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PeptiCKDdb-peptide- and protein-centric database for the investigation of genesis and progression of chronic kidney disease.

Database : the journal of biological databases and curation | 2016

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.

Pubmed ID: 27589965 RIS Download

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Publication data is provided by the National Library of Medicine ® and PubMed ®. Data is retrieved from PubMed ® on a weekly schedule. For terms and conditions see the National Library of Medicine Terms and Conditions.

This is a list of tools and resources that we have found mentioned in this publication.


Kidney and Urinary Pathway Knowledge Base (tool)

RRID:SCR_001746

A collection of omics datasets (mRNA, proteins and miRNA) that have been extracted from PubMed and other related renal databases, all related to kidney physiology and pathology giving KUP biologists the means to ask queries across many resources in order to aggregate knowledge that is necessary for answering biological questions. Some microarray raw datasets have also been downloaded from the Gene Expression Omnibus and analyzed by the open-source software GeneArmada. The Semantic Web technologies, together with the background knowledge from the domain's ontologies, allows both rapid conversion and integration of this knowledge base. SPARQL endpoint http://sparql.kupkb.org/sparql The KUPKB Network Explorer will help you visualize the relationships among molecules stored in the KUPKB. A simple spreadsheet template is available for users to submit data to the KUPKB. It aims to capture a minimal amount of information about the experiment and the observations made.

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UniProt (tool)

RRID:SCR_002380

Collection of data of protein sequence and functional information. Resource for protein sequence and annotation data. Consortium for preservation of the UniProt databases: UniProt Knowledgebase (UniProtKB), UniProt Reference Clusters (UniRef), and UniProt Archive (UniParc), UniProt Proteomes. Collaboration between European Bioinformatics Institute (EMBL-EBI), SIB Swiss Institute of Bioinformatics and Protein Information Resource. Swiss-Prot is a curated subset of UniProtKB.

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PubMed (tool)

RRID:SCR_004846

Public bibliographic database that provides access to citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites. PubMed citations and abstracts include fields of biomedicine and health, covering portions of life sciences, behavioral sciences, chemical sciences, and bioengineering. Provides access to additional relevant web sites and links to other NCBI molecular biology resources. Publishers of journals can submit their citations to NCBI and then provide access to full-text of articles at journal web sites using LinkOut.

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