DbDEPC 3.0: the database of differentially expressed proteins in human cancer with multi-level annotation and drug indication. (22nd February 2018)

• Record Type: Journal Article
• Authors: Yang, Qingmin; Zhang, Yuqi; Cui, Hui; Chen, Lanming; Zhao, Yong; Lin, Yong; Zhang, Menghuan; Xie, Lu
• Is Part Of: Database. Volume 2018(2018)
• Publication Date: 2018-02-22
• Subjects: Biology -- Databases -- Periodicals; Bioinformatics -- Periodicals; 570.285
• DOI: 10.1093/database/bay015
• Languages: English
• ISSNs: 1758-0463

Abstract

Abstract: Proteins are major effectors of biological functions, and differentially expressed proteins (DEPs) are widely reported as biomarkers in pathological mechanism, prognosis prediction as well as treatment targeting in cancer research. High-throughput technology of mass spectrometry (MS) has identified large amounts of DEPs in human cancers. Through mining published researches with detailed experiment information, dbDEPC was the first database aimed to provide a systematic resource for the storage and query of the DEPs generated by MS in cancer research. It was updated to dbDEPC 2.0 in 2012. Here, we provide another updated version of dbDEPC, with improvement of database contents and enhanced web interface. The current version of dbDEPC 3.0 contains 11 669 unique DEPs in 26 different cancer types. Multi-level annotations of DEPs have been firstly introduced this time, including cancer-related peptide amino acid variations, post-translational modifications and drug information. Moreover, these multi-level annotations can be displayed in the biological networks, which can benefit integrative analysis. Finally, an online enrichment analysis tool has been developed, to support a KEGG enrichment analysis and to browse the relationship among interested protein list and known DEPs in KEGG pathways. In summary, dbDEPC 3.0 provides a comprehensive resource for accessing integrated and highly annotated DEPs in human cancer. Database URL : https://www.scbit.org/dbdepc3/index.php