ゲノム情報科学研究教育機構  アブストラクト
Date April 23, 2007
Speaker Dr. Yang Dai, Department of Bioengineering, University of Illinois at Chicago
Title Reconstruction of Functional Gene Networks based on Published Literature
Abstract   Genomics and proteomics technologies have provided unprecedented opportunity to providing a comprehensive survey of the cell's interactome. The mapping of interactions among genes/proteins is extremely important for the understanding of underlying mechanism of the cell. These technologies provide unbiased opportunity for the study.
  However, large body of false positive interactions also presents problems. These problems are partially alleviated by performing (1) the rigorous statistical analysis to derive significant results, and (2) the integration of various genomic, proteomic data and prior biological knowledge. The utilization of prior biological knowledge, especially the information from published literature, can be extremely important.
  However, the existing methods are still primitive; basically forming the networks by taking the sum of all interactions identified from published literature. The resulted networks are static and do not provide information on interactions that have yet to be discovered. Systematic analyses of the literature networks and extraction of knowledge that can be used for the assessment of biological relevance of detected interactions from the experimental data are clearly needed. In this study we address this issue. We propose a novel statistical method to compute the likelihood of interaction (LOI) scores for interactions of each type (regulation, expression, binding, inhibition, and protein modification) obtained from the databases of published literature.
  The Gene Ontology Molecular Function annotations will be used for the representation of functional resemblance among interactions. We demonstrate the effectiveness of this approach through the validation of published literature on yeast and human at genome scale and as well as KEGG and MARK-Signaling curated yeast pathways.
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