Predicting protein-protein interactions from primary structure

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dc.contributor.advisorSubramanian, Devikaen_US
dc.creatorBandyopadhyay, Rajarshien_US
dc.date.accessioned2009-06-04T06:45:13Zen_US
dc.date.available2009-06-04T06:45:13Zen_US
dc.date.issued2002en_US
dc.description.abstractOne of the key challenges in the post-genomic era is to understand protein-protein interactions on a large scale. Given the primary structures of proteins and ligands, along with other information, how well can we computationally predict protein-protein interaction networks? We train Naive Bayes classifiers to classify positive and negative examples of protein-ligand interactions. Such a predictive model can screen large numbers of potential ligands, saving laboratory time and costs. We demonstrate our approach in predicting interactions between SH3 domains and proline-rich ligands. Using laboratory data, we construct positive and negative examples, learn Naive Bayes models of ligand binding specificity of 8 diverse SH3 domains and visualize our models using an information theory-based measure to reveal potential binding sites. We use our classifiers to screen PxxP ligands from SwissProt for the given SH3 domains and demonstrate improvements over existing predictors. For validating our method, we use our technique to predict a computational interaction network and intersect it with an experimental yeast 2-hybrid network, using the methodology and data from Tong et al. [TDN +02]. Our technique produces comparable results to Tong et al., even without incorporating their consensus sequences.en_US
dc.format.extent70 p.en_US
dc.format.mimetypeapplication/pdfen_US
dc.identifier.callnoTHESIS COMP.SCI. 2002 BANDYOPADHYAYen_US
dc.identifier.citationBandyopadhyay, Rajarshi. "Predicting protein-protein interactions from primary structure." (2002) Master’s Thesis, Rice University. <a href="https://hdl.handle.net/1911/17492">https://hdl.handle.net/1911/17492</a>.en_US
dc.identifier.urihttps://hdl.handle.net/1911/17492en_US
dc.language.isoengen_US
dc.rightsCopyright is held by the author, unless otherwise indicated. Permission to reuse, publish, or reproduce the work beyond the bounds of fair use or other exemptions to copyright law must be obtained from the copyright holder.en_US
dc.subjectBiochemistryen_US
dc.subjectComputer scienceen_US
dc.titlePredicting protein-protein interactions from primary structureen_US
dc.typeThesisen_US
dc.type.materialTexten_US
thesis.degree.departmentComputer Scienceen_US
thesis.degree.disciplineEngineeringen_US
thesis.degree.grantorRice Universityen_US
thesis.degree.levelMastersen_US
thesis.degree.nameMaster of Scienceen_US
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