Bioinformatics analysis and its applications in kidney disease studies

doi:10.3877/cma.j.issn.2095-3216.2017.01.004

Abstract

Abstract:

Under the recent development of high-throughput omics technologies, data of different omics can be accumulated to an enormous number easily. The rapid development of bioinformatics technology helps us to interpret such a large amount of data, and to understand the underlying molecular mechanisms at baseline and in disease conditions. High-throughput omics technologies and bioinformatics analysis have been widely used in the study of kidney diseases, helping us to better understand the genetic basis and biological process behind kidney diseases. Under the aid of the rapid development of omics technology and analysis methods, multi-omics will be widely used to provide more information on biological and pathological processes of kidney diseases, further giving guidance on the early diagnosis and treatment decisions in kidney diseases. In this review, the authors mainly discussed the development of high-throughput omics technology and bioinformatics analysis with examples of kidney disease research.

Key words: Bioinformatics analysis, Genomics, Transcriptomics, Metabolomics, Kidney diseases

Yubao Chen, Pengcheng Yan. Bioinformatics analysis and its applications in kidney disease studies[J]. Chinese Journal of Kidney Disease Investigation(Electronic Edition), 2017, 06(01): 14-19.

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References 39

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数据库名称和地址	数据库内容
National Human Genome Research Institute, Office of Population Genomics(http：//www.genome.gov/gwastudies/)	GWAS研究的公共数据库，其中包含肾脏病的相关结果。
Nephromine(http：//www.nephromine.org)	肾脏病基因表达数据挖掘的数据平台
GEO(Gene Expression Omnibus)(http：//www.ncbi.nlm.nih.gov/geo)	综合性基因表达数据库，收录多种表达数据
ArrayExpress Archive and Gene Expression Atlas(http：//www.ebi.ac.uk/arrayexpress)	不同生物条件下的表达数据
Human Kidney and Urine Proteome Project(http：//www.hkupp.org)	正常人体肾脏的蛋白质组数据库
Human glomerular SAGE transcriptome database(http：//cgap.nci.nih.gov/SAGE)	专门收录了肾小球相关的表达数据
HPRD(http：//www.hprd.org/)	关于蛋白结构域，翻译后修饰，相互作用和疾病信息的人类蛋白质数据库
Pathway Interaction Database(http：//pid.nci.nih.gov/)	分子互作信息和细胞信号通路信息

数据库名称和地址	数据库内容
National Human Genome Research Institute, Office of Population Genomics(http：//www.genome.gov/gwastudies/)	GWAS研究的公共数据库，其中包含肾脏病的相关结果。
Nephromine(http：//www.nephromine.org)	肾脏病基因表达数据挖掘的数据平台
GEO(Gene Expression Omnibus)(http：//www.ncbi.nlm.nih.gov/geo)	综合性基因表达数据库，收录多种表达数据
ArrayExpress Archive and Gene Expression Atlas(http：//www.ebi.ac.uk/arrayexpress)	不同生物条件下的表达数据
Human Kidney and Urine Proteome Project(http：//www.hkupp.org)	正常人体肾脏的蛋白质组数据库
Human glomerular SAGE transcriptome database(http：//cgap.nci.nih.gov/SAGE)	专门收录了肾小球相关的表达数据
HPRD(http：//www.hprd.org/)	关于蛋白结构域，翻译后修饰，相互作用和疾病信息的人类蛋白质数据库
Pathway Interaction Database(http：//pid.nci.nih.gov/)	分子互作信息和细胞信号通路信息

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