Ensemble non-negative matrix factorization methods for clustering protein-protein interactions

Derek Greene, Gerard Cagney, Nevan Krogan, Pádraig Cunningham

Research output: Contribution to journalArticlepeer-review

76 Scopus citations

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 non-negative matrix factorization (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.

Original languageEnglish
Pages (from-to)1722-1728
Number of pages7
JournalBioinformatics
Volume24
Issue number15
DOIs
StatePublished - Aug 2008
Externally publishedYes

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