Is subcellular localization informative for modeling protein-protein interaction signal?
Research Letters in Signal Processing
Domain-Domain Interaction Identification with a Feature Selection Approach
PRIB '08 Proceedings of the Third IAPR International Conference on Pattern Recognition in Bioinformatics
Artificial Neural Network Based Algorithm for Biomolecular Interactions Modeling
IWANN '09 Proceedings of the 10th International Work-Conference on Artificial Neural Networks: Part I: Bio-Inspired Systems: Computational and Ambient Intelligence
Information Sciences: an International Journal
Using a stochastic adaboost algorithm to discover interactome motif pairs from sequences
ICIC'06 Proceedings of the 2006 international conference on Computational Intelligence and Bioinformatics - Volume Part III
A Computational Model for Predicting Protein Interactions Based on Multidomain Collaboration
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
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Motivation: Identifying protein--protein interactions is critical for understanding cellular processes. Because protein domains represent binding modules and are responsible for the interactions between proteins, computational approaches have been proposed to predict protein interactions at the domain level. The fact that protein domains are likely evolutionarily conserved allows us to pool information from data across multiple organisms for the inference of domain--domain and protein--protein interaction probabilities. Results: We use a likelihood approach to estimating domain--domain interaction probabilities by integrating large-scale protein interaction data from three organisms, Saccharomyces cerevisiae, Caenorhabditis elegans and Drosophila melanogaster. The estimated domain--domain interaction probabilities are then used to predict protein--protein interactions in S.cerevisiae. Based on a thorough comparison of sensitivity and specificity, Gene Ontology term enrichment and gene expression profiles, we have demonstrated that it may be far more informative to predict protein--protein interactions from diverse organisms than from a single organism. Availability: The program for computing the protein--protein interaction probabilities and supplementary material are available at http://bioinformatics.med.yale.edu/interaction Contact: hongyu.zhao@yale.edu