possible variables potentially related to both vascular and cardiac damage: for Carotid score we found significant associations with age, sex and pulse pressure. As for m-IMT, body mass index was significant in addition to the above mentioned variables. Instead with regards to the LVM the significant associations in the multiple regression analysis were with sex, pulse pressure and body mass index. These statistical evaluations suggest that, among modifiable cardiovascular risk factors, blood pressure is more important than cholesterol in inducing initial damage of heart and vessels.An apparent contradiction in our results is a better correlation with the Progetto Cuore score exhibited by the carotid damage with respect to the heart: it is well known that the left ventricular hypertrophy is a better prognostic indicator in terms of cardiovascular events. Again we believe that our particular population (subjects with not a long exposure to risk factors) can explain this discrepancy. Only one subject could be considered with left ventricular hypertrophy (according to the ESH-ESC criteria) and in this setting of subjects a thorough vascular evaluation can be more sensitive than the echocardiographic examination.per se, indipendently of the usual risk factors [A final issue of these results is the presence of rather low correlation coefficients, although with good statistical significance. This is something already shown in similar studies , likely  factors ,18.Our paper confirms previous studies about the association between a comprehensive risk score and signs of early cardiovascular damage. A temporally limited exposure to cardiovascular risk factors is already able to induce significant changes in both the heart structure and the vascular wall. Among the possible risk factors for these changes blood pressure seems to be the most powerful inducer.Echographic examination of the cardiovascular system represents a useful tool for a complete prognostic evaluation of subjects with different risk factors.The authors declare that they have no competing interests.AP conceived the study, carried out the clinical evaluations, and drafted the manuscript. CG carried out the clinical evaluations and the ultrasound examinations. SB participated in the design of the study and helped to draft the manuscript. All the authors read and approved the final manuscript.


A protein annotation database, such as the Universal Protein Resource knowledge base (UniProtKb), is a valuable resource for the validation and interpretation of predicted 3D structure patterns in proteins. Existing studies have focussed on point mutation extraction methods from biomedical literature which can be used to support the time consuming work of manual database curation. However, these methods were limited to point mutation extraction and do not extract features for the annotation of proteins at the residue level.This work introduces a system that identifies protein residues in MEDLINE abstracts and annotates them with features extracted from the context written in the surrounding text. MEDLINE abstract texts have been processed to identify protein mentions in combination with taxonomic species and protein residues (F1-measure 0.52). The identified protein-species-residue triplets have been validated and benchmarked against reference data resources . Then, contextual features were extracted through shallow and deep parsing and the features have been classified into predefined categories (F1-measure ranges from 0.15 to 0.67). Furthermore, the feature sets have been aligned with annotation types in UniProtKb to assess the relevance of the annotations for ongoing curation projects. Altogether, the annotations have been assessed automatically and manually against reference data resources.This work proposes a solution for the automatic extraction of functional annotation for protein residues from biomedical articles. The presented approach is an extension to other existing systems in that a wider range of residue entities are considered and that features of residues are extracted as annotations. The understanding of the biological function of proteins remains to be a central challenge in biology. In protein science, sequence analysis of amino acids or studies of their spatial distribution have led to predictions and discoveries of a number of biological significant patterns and motifs, e.g. metal-binding sites, catalytic triads, and ligand binding sites -7. ComplWorks have been published in the biomedical text mining community that focused on the extraction of point mutations, which is one type of a residue mention but others have to be considered as well -19. The All of the listed text mining systems are dedicated to the extraction of point mutations, but do not extract contextual features from text as functional annotations of protein residues. A recent publication  proposesThe contribution of this work is the automatic extraction of protein residue annotation from biomedical articles. Contextual information are exploited to identify features of residues that correspond to one of six chosen target categories. As a result, proteins can be selected with residues clustered by annotation types, which can lead to, for example, the identification of active site residues.The extraction of functional annotations for protein residues from literature consists of two parts: protein residue identification, and contextual feature extraction. Figure Named entity recognition for proteins was based on a combination of dictionary lookup with fuzzy matching and basic disambiguation -25. All The extraction