Inferring functional communities from partially observed biological networks exploiting geometric topology and side information.

ABSTRACT: Cellular biological networks represent the molecular interactions that shape function of living cells. Uncovering the organization of a biological network requires efficient and accurate algorithms to determine the components, termed communities, underlying specific processes. Detecting functional communities is challenging because reconstructed biological networks are always incomplete due to technical bias and biological complexity, and the evaluation of putative communities is further complicated by a lack of known ground truth. To address these challenges, we developed a geometric-based detection framework based on Ollivier-Ricci curvature to exploit information about network topology to perform community detection from partially observed biological networks. We further improved this a

SUBMITTER: Sia J 

PROVIDER: S-EPMC9237089 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature