BLOBFISH: Bipartite Limited Subnetworks from Multiple Observations using Breadth-First Search with Constrained Hops.
Tara Eicher1, Marouen Ben Guebila1, John Quackenbush1,2
1Department of Biostatistics, T.H. Chan School of Public Health, Harvard University, Boston, MA, 02115, USA.
Biorxiv : the Preprint Server for Biology
|April 8, 2025
Summary
BLOBFISH identifies gene regulatory subnetworks by connecting gene sets. This tool provides regulatory context for phenotypes using tissue-specific data.
Area of Science:
- Bioinformatics
- Systems Biology
- Genomics
Background:
- Analyzing gene regulatory networks often involves understanding connections within specific gene sets.
- Identifying regulatory relationships is crucial for understanding biological mechanisms and phenotypes.
Purpose of the Study:
- To introduce BLOBFISH, a novel algorithm for extracting compact gene regulatory subnetworks.
- To provide a method for exploring the regulatory context of pre-specified gene sets.
Main Methods:
- BLOBFISH employs a breadth-first search algorithm adapted for bipartite graphs.
- The algorithm identifies subnetworks connecting user-defined gene sets.
Main Results:
- BLOBFISH successfully extracts gene regulatory subnetworks that reflect tissue specificity.
- Demonstrated application using publicly available Genotype Tissue Expression (GTEx) project data.
Conclusions:
- BLOBFISH offers a valuable tool for dissecting gene regulatory networks.
- The method aids in uncovering specific mechanisms underlying phenotypes and their development.
