Ensemble Non-negative Matrix Factorization Methods for Clustering Protein-Protein Interactions

@article{citeulike:2932383, abstract = {Motivation: When working with large-scale protein interaction data, an important analysis task is the assignment of pairs of proteins to groups that correspond to higher order assemblies. Previously a common approach to this problem has been to apply standard hierarchical clustering methods to identify such a groups. Here we propose a new algorithm for aggregating a diverse collection of matrix factorizations to produce a more informative clustering, which takes the form of a "soft" hierarchy of clusters. Results: We apply the proposed Ensemble NMF algorithm to a high-quality assembly of binary protein interactions derived from two proteome-wide studies in yeast. Our experimental evaluation demonstrates that the algorithm lends itself to discovering small localized structures in this data, which correspond to known functional groupings of complexes. In addition, we show that the algorithm also supports the assignment of putative functions for previously uncharacterized proteins, for instance the protein YNR024W, which may be an uncharacterized component of the exosome. Contact: derek.greene@ucd.ie Supplementary information: http://mlg.ucd.ie/nmf 10.1093/bioinformatics/btn286}, author = {Greene, Derek and Cagney, Gerard and Krogan, Nevan and Cunningham, Padraig }, citeulike-article-id = {2932383}, doi = {10.1093/bioinformatics/btn286}, journal = {Bioinformatics}, keywords = {clustering, interaction, protein}, month = {June}, pages = {btn286+}, posted-at = {2008-06-27 03:43:26}, priority = {2}, title = {Ensemble Non-negative Matrix Factorization Methods for Clustering Protein-Protein Interactions}, url = {http://dx.doi.org/10.1093/bioinformatics/btn286}, year = {2008} }

TY - JOUR ID - citeulike:2932383 L3 - citeulike-article-id:2932383 TI - Ensemble Non-negative Matrix Factorization Methods for Clustering Protein-Protein Interactions JF - Bioinformatics SP - btn286 N2 - Motivation: When working with large-scale protein interaction data, an important analysis task is the assignment of pairs of proteins to groups that correspond to higher order assemblies. Previously a common approach to this problem has been to apply standard hierarchical clustering methods to identify such a groups. Here we propose a new algorithm for aggregating a diverse collection of matrix factorizations to produce a more informative clustering, which takes the form of a "soft" hierarchy of clusters. Results: We apply the proposed Ensemble NMF algorithm to a high-quality assembly of binary protein interactions derived from two proteome-wide studies in yeast. Our experimental evaluation demonstrates that the algorithm lends itself to discovering small localized structures in this data, which correspond to known functional groupings of complexes. In addition, we show that the algorithm also supports the assignment of putative functions for previously uncharacterized proteins, for instance the protein YNR024W, which may be an uncharacterized component of the exosome. Contact: derek.greene@ucd.ie Supplementary information: http://mlg.ucd.ie/nmf 10.1093/bioinformatics/btn286 KW - clustering KW - interaction KW - protein AU - Greene, Derek AU - Cagney, Gerard AU - Krogan, Nevan AU - Cunningham, Padraig PY - 2008/06/12/ UR - http://dx.doi.org/10.1093/bioinformatics/btn286 ER -