Evaluation of different domain-based methods in protein interaction prediction.
Protein-protein interactions (PPIs) play an important role in many biological functions. PPIs typically involve binding between domains, the basic units of protein folding, evolution and function. Identifying domain-domain interactions (DDIs) would aid understanding PPI networks. Recently, many computational methods aimed to infer DDIs from databases of interacting proteins and subsequently used the inferred DDIs to predict new PPIs. We attempt to describe systematically current domain-based approaches including the association method, maximum likelihood estimation and parsimonious explanation method. The performance of these methods at inferring DDIs and predicting PPIs was evaluated comparatively. We observe that each method generates artefacts in certain situations and discuss biases in the available benchmark sets.
Institute of Biotechnology, PO Box 56, University of Helsinki, 00014 Helsinki, Finland. xuanhung.ta@helsinki.fi
Hung Xuan
HX
Ta
Liisa
L
Holm
D019295:Computational Biology / Q000379:methods*; D016013:Likelihood Functions; D054730:Protein Interaction Domains and Motifs; D025941:Protein Interaction Mapping; D020539:Sequence Analysis, Protein / Q000379:methods*