Abstract
PathLinker is a graph-theoretic algorithm for reconstructing the interactions in a signaling pathway of interest. It efficiently computes multiple short paths within a background protein interaction network from the receptors to transcription factors (TFs) in a pathway. We originally developed PathLinker to complement manual curation of signaling pathways, which is slow and painstaking. The method can be used in general to connect any set of sources to any set of targets in an interaction network. The app presented here makes the PathLinker functionality available to Cytoscape users. We present an example where we used PathLinker to compute and analyze the network of interactions connecting proteins that are perturbed by the drug lovastatin.
Highlights
Signaling pathways are a cornerstone of systems biology
We describe in detail a use case where we employ PathLinker to analyze the Environmental Protection Agency’s Toxicity Forecaster (ToxCast) data
We demonstrate how we applied the ClueGo app for functional enrichment[19] to see if the lovastatin sub-network was enriched for any Gene Ontology (GO) terms or KEGG pathways
Summary
2. Tamás Korcsmáros , Earlham Institute, Norwich, UK David Fazekas, Eotvos Lorand University, Budapest, Hungary. This article is included in the International Society for Computational Biology Community. Any reports and responses or comments on the article can be found at the end of the article. This article is included in the Cytoscape gateway
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