Prediction of Protein Function Using Protein–Protein Interaction Data
Prediction of Protein Function Using Protein–Protein Interaction Data is a scholarly work, published in 2003 in ''Journal of Computational Biology''. The main subjects of the publication include gene regulatory network, protein function prediction, mass spectrometry, data mining, protein-protein interaction, proteome, biological function, computer science, artificial intelligence, Bayesian probability, computational biology, proteomics, microarray, protein, and biology. The authors develop a novel approach that employs the theory of Markov random fields to infer a protein's functions using protein-protein interaction data and the functional annotations of protein's interaction partners.