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BiomarkerDigger: A versatile disease proteome database and analysis platform for the identification of plasma cancer biomarkers
Author(s) -
Jeong SeulKi,
Kwon MinSeok,
Lee EunYoung,
Lee HyoungJoo,
Cho Sang Yun,
Kim Hoguen,
Yoo Jong Shin,
Omenn Gilbert S.,
Aebersold Ruedi,
Hanash Sam,
Paik YoungKi
Publication year - 2009
Publication title -
proteomics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.26
H-Index - 167
eISSN - 1615-9861
pISSN - 1615-9853
DOI - 10.1002/pmic.200800593
Subject(s) - proteome , omim : online mendelian inheritance in man , metadata , proteomics , identification (biology) , computational biology , biomarker , annotation , biomarker discovery , computer science , function (biology) , bioinformatics , database , biology , gene , world wide web , genetics , botany , phenotype
We have developed a proteome database (DB), BiomarkerDigger (http://biomarkerdigger.org) that automates data analysis, searching, and metadata-gathering function. The metadata-gathering function searches proteome DBs for protein-protein interaction, Gene Ontology, protein domain, Online Mendelian Inheritance in Man, and tissue expression profile information and integrates it into protein data sets that are accessed through a search function in BiomarkerDigger. This DB also facilitates cross-proteome comparisons by classifying proteins based on their annotation. BiomarkerDigger highlights relationships between a given protein in a proteomic data set and any known biomarkers or biomarker candidates. The newly developed BiomarkerDigger system is useful for multi-level synthesis, comparison, and analyses of data sets obtained from currently available web sources. We demonstrate the application of this resource to the identification of a serological biomarker for hepatocellular carcinoma by comparison of plasma and tissue proteomic data sets from healthy volunteers and cancer patients.