of residue mentions follows approaches of previous publications by reusing a selection of regular expression patterns for point mutation ,19. The The identification of the entity triplet organism, protein, and residue, is based on the algorithm described by  with somIn the first step proteins were associated with their hosting organisms. All pairs of protein-species were determined for each protein in a text and ranked by the smallest word distance between the entities in the pair. The identification of organism-protein began with the pair with the smallest word distance measure. A valid association was found, if the relation was specified in UniProtKb. If an association was validated then the search was terminated, and the protein was annotated with the corresponding Uniprot identifier, otherwise the next entity pair from the list was tested. If no match between protein and species was found, then the search was relaxed to genus matching. This relaxed matching is the expansion to the  algorithThe second step of entity triplet association was the association of residues with their source proteins. The procedure of selecting and ranking the residue-protein pairs was similar to the protein-organism association identification. For each pair that was to be tested the annotated Uniprot identifier of the protein was used to retrieve the protein sequence from the database. Three cases can be distinguished: (1) the residue correctly matches the protein sequence; (2) several alternative sequences are matching from a list of proteins; and (3) no match can be found for the residue with the available protein sequences. If a match was not found, then the protein-residue pair was rejected, and the search continued with the next pair from the ranked list. Notice that protein-residue association is purely based on the identification of a residue in a protein sequence. A grounding step was not utilised as the identification of the correct sequence position of a residue would require either the simultaneous alignment of residues, or the use of a commonly agreed and standardised sequence indexing scheme.The extraction of contextual features of protein residue mentions is based on a syntactical analysis of natural language sentences. Two approaches were developed in this work and compared in the performance evaluation study: shallow parser based relation extraction, and full parser based relation extraction.The first approach was to develop a shallow parser, which aims to find the boundaries of major constituents in a sentence, such as noun phrases. The design is based on heuristics and the idea of finding general relations between closed-class English words . All preInitially, an abstract text was split into sentences, and then annotated with part-of-speech (POS) tags using the CISTAGGER , which wThe second approach in contextual feature extraction utilises the full parser ENJU   is the probability of a category associated with a term. The categorisation of a multi-word term into one of the categories, amounts to the identification of the category c* that maximises the association A:where UniProtKb is a comprehensive protein knowledge base that contains manually curated functional annotations for proteins, their sequences, and their residues. It also contributes citation references (PMIDs) for relevant articles. However, the precise association of a citation and a protein residue in context of functional annotation is generally not available.The test dataset for the developed functional annotation extraction is based on the citation references from UniProtKb. A Uniprot corpus was generated by retrieving abstract texts from MEDLINE, that are indexed by the knowledge base. From the 136,566 citations listed in UniProtKb, an almost complete set of 136,559 abstract texts was retrieved from MEDLINE. Although not all information presented in the UniProtKb are necessarily available in the Uniprot corpus, the Uniprot corpus is a starting point for the evaluation of the developed text mining modules. Two derived test corpora were generated from the Uniprot corpus: the gold standard corpus with manual annotation and the cross-validation corpus with automatically annotated information derived from UniProtKb. Table From this set of 100 abstract texts, manual analysis results in four types of annotations. The first type is the annotation of the biological entities of organism, protein, and residue, while the second is the annotation of entity triplet associations, i.e. organism-protein-residue. In addition, text segments of sentences with a residue entity were annotated, if they represent keywords for functional annotation. Finally, the association of a keyword and a residue was also annotated in GC.For the automatic evaluation of extracted data, a cross-validation corpus (XC) was derived from Uniprot corpus. This test set was used to analyse the performance of protein-organism (XC1) and residue-protein (XC2) associations. The test set was annotated automatically, i.e. the biological entities were detected with the same entity recognition systems. The documents in the Uniprot corpus were scanned for tri-occurrences of organism, protein, and residue in text and analysed, if the combinations of the four identifiers, (UID+TID+RID+PMID), can be found in the database. UID is the Uniprot ID, TID is the NCBI Taxonomy ID, RID is a residue identifier, which consists of a residue name + sequence position, and PMID is the PubMed identifier. If at least a single match was found, then the document was selected. For the non-matching combinations the corresponding annotations were removed from text. From the retained and validated associations of the identifiers, two sets of three identifier combinations were determined: UTP = (UID+TID+PMID), and URP = (UIP+RID+PMID). 