| Title | BiomarkerDigger: a versatile disease proteome database and analysis platform for the identification of plasma cancer biomarkers |
| Publication Type | Journal Article |
| Year of Publication | 2009 |
| Authors | Jeong SK, Kwon MS, Lee EY, Lee HJ, Cho SY, Kim H, Yoo JS, Omenn GS, Aebersold R, Hanash S, Paik YK |
| Journal | Proteomics |
| Volume | 9 |
| Pagination | 3729-40 |
| Date Published | Jul |
| PMID | 19639590 |
| Keywords | *Databases, Protein, *Software, Computational Biology/methods, Humans, Models, Theoretical, Neoplasms, Plasma Cell/*metabolism, Proteomics/*methods, Tumor Markers, Biological/*analysis, User-Computer Interface |
| Abstract | 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. |
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