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Investigation of the Mechanism of Complement System in Diabetic Nephropathy via Bioinformatics Analysis.

Bojun Xu | Lei Wang | Huakui Zhan | Liangbin Zhao | Yuehan Wang | Meng Shen | Keyang Xu | Li Li | Xu Luo | Shasha Zhou | Anqi Tang | Gang Liu | Lu Song | Yan Li
Journal of diabetes research | 2021

Diabetic nephropathy (DN) is a major cause of end-stage renal disease (ESRD) throughout the world, and the identification of novel biomarkers via bioinformatics analysis could provide research foundation for future experimental verification and large-group cohort in DN models and patients.

Pubmed ID: 34124269

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


KEGG (tool)

RRID:SCR_012773

Integrated database resource consisting of 16 main databases, broadly categorized into systems information, genomic information, and chemical information. In particular, gene catalogs in completely sequenced genomes are linked to higher-level systemic functions of cell, organism, and ecosystem. Analysis tools are also available. KEGG may be used as reference knowledge base for biological interpretation of large-scale datasets generated by sequencing and other high-throughput experimental technologies.

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STRING (tool)

RRID:SCR_005223

Database of known and predicted protein interactions. The interactions include direct (physical) and indirect (functional) associations and are derived from four sources: Genomic Context, High-throughput experiments, (Conserved) Coexpression, and previous knowledge. STRING quantitatively integrates interaction data from these sources for a large number of organisms, and transfers information between these organisms where applicable. The database currently covers 5''214''234 proteins from 1133 organisms. (2013)

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clusterProfiler (tool)

RRID:SCR_016884

Software R package for statistical analysis and visualization of functional profiles for genes and gene clusters.

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