70,401 UTPs from 55,998 abstract texts were determined for XC1, and correspondingly 68,008 URPs were derived from 5,253 MEDLINE articles in XC2.The performance of each process of the developed protein residue identification was scored against a manually annotated gold standard corpus. Proteins, where the protein entity recognition system and manual curation assigned the same entity were considered as true positives (TP). The same rule also applied for counting TP of residue and organism entity detections.The evaluation of the entity triplet association detection considered only associations as TP, if both pair relations organism-protein and protein-residue were determined correctly. If one of the relations was incorrect, a found association was counted as false positive (FP).In contrast, the automatic evaluations of the entity recognition and entity association detection systems were performed on XC. A true positive of an annotated entity within an abstract text was identified, if UniProtKb lists the same entity in context of the given PMID. For example, if organism X in text Y is also indexed in UniProtKb as a combination of TID+PMID, then a true positive was counted.A correct protein-organism association was detected, if the determined identifier combination UTP was found in XC. Similarly, a correct residue-protein association was found, if the derived identifier combination URP was found in the test corpus. Notice that within this evaluation setup a UTP or URP was counted as FP if the information was not stored in UniProtKb albeit the correct entity association. The effectiveness of the entity recognition and the association detection systems was measured in terms of precision, recall and the balanced F-measure (F1).The extraction of contextual features of residues results in a set of syntactical relations, which are represented as PAS. The performance of this extraction module was evaluated by comparing the returned PAS data with manual annotations in GC. A TP was counted, if the syntactical relations in a PAS were correct, and if the arguments in the PAS contained the annotated residue entity and the marked keyword(s) in the test corpus.The performance of the developed classification method was evaluated by a 100 times 5-fold cross-validation. For each iteration, terms in the reference set were shuffled, and partitioned into a test set (1/5 of the data) and a training set (4/5 of the data). The average precision, recall and F1-measure were calculated for each classifier from the determined confusion matrix.The following sections assess first the extraction system and then the extracted data.All presented results have been evaluated against the manually curated test set, i.e. the gold standard corpus (GC). Entity recognition for the residue mention yields to 92% precision and 98% recall (95% F1 measure). This performance is slightly higher than the one of previously reported solutions of point mutation identification ,16,18, iThe performance of the organism entity recognition system shows better performance than the protein entity recognition solution .The identification of entity triplets consisting of one of each entity type, i.e. the protein, organism and residue mention (POR), is based on association rules. The identification resulted to 82% precision and 38% recall, where our precision is similar to other reported solutions. Our recall is lower than the one reported in MutationGraB and MuteXt and could be explained by the fact that both systems are focused on protein family specific full-text articles. According to our manual inspection the main cause for low recall is because the association of the protein to the organism is often not stated explicitly.The POR detection still requires improvements but is sufficiently precise (82%) to use it for the annotation of protein residues with contextual features. Furthermore, the identification of the correct organism from the literature is helpful for the alignment of the finding with the correct database entry, but it is also an option to relax the organism identification and to rely more on the database content for the final resolution of the protein residue.The POR triplets were now cross-validated against the content of UniProtKb which is the reference database for protein annotations using the cross-validation corpus (XC). We assessed the association of the protein to the organism independently from the residue-protein association. The comparison yielded 82% precision and a recall of 88% for the protein-organism. In the performance assessment of the residue-protein association detection we measured 83% precision and 13% recall. The low recall is less surprising in this case since the annotation of residues is not as mandatory as the species annotation in UniProtKb.The cross-validation of both associations resulted to 54% F1 measure with 83% precision which is similar to our analysis against the GC. By contrast, the average recall in the cross-validation is higher than the one reported from analysis based on the gold standard. The reference database provides reliable information for comparison but the time-consuming curation process is one reason for the lack of content in comparison to the scientific literature.Finally, we filtered all MEDLINE abstracts for mentions of POR triplets and compared the retrieved citations against the references in the citation sets in UniProtKb/PDB. In total 40,750 