BLOBFISH: Bipartite Limited Subnetworks from Multiple Observations using Breadth-First Search with Constrained Hops
Abstract
SummaryIn analyzing gene regulatory network models, a common question is how members of a particular set of genes are connected. For example, one might want to explore network relationship between a set of differentially expressed genes, a gene set previously reported in the literature, or elements of one or more pathways. BLOBFISH uses a breadth-first search algorithm adapted to bipartite graphs to identify a compact subnetwork connecting the members of a pre-specified set of genes, providing a regulatory context that can shed light on specific mechanisms involved in a phenotype and its development. We demonstrate the use of BLOBFISH to extract gene regulatory subnetworks reflecting tissue specificity using publicly available data from the Genotype Tissue Expression (GTEx) project.
02 /Specification & Classification
Click any tag to browse matching papers- Citations
- 2
- FWCI
- 4.10
- Field percentile
- top 10%
- Organism
- Assay
- Research Focus
- Approach
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- Sharing and specificity of co-expression networks across 35 human tissues
Emma Pierson, GTEx Consortium, … Sara Mostafavi·PLOS Computational BiologyPeer-reviewed·May 13, 2015
- Composition structures and biologically meaningful logics: plausibility and relevance in bipartite models of gene regulation
Yasharth Yadav, Ajay Subbaroyan, … Areejit Samal·bioRxiv·May 7, 2022
- NetREX: Network Rewiring using EXpression - Towards Context Specific Regulatory Networks
Yijie Wang, Dong-Yeon Cho, … Teresa M. Przytycka·bioRxiv·Apr 24, 2017
- Capturing context-specific regulation in molecular interaction networks
Stephen T. A. Rush, Dirk Repsilber·BMC BioinformaticsPeer-reviewed·Dec 1, 2018
- Comparison of single gene and module-based methods for modeling gene regulatory networks
Mikel Hernáez, Charles A. Blatti, Olivier Gevaert·BioinformaticsPeer-reviewed·Jul 6, 2019
- A Scalable Algorithm for Structure Identification of Complex Gene Regulatory Network from Temporal Expression Data
Shupeng Gui, Rui Chen, … Hongyu Miao·BMC BioinformaticsPeer-reviewed·Jan 31, 2017