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PeptiCKDdb—peptide- and protein-centric database for the investigation of genesis and progression of chronic kidney disease
Author(s) -
Magdalena Krochmal,
Marco Fernandes,
Szymon K. Filip,
Claudia Pontillo,
Holger Husi,
Jérôme Zoidakis,
Harald Mischak,
Antonia Vlahou,
Joachim Jankowski
Publication year - 2016
Publication title -
database
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.406
H-Index - 62
ISSN - 1758-0463
DOI - 10.1093/database/baw128
Subject(s) - proteomics , profiling (computer programming) , computer science , proteome , identification (biology) , kidney disease , bioinformatics , computational biology , database , medicine , biology , biochemistry , botany , gene , operating system
The peptiCKDdb is a publicly available database platform dedicated to support research in the field of chronic kidney disease (CKD) through identification of novel biomarkers and molecular features of this complex pathology. PeptiCKDdb collects peptidomics and proteomics datasets manually extracted from published studies related to CKD. Datasets from peptidomics or proteomics, human case/control studies on CKD and kidney or urine profiling were included. Data from 114 publications (studies of body fluids and kidney tissue: 26 peptidomics and 76 proteomics manuscripts on human CKD, and 12 focusing on healthy proteome profiling) are currently deposited and the content is quarterly updated. Extracted datasets include information about the experimental setup, clinical study design, discovery-validation sample sizes and list of differentially expressed proteins (P-value < 0.05). A dedicated interactive web interface, equipped with multiparametric search engine, data export and visualization tools, enables easy browsing of the data and comprehensive analysis. In conclusion, this repository might serve as a source of data for integrative analysis or a knowledgebase for scientists seeking confirmation of their findings and as such, is expected to facilitate the modeling of molecular mechanisms underlying CKD and identification of biologically relevant biomarkers.Database URL: www.peptickddb.com.

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