MEDLINE abstracts make a reference to POR triplets. In total 9,354 Uniprot proteins are covered and 2,884 of these proteins have hyperlinks to 14,007 PDB entries. These 2,884 shared protein mentions are linked to 18,427 MEDLINE abstracts, whereas UniProtKb/PDB makes only reference to 4,652 PMIDs out of which 657 PMIDs are shared between both resources. This demonstrates again that the MEDLINE abstracts do not necessarily cover the information that curators have deemed relevant  and ENJU produced 31% F1 . Manual inspection of the false positive results indicates that mistakes in the part-of-speech tagging are the main source of the error rate. For example, in the sentence"Conversely, K382Q displays a highly altered responsiveness to the activator, suggesting that Lys(382) is involved in both activator binding and allosteric transition mechanism." (PMID:10751408),both parsers identified "altered" as a verb in past tense, although the correct POS is a noun modifier. The performance of the POS tagger is critical for the detection of phrase boundaries.Altogether, the developed shallow parser identifies predicate-argument structure from the context of residue entities. The extracted information is used as functional annotation.The identification of functional annotations in the scientific literature is a challenging task. It requires the identification of textual features that can be linked to predefined classes. The categories of interest are listed in table The classifiers have been trained on the proposed feature sets and the performance has been measured using a cross-validation scheme. For MAN, the best performing classifiers produced F1 measures of 62%, 57%, and 57% for the categories STR_COMP, CHEM_MOD and BINDING  is 172. This represents the target for protein residue identification.Corresponding to these PORs is the set of functional annotations (PAS data). For 109 out of 172 PORs, keywords were co-mentioned in verbal relations. The number of PAS associated with the 109 PORs is 117. This represents the target of functional annotation extraction.Figure In comparison, if the system would have identified all protein residues correctly, the performance of the whole extraction would have yielded in a precision of 0.68 and a recall of 0.48. This shows that functional annotation can be extracted with a reasonable confidence. The recall can be explained by the performance of the contextual feature extraction module.The result indicates that the extracted functional annotations have a reasonable precision, but are low in coverage. This can be explained by the sum of the performances of each text mining module. On one hand, an incorrectly determined protein residue leads to a false positive of PAS. On the other hand, failed entity recognition contributes to the false negative rate. In addition, language complexity, and incorrectly parsed sentences are the other reasons for the false positive and false negative rate of functional annotation extraction.Despite the low coverage of the functional annotation extraction system, the extracted information is correct and reusable for the annotation of protein residues. A comparison with UniProtKb shows, that 5 out of 16 are rediscovered knowledge .The following information was extracted and semantic categories were assigned to the arguments of the PASpred = inhibitedarg1 = Specific bindingCHEM_MODarg1-of = [the WT and mutant receptors CYS14ALA and CYS199ALA]/arg2-in = the presencearg2-of = the disulfide bond reducing agent.Although, one part of the information in the example has been correctly assigned with the label CHEM_MOD, the entire text phrase should be labeled with BINDING. A solution to this problem is not trivial and requires several levels of linguistic analysis.The aim of this work was to compile protein residue features from MEDLINE texts as annotation for UniProtKb proteins by combining a series of previously studied text mining methods. Although the performances of each module may not be at optimal level, the generated data output indicates that the strategy is able to deliver biological meaningful results. Cross-validation with UniProtKb analysis indicates that the extraction contains novel information that can complement and update the knowledge in UniProtKb and consequently provide annotations for PDB protein structures. However, as with high performing biological entity recognition and relation extraction systems become more available, this conceptual strategy in protein residue annotation extraction may yield optimal results for the biological community.It is important to note that the extraction was done only on abstract texts from MEDLINE. The benefits lie in the broad coverage of biological topics, and the open access to a vast amount of scientific articles, which are advantageous for evaluating the biological significance of residues in proteins from various biological context. However, we acknowledge that the goal in this specialised information extraction task is to be able to find relevant data from full text articles. Considering that full text documents contain more information than abstract texts, and that this setup is more advantageous for previously reported point mutation identification systems, it is interesting to see how the proposed functional annotation extraction system performs on full text articles.The authors declare that they have no competing interests.Kevin Nagel carried out the experiments, developed and implemented the methods, assessed the annotations, and drafted the manuscript. Antonio Jimeno-Yepes participated in the development of the methods and drafted the manuscript. Dietrich Rebholz-Schuhmann participated in design of the experiments, assessed the annotation and drafted the manuscript. All authors read and approved the final manuscript.Labeled termlist according to the MAN scheme. The listed terms were found according to a substring analysis of noun phrases with identified protein residues with the whole string of other coocurring noun phrases . The terms were manually assigned to categories from the categorisation scheme MAN.Click here for fileComparison of extracted functional annotations from GC with UniProtKb. Comparison of extracted protein residue annotations from GC with UniProtKb. Mined functional annotations are listed as PAS, while relevant information from UniProtKb are reproduced from the feature table entry line.Click here for file


Recent advances in the field of high-throughput genomics have rendered possible the performance of genome-scale studies to define the nucleosomal landscapes of eukaryote genomes. Such analyses are aimed towards providing a better understanding of the process of nucleosome positioning, for which several models have been suggested. Nevertheless, questions regarding the sequence constraints of nucleosomal DNA and how they may have been shaped through evolution remain open. In this paper, we analyze in detail different experimental nucleosome datasets with the aim of providing a hypothesis for the emergence of nucleosome-forming sequences.Saccharomyces cerevisiae) as defined in the output of two independent experiments with the use of two different experimental techniques. We found that < 10% of the experimentally defined nucleosome positions were consistently positioned in both datasets. This subset of well-positioned nucleosomes, when compared with the bulk, was shown to have particular properties at both sequence and structural levels. Consistently positioned nucleosomes were also shown to occur preferentially in pairs of dinucleosomes, and to be surprisingly less conserved compared with their adjacent nucleosome-free linkers.We compared the complete sets of nucleosome positions for the budding yeast (Our findings may be combined into a hypothesis for the emergence of a weak nucleosome-positioning code. According to this hypothesis, consistent nucleosomes may be partly guided by nearby nucleosome-free regions through statistical positioning. Once established, a set of well-positioned consistent nucleosomes may impose secondary constraints that further shape the structure of the underlying DNA. We were able to capture these constraints through the application of a recently introduced structural property that is related to the symmetry of DNA curvature. Furthermore, we found that both consistently positioned nucleosomes and their adjacent nucleosome-free regions show an increased tendency towards conservation of this structural feature. Recent studies have suggested that the nucleosomal organization of eukaryotic genome, should not be considered a mere obstacle but rather a vital component of fundamental molecular processes, such as transcriptional regulation ,2 or repet al.  value was calculated on the basis of mean and standard deviation values of SymCurv for the complete yeast genome. Thus, the average values were set around 0.L, its average SymCurv value was initially calculated as described above. We then produced the complete set of DNA sequences, which differ from the original by one nucleotide, by mutating all individual positions but keeping the rest of the sequence intact. For a sequence of length L, there are 3L one-nucleotide mutants or neighbors. We then calculated the average SymCurv values for all neighbors and defined the distance within them as the variance of the four values for each nucleotide position. Thus for nucleotide i the distance D(i) is:The robustness of SymCurv values was then tested. Given a DNA sequence of length SymCurv[X] is the value of SymCurv at the i-th nucleotide for the neighbor bearing nucleotide X at that specific position.where seq Dis then calculated as the average over all L positions:The overall distance for the complete sequence R) as the negative logarithm of the above distance:As high variance is a measure of variability, which is inversely related to robustness, we may define robustness  exhibit a range of values over several orders of magnitude.The logarithm is used here to decrease the dynamic range of seq Ris used as a measure of the variance of the SymCurv values between the one-nucleotide neighbors. It represents the tendency of a given sequence to radically alter its structural properties (as measured by SymCurv) given a single mutation anywhere within it. In this sense, robust sequences will tend to have low (strongly negative) values of D. By contrast, sequences under strong structural constraints will tend to have increased variance, as even single nucleotide mutations may bring about notable changes in the structural profile, and their robustness will therefore be decreased.A property such as The authors declare that they have no competing interests.CN conceived the study, performed the SymCurv analysis, suggested the model and wrote the paper. SA carried out the computational analyses. MB coordinated the project and reviewed the manuscript. RG suggested the study, coordinated the project, designed the analyses, and reviewed the manuscript. All authors read and approved the final manuscript.Additional information on the definition and validation of consistent nucleosomes. Text containing additional information on the definition and validation of consistent nucleosomes.Click here for file