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dbDEPC 3.0: the database of differentially expressed proteins in human cancer with multi-level annotation and drug indication
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...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5824774/ https://www.ncbi.nlm.nih.gov/pubmed/29688359 http://dx.doi.org/10.1093/database/bay015 |
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author | Yang, Qingmin Zhang, Yuqi Cui, Hui Chen, Lanming Zhao, Yong Lin, Yong Zhang, Menghuan Xie, Lu |
author_facet | Yang, Qingmin Zhang, Yuqi Cui, Hui Chen, Lanming Zhao, Yong Lin, Yong Zhang, Menghuan Xie, Lu |
author_sort | Yang, Qingmin |
collection | PubMed |
description | 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 |
format | Online Article Text |
id | pubmed-5824774 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-58247742018-02-28 dbDEPC 3.0: the database of differentially expressed proteins in human cancer with multi-level annotation and drug indication Yang, Qingmin Zhang, Yuqi Cui, Hui Chen, Lanming Zhao, Yong Lin, Yong Zhang, Menghuan Xie, Lu Database (Oxford) Database Update 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 Oxford University Press 2018-02-22 /pmc/articles/PMC5824774/ /pubmed/29688359 http://dx.doi.org/10.1093/database/bay015 Text en © The Author(s) 2018. Published by Oxford University Press. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Database Update Yang, Qingmin Zhang, Yuqi Cui, Hui Chen, Lanming Zhao, Yong Lin, Yong Zhang, Menghuan Xie, Lu dbDEPC 3.0: the database of differentially expressed proteins in human cancer with multi-level annotation and drug indication |
title | dbDEPC 3.0: the database of differentially expressed proteins in human cancer with multi-level annotation and drug indication |
title_full | dbDEPC 3.0: the database of differentially expressed proteins in human cancer with multi-level annotation and drug indication |
title_fullStr | dbDEPC 3.0: the database of differentially expressed proteins in human cancer with multi-level annotation and drug indication |
title_full_unstemmed | dbDEPC 3.0: the database of differentially expressed proteins in human cancer with multi-level annotation and drug indication |
title_short | dbDEPC 3.0: the database of differentially expressed proteins in human cancer with multi-level annotation and drug indication |
title_sort | dbdepc 3.0: the database of differentially expressed proteins in human cancer with multi-level annotation and drug indication |
topic | Database Update |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5824774/ https://www.ncbi.nlm.nih.gov/pubmed/29688359 http://dx.doi.org/10.1093/database/bay015 |
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