CLARM: An integrative approach for functional modules discovery

Handle URI:
http://hdl.handle.net/10754/564351
Title:
CLARM: An integrative approach for functional modules discovery
Authors:
Salem, Saeed M.; Alroobi, Rami; Banitaan, Shadi; Seridi, Loqmane; Brewer, James E.; Aljarah, Ibrahim
Abstract:
Functional module discovery aims to find well-connected subnetworks which can serve as candidate protein complexes. Advances in High-throughput proteomic technologies have enabled the collection of large amount of interaction data as well as gene expression data. We propose, CLARM, a clustering algorithm that integrates gene expression profiles and protein protein interaction network for biological modules discovery. The main premise is that by enriching the interaction network by adding interactions between genes which are highly co-expressed over a wide range of biological and environmental conditions, we can improve the quality of the discovered modules. Protein protein interactions, known protein complexes, and gene expression profiles for diverse environmental conditions from the yeast Saccharomyces cerevisiae were used for evaluate the biological significance of the reported modules. Our experiments show that the CLARM approach is competitive to wellestablished module discovery methods. Copyright © 2011 ACM.
KAUST Department:
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division; Computer Science Program
Publisher:
Association for Computing Machinery (ACM)
Journal:
Proceedings of the 2nd ACM Conference on Bioinformatics, Computational Biology and Biomedicine - BCB '11
Conference/Event name:
2011 ACM Conference on Bioinformatics, Computational Biology and Biomedicine, ACM-BCB 2011
Issue Date:
2011
DOI:
10.1145/2147805.2147917
Type:
Conference Paper
ISBN:
9781450307963
Appears in Collections:
Conference Papers; Computer Science Program; Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division

Full metadata record

DC FieldValue Language
dc.contributor.authorSalem, Saeed M.en
dc.contributor.authorAlroobi, Ramien
dc.contributor.authorBanitaan, Shadien
dc.contributor.authorSeridi, Loqmaneen
dc.contributor.authorBrewer, James E.en
dc.contributor.authorAljarah, Ibrahimen
dc.date.accessioned2015-08-04T06:24:37Zen
dc.date.available2015-08-04T06:24:37Zen
dc.date.issued2011en
dc.identifier.isbn9781450307963en
dc.identifier.doi10.1145/2147805.2147917en
dc.identifier.urihttp://hdl.handle.net/10754/564351en
dc.description.abstractFunctional module discovery aims to find well-connected subnetworks which can serve as candidate protein complexes. Advances in High-throughput proteomic technologies have enabled the collection of large amount of interaction data as well as gene expression data. We propose, CLARM, a clustering algorithm that integrates gene expression profiles and protein protein interaction network for biological modules discovery. The main premise is that by enriching the interaction network by adding interactions between genes which are highly co-expressed over a wide range of biological and environmental conditions, we can improve the quality of the discovered modules. Protein protein interactions, known protein complexes, and gene expression profiles for diverse environmental conditions from the yeast Saccharomyces cerevisiae were used for evaluate the biological significance of the reported modules. Our experiments show that the CLARM approach is competitive to wellestablished module discovery methods. Copyright © 2011 ACM.en
dc.publisherAssociation for Computing Machinery (ACM)en
dc.titleCLARM: An integrative approach for functional modules discoveryen
dc.typeConference Paperen
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Divisionen
dc.contributor.departmentComputer Science Programen
dc.identifier.journalProceedings of the 2nd ACM Conference on Bioinformatics, Computational Biology and Biomedicine - BCB '11en
dc.conference.date1 August 2011 through 3 August 2011en
dc.conference.name2011 ACM Conference on Bioinformatics, Computational Biology and Biomedicine, ACM-BCB 2011en
dc.conference.locationChicago, ILen
dc.contributor.institutionDepartment of Computer Science, North Dakota State University, Fargo, ND 58102, United Statesen
kaust.authorSeridi, Loqmaneen
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