Identification of important genes associated with total cholesterol using bioinformatics analysis.

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Identification of important genes associated with total cholesterol using bioinformatics analysis.

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2016 nî lūn-bûn

@nan

2016年の論文

@ja

2016年論文

@yue

2016年論文

@zh-hant

2016年論文

@zh-hk

2016年論文

@zh-mo

2016年論文

@zh-tw

2016年论文

@wuu

2016年论文

@zh

2016年论文

@zh-cn

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Identification of important ge ...... using bioinformatics analysis.

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Identification of important ge ...... using bioinformatics analysis.

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Identification of important ge ...... using bioinformatics analysis.

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P1476

Identification of important ge ...... using bioinformatics analysis.

@en

P2093

Huan Zhang

http://www.w3.org/2001/XMLSchema#string

Shu-Feng Lei

http://www.w3.org/2001/XMLSchema#