Detecting functional modules in the yeast protein-protein interaction network Export

@article{citeulike:846789, abstract = {MOTIVATION: Identification of functional modules in protein interaction networks is a first step in understanding the organization and dynamics of cell functions. To ensure that the identified modules are biologically meaningful, network-partitioning algorithms should take into account not only topological features but also functional relationships, and identified modules should be rigorously validated. RESULTS: In this study we first integrate proteomics and microarray datasets and represent the yeast protein-protein interaction network as a weighted graph. We then extend a betweenness-based partition algorithm, and use it to identify 266 functional modules in the yeast proteome network. For validation we show that the functional modules are indeed densely connected subgraphs. In addition, genes in the same functional module confer a similar phenotype. Furthermore, known protein complexes are largely contained in the functional modules in their entirety. We also analyze an example of a functional module and show that functional modules can be useful for gene annotation. CONTACT: yuan.33@osu.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.}, author = {Jingchun, Chen and Bo, Yuan}, citeulike-article-id = {846789}, citeulike-linkout-0 = {http://dx.doi.org/10.1093/bioinformatics/btl370}, citeulike-linkout-1 = {http://bioinformatics.oxfordjournals.org/cgi/content/abstract/22/18/2283}, citeulike-linkout-2 = {http://www.ingentaconnect.com/content/oup/cabios/2006/00000022/00000018/art02283}, citeulike-linkout-3 = {http://view.ncbi.nlm.nih.gov/pubmed/16837529}, citeulike-linkout-4 = {http://www.hubmed.org/display.cgi?uids=16837529}, doi = {10.1093/bioinformatics/btl370}, issn = {1367-4803}, journal = {Bioinformatics}, keywords = {betweenness, modularity, probmod, weighted}, month = {September}, number = {18}, pages = {2283--2290}, posted-at = {2008-06-18 21:50:25}, priority = {2}, publisher = {Oxford University Press}, title = {Detecting functional modules in the yeast protein-protein interaction network}, url = {http://dx.doi.org/10.1093/bioinformatics/btl370}, volume = {22}, year = {2006} }

TY - JOUR ID - citeulike:846789 L3 - citeulike-article-id:846789 N2 - MOTIVATION: Identification of functional modules in protein interaction networks is a first step in understanding the organization and dynamics of cell functions. To ensure that the identified modules are biologically meaningful, network-partitioning algorithms should take into account not only topological features but also functional relationships, and identified modules should be rigorously validated. RESULTS: In this study we first integrate proteomics and microarray datasets and represent the yeast protein-protein interaction network as a weighted graph. We then extend a betweenness-based partition algorithm, and use it to identify 266 functional modules in the yeast proteome network. For validation we show that the functional modules are indeed densely connected subgraphs. In addition, genes in the same functional module confer a similar phenotype. Furthermore, known protein complexes are largely contained in the functional modules in their entirety. We also analyze an example of a functional module and show that functional modules can be useful for gene annotation. CONTACT: yuan.33@osu.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. IS - 18 JF - Bioinformatics SN - 1367-4803 EP - 2290 TI - Detecting functional modules in the yeast protein-protein interaction network PB - Oxford University Press VL - 22 SP - 2283 KW - betweenness KW - modularity KW - probmod KW - weighted AU - Jingchun, Chen AU - Bo, Yuan PY - 2006/09/15/ UR - http://dx.doi.org/10.1093/bioinformatics/btl370 ER -