Knowledge-based analysis of proteomics data

被引:76
作者
Bessarabova, Marina [1 ]
Ishkin, Alexander [1 ]
JeBailey, Lellean [1 ]
Nikolskaya, Tatiana [1 ]
Nikolsky, Yuri [1 ]
机构
[1] Thomson Reuters, IP & Sci, Carlsbad, CA 92008 USA
来源
BMC BIOINFORMATICS | 2012年 / 13卷
关键词
GENE SET ENRICHMENT;
D O I
10.1186/1471-2105-13-S16-S13
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
As it is the case with any OMICs technology, the value of proteomics data is defined by the degree of its functional interpretation in the context of phenotype. Functional analysis of proteomics profiles is inherently complex, as each of hundreds of detected proteins can belong to dozens of pathways, be connected in different context-specific groups by protein interactions and regulated by a variety of one-step and remote regulators. Knowledge-based approach deals with this complexity by creating a structured database of protein interactions, pathways and protein-disease associations from experimental literature and a set of statistical tools to compare the proteomics profiles with this rich source of accumulated knowledge. Here we describe the main methods of ontology enrichment, interactome topology and network analysis applied on a comprehensive, manually curated and semantically consistent knowledge source MetaBase and demonstrate several case studies in different disease areas.
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收藏
页数:19
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