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Cited by 1,197Bioinformatics and Genomic NetworksGene Regulatory Network AnalysisFungal and yeast genetics research

Discovering regulatory and signalling circuits in molecular interaction networks

Ideker, Trey, Ozier, Owen, Schwikowski, Benno, Siegel, Andrew F.·2002·Bioinformatics
DOI 10.1093/bioinformatics/18.suppl_1.s233
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Abstract

Motivation: In model organisms such as yeast, large databases of protein–protein and protein-DNA interactions have become an extremely important resource for the study of protein function, evolution, and gene regulatory dynamics. In this paper we demonstrate that by integrating these interactions with widely-available mRNA expression data, it is possible to generate concrete hypotheses for the underlying mechanisms governing the observed changes in gene expression. To perform this integration systematically and at large scale, we introduce an approach for screening a molecular interaction network to identify active subnetworks, i.e., connected regions of the network that show significant changes in expression over particular subsets of conditions. The method we present here combines a rigorous statistical measure for scoring subnetworks with a search algorithm for identifying subnetworks with high score. Results: We evaluated our procedure on a small network of 332 genes and 362 interactions and a large network of 4160 genes containing all 7462 protein–protein and protein-DNA interactions in the yeast public databases. In the case of the small network, we identified five significant subnetworks that covered 41 out of 77 (53%) of all significant changes in expression. Both network analyses returned several top-scoring subnetworks with good correspondence to known regulatory mechanisms in the literature. These results demonstrate how large-scale genomic approaches may be used to uncover signalling and regulatory pathways in a systematic, integrative fashion. Availability: The methods presented in this paper are implemented in the Cytoscape software package which is available to the academic community at http://www.cytoscape.org. Contact: trey@wi.mit.edu Keywords: molecular interactions; gene expression; data integration; simulated annealing; Monte carlo methods. *To whom correspondence should be addressed.

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Crossref · 10.1093/bioinformatics/18.suppl_1.s233

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  • A number of recent papers have used pathway analysis workflow to highlight genes and pathways active in specific model organisms or diseased tissues.

    “A number of recent papers have used this pathway analysis workflow to highlight genes and pathways that are active in specific model organisms or diseased tissues, such as breast cancer, using gene and protein expression, copy number variants (CNVs) and SNPs19,44-49.”

    From The BioPAX community standard for pathway data sharing (2010) · cites this paper as [46]

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Authors
Ideker, T., Ozier, O., Schwikowski, B., & Siegel, A. F.
Affiliations
Institute for Systems Biology (US)
ORCID
Venue
Bioinformatics
Publisher
Oxford University Press (OUP)
Published
2002-07-01
Volume
18
Issue
suppl_1
Pages
S233-S240
ISSN
  • 1367-4803 (ISSN-L)
  • 1367-4811
DOI
10.1093/bioinformatics/18.suppl_1.s233
OpenAlex
W2112811019
Cited by
1,197
References
15
Citations by year
2026: 5 · 2025: 9 · 2024: 31 · 2023: 26 · 2022: 30 · 2021: 50 · 2020: 56 · 2019: 49 · 2018: 53 · 2017: 73 · 2016: 62 · 2015: 76 · 2014: 85 · 2013: 96 · 2012: 73
FWCI
12.20
Type
journal article
Language
en
Open access
closed
Locations
  • Bioinformatics (publishedVersion)
  • PubMed (publishedVersion)
Funders
Pfizer
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene Regulatory Network Analysis
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Fungal and yeast genetics research
Keywords
molecular interaction networks, protein-protein interaction, protein-DNA interactions, gene regulatory networks, signaling pathways, subnetwork identification, gene expression changes, yeast, simulated annealing, Monte Carlo search, Cytoscape
MeSH terms
Algorithms, Computer Simulation, Gene Expression Regulation, Models, Biological, Yeasts, Signal Transduction, Proteome, Gene Expression Profiling

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