A network-based approach for predicting missing pathway interactions

Navlakha, S., Gitter, A., Bar-Joseph, Z. (August 2012) A network-based approach for predicting missing pathway interactions. PLoS Comput Biol, 8 (8). e1002640. ISSN 1553-734x

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URL: https://www.ncbi.nlm.nih.gov/pubmed/22916002
DOI: 10.1371/journal.pcbi.1002640

Abstract

Embedded within large-scale protein interaction networks are signaling pathways that encode response cascades in the cell. Unfortunately, even for well-studied species like S. cerevisiae, only a fraction of all true protein interactions are known, which makes it difficult to reason about the exact flow of signals and the corresponding causal relations in the network. To help address this problem, we introduce a framework for predicting new interactions that aid connectivity between upstream proteins (sources) and downstream transcription factors (targets) of a particular pathway. Our algorithms attempt to globally minimize the distance between sources and targets by finding a small set of shortcut edges to add to the network. Unlike existing algorithms for predicting general protein interactions, by focusing on proteins involved in specific responses our approach homes-in on pathway-consistent interactions. We applied our method to extend pathways in osmotic stress response in yeast and identified several missing interactions, some of which are supported by published reports. We also performed experiments that support a novel interaction not previously reported. Our framework is general and may be applicable to edge prediction problems in other domains.

Item Type: Paper
Subjects: bioinformatics > genomics and proteomics > design > protein network design
bioinformatics > computational biology > algorithms
organs, tissues, organelles, cell types and functions > tissues types and functions > signal transduction
organism description > yeast
CSHL Authors:
Communities: CSHL labs > Navlakha lab
Depositing User: Matthew Dunn
Date: 18 August 2012
Date Deposited: 08 Nov 2019 14:22
Last Modified: 08 Nov 2019 14:22
PMCID: PMC3420932
Related URLs:
URI: https://repository.cshl.edu/id/eprint/38689

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