Challenges and opportunities in network-based solutions for biological questions

Brief Bioinform. 2022 Jan 17;23(1):bbab437. doi: 10.1093/bib/bbab437.


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.

Keywords: biological validation; embeddings; interpretability; knowledge graphs; networks.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Machine Learning*