A graph theoretical approach to experimental prioritization in genome-scale investigations.

ABSTRACT: The goal of systems biology is to gain a network level understanding of how gene interactions influence biological states, and ultimately inform upon human disease. Given the scale and scope of systems biology studies, resource constraints often limit researchers when validating genome-wide phenomena and potentially lead to an incomplete understanding of the underlying mechanisms. Further, prioritization strategies are often biased towards known entities (e.g. previously studied genes/proteins with commercially available reagents), and other technical issues that limit experimental breadth. Here, heterogeneous biological information is modeled as an association graph to which a high-performance minimum dominating set solver is applied to maximize coverage across the graph, and thus increas

SUBMITTER: Grady SK 

PROVIDER: S-EPMC11522061 | biostudies-literature | 2024 Dec

REPOSITORIES: biostudies-literature