Predicting protein-protein interactions from multimodal biological data sources via nonnegative matrix tri-factorization

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 7262 LNBI, Issue , 2012, Pages 314-325

  Wang, Hua ^a   Huang, Heng ^a   Ding, Chris ^a   Nie, Feiping ^a  

^a The University of Texas at Arlington   (United States)

Author keywords

Multimodal Biological Data; Nonnegative Matrix Factorization; Protein Protein Interaction

Indexed keywords

BIOLOGICAL DATA; CLASSIFICATION BASED METHODS; CLASSIFICATION MODELS; EXPERIMENTAL METHODS; FALSE POSITIVE RATES; FUNCTIONAL ASSOCIATIONS; HIGH-THROUGHPUT; MATRIX COMPLETION; MULTI-MODAL; NON-NEGATIVE MATRIX; NONNEGATIVE MATRIX FACTORIZATION; PHYSICAL INTERACTIONS; PROTEIN INTERACTION; PROTEIN INTERACTION NETWORKS; PROTEIN SEQUENCES; PROTEIN STRUCTURES; PROTEIN-PROTEIN INTERACTIONS; PUTATIVE PROTEINS; SACCHAROMYCES CEREVISIAE GENOME; SPARSE MATRICES;

ASSOCIATION REACTIONS; FACTORIZATION; FORECASTING; GENE EXPRESSION; MATRIX ALGEBRA; MODELS; MOLECULAR BIOLOGY; MOLECULAR STRUCTURE; YEAST;

PROTEINS;

EID: 84860831442     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-29627-7_33     Document Type: Conference Paper

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