Complex discovery from weighted PPI networks | Zendy

Guimei Liu | Zendy; Limsoon Wong | Zendy; Hon Nian Chua | Zendy

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Complex discovery from weighted PPI networks

Author(s) -

Guimei Liu,

Limsoon Wong,

Hon Nian Chua

Publication year - 2009

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btp311

Subject(s) - computer science , cluster analysis , reliability (semiconductor) , iterative method , noise (video) , interconnectivity , data mining , function (biology) , throughput , interaction network , algorithm , artificial intelligence , chemistry , biology , telecommunications , power (physics) , physics , quantum mechanics , evolutionary biology , image (mathematics) , wireless , biochemistry , gene

Protein complexes are important for understanding principles of cellular organization and function. High-throughput experimental techniques have produced a large amount of protein interactions, which makes it possible to predict protein complexes from protein-protein interaction (PPI) networks. However, protein interaction data produced by high-throughput experiments are often associated with high false positive and false negative rates, which makes it difficult to predict complexes accurately.

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