Functional Analysis of OMICs Data and Small Molecule Compounds in an Integrated “Knowledge-Based” Platform
作者： Yuri Nikolsky , Eugene Kirillov , Roman Zuev , Eugene Rakhmatulin , Tatiana Nikolskaya
DOI: 10.1007/978-1-60761-175-2_10
关键词:
摘要: Analysis of microarray, SNPs, proteomics, and other high-throughput (OMICs) data is challenging because its biological complexity high level technical noise. One way to deal with both problems perform analysis a high-fidelity annotated knowledge base protein interactions, pathways, functional ontologies. This has be structured in computer-readable format must include software tools for managing experimental data, analysis, reporting. Here we present MetaDiscovery, an integrated platform which being developed at GeneGo the past 8 years. On content side, MetaDiscovery encompasses comprehensive database interactions different types, network models 10 ontologies covering human, mouse, rat proteins. The analytical toolkit includes gene/protein list enrichment statistical "interactome" tool identification over- under-connected proteins set, module made up generation algorithms filters. suite also features MetaSearch, application combinatorial search content, as well Java-based called MapEditor drawing editing custom pathway maps. Applications potential biomarkers drug targets, hypothesis generation, effects novel small molecule compounds, clinical applications (analysis large cohorts patients translational personalized medicine).
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