Challenges and opportunities in network-based solutions for biological questions.
Network biology is useful for modeling complex biological phenomena; it has attracted attention with the advent of novel graph-based machine learning methods. However, biological applications of network methods often suffer from inadequate follow-up. In this perspective, we discuss obstacles for contemporary network approaches-particularly focusing on challenges representing biological concepts, applying machine learning methods, and interpreting and validating computational findings about biology-in an effort to catalyze actionable biological discovery.
['Guo|Margaret G|MG|0000-0001-7713-3846', 'Sosa|Daniel N|DN|0000-0001-7184-8736', 'Altman|Russ B|RB|0000-0003-3859-2905']
networks interpretability biological validation embeddings knowledge graphs