Clustering incorporating shortest paths identifies relevant modules in functional interaction networks

Jennifer Hallinan; Matthew Pocock; Stephen Addinall; David A. Lydall; Anil Wipat

doi:10.1109/CIBCB.2009.4925733

Clustering incorporating shortest paths identifies relevant modules in functional interaction networks

Jennifer Hallinan^*, Matthew Pocock, Stephen Addinall, David A. Lydall, Anil Wipat

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution

Abstract

Many biological systems can be modeled as networks. Hence, network analysis is of increasing importance to systems biology. We describe an evolutionary algorithm for selecting clusters of nodes within a large network based upon network topology together with a measure of the relevance of nodes to a set of independently identified genes of interest. We apply the algorithm to a previously published integrated functional network of yeast genes, using a set of query genes derived from a whole genome screen of yeast strains with a mutation in a telomere uncapping gene. We find that the algorithm identifies biologically plausible clusters of genes which are related to the cell cycle, and which contain interactions not previously identified as potentially important. We conclude that the algorithm is valuable for the querying of complex networks, and the generation of biological hypotheses.

Original language	English
Title of host publication	2009 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB 2009 - Proceedings
Place of Publication	Piscataway, NJ
Publisher	Institute of Electrical and Electronics Engineers (IEEE)
Pages	228-236
Number of pages	9
ISBN (Print)	9781424427567
DOIs	https://doi.org/10.1109/CIBCB.2009.4925733
Publication status	Published - Apr 2009
Externally published	Yes
Event	2009 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB - 2009 - Nashville, United States Duration: 30 Mar 2009 → 2 Apr 2009

Other

Other	2009 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB - 2009
Country	United States
City	Nashville
Period	30/03/09 → 2/04/09

Access to Document

10.1109/CIBCB.2009.4925733

Link to publication in Scopus

Fingerprint Dive into the research topics of 'Clustering incorporating shortest paths identifies relevant modules in functional interaction networks'. Together they form a unique fingerprint.

Cite this

Hallinan, J., Pocock, M., Addinall, S., Lydall, D. A., & Wipat, A. (2009). Clustering incorporating shortest paths identifies relevant modules in functional interaction networks. In 2009 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB 2009 - Proceedings (pp. 228-236). [4925733] Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/CIBCB.2009.4925733

Hallinan, Jennifer ; Pocock, Matthew ; Addinall, Stephen ; Lydall, David A. ; Wipat, Anil. / Clustering incorporating shortest paths identifies relevant modules in functional interaction networks. 2009 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB 2009 - Proceedings. Piscataway, NJ : Institute of Electrical and Electronics Engineers (IEEE), 2009. pp. 228-236

@inproceedings{cc7e3c724cb6489f820322e43056037b,

title = "Clustering incorporating shortest paths identifies relevant modules in functional interaction networks",

abstract = "Many biological systems can be modeled as networks. Hence, network analysis is of increasing importance to systems biology. We describe an evolutionary algorithm for selecting clusters of nodes within a large network based upon network topology together with a measure of the relevance of nodes to a set of independently identified genes of interest. We apply the algorithm to a previously published integrated functional network of yeast genes, using a set of query genes derived from a whole genome screen of yeast strains with a mutation in a telomere uncapping gene. We find that the algorithm identifies biologically plausible clusters of genes which are related to the cell cycle, and which contain interactions not previously identified as potentially important. We conclude that the algorithm is valuable for the querying of complex networks, and the generation of biological hypotheses.",

author = "Jennifer Hallinan and Matthew Pocock and Stephen Addinall and Lydall, {David A.} and Anil Wipat",

year = "2009",

month = "4",

doi = "10.1109/CIBCB.2009.4925733",

language = "English",

isbn = "9781424427567",

pages = "228--236",

booktitle = "2009 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB 2009 - Proceedings",

publisher = "Institute of Electrical and Electronics Engineers (IEEE)",

address = "United States",

}

Hallinan, J, Pocock, M, Addinall, S, Lydall, DA & Wipat, A 2009, Clustering incorporating shortest paths identifies relevant modules in functional interaction networks. in 2009 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB 2009 - Proceedings., 4925733, Institute of Electrical and Electronics Engineers (IEEE), Piscataway, NJ, pp. 228-236, 2009 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB - 2009, Nashville, United States, 30/03/09. https://doi.org/10.1109/CIBCB.2009.4925733

Clustering incorporating shortest paths identifies relevant modules in functional interaction networks. / Hallinan, Jennifer; Pocock, Matthew; Addinall, Stephen; Lydall, David A.; Wipat, Anil.

2009 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB 2009 - Proceedings. Piscataway, NJ : Institute of Electrical and Electronics Engineers (IEEE), 2009. p. 228-236 4925733.

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution

TY - GEN

T1 - Clustering incorporating shortest paths identifies relevant modules in functional interaction networks

AU - Hallinan, Jennifer

AU - Pocock, Matthew

AU - Addinall, Stephen

AU - Lydall, David A.

AU - Wipat, Anil

PY - 2009/4

Y1 - 2009/4

N2 - Many biological systems can be modeled as networks. Hence, network analysis is of increasing importance to systems biology. We describe an evolutionary algorithm for selecting clusters of nodes within a large network based upon network topology together with a measure of the relevance of nodes to a set of independently identified genes of interest. We apply the algorithm to a previously published integrated functional network of yeast genes, using a set of query genes derived from a whole genome screen of yeast strains with a mutation in a telomere uncapping gene. We find that the algorithm identifies biologically plausible clusters of genes which are related to the cell cycle, and which contain interactions not previously identified as potentially important. We conclude that the algorithm is valuable for the querying of complex networks, and the generation of biological hypotheses.

AB - Many biological systems can be modeled as networks. Hence, network analysis is of increasing importance to systems biology. We describe an evolutionary algorithm for selecting clusters of nodes within a large network based upon network topology together with a measure of the relevance of nodes to a set of independently identified genes of interest. We apply the algorithm to a previously published integrated functional network of yeast genes, using a set of query genes derived from a whole genome screen of yeast strains with a mutation in a telomere uncapping gene. We find that the algorithm identifies biologically plausible clusters of genes which are related to the cell cycle, and which contain interactions not previously identified as potentially important. We conclude that the algorithm is valuable for the querying of complex networks, and the generation of biological hypotheses.

UR - http://www.scopus.com/inward/record.url?scp=67650360801&partnerID=8YFLogxK

U2 - 10.1109/CIBCB.2009.4925733

DO - 10.1109/CIBCB.2009.4925733

M3 - Conference proceeding contribution

SN - 9781424427567

SP - 228

EP - 236

BT - 2009 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB 2009 - Proceedings

PB - Institute of Electrical and Electronics Engineers (IEEE)

CY - Piscataway, NJ

ER -

Hallinan J, Pocock M, Addinall S, Lydall DA, Wipat A. Clustering incorporating shortest paths identifies relevant modules in functional interaction networks. In 2009 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB 2009 - Proceedings. Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE). 2009. p. 228-236. 4925733 https://doi.org/10.1109/CIBCB.2009.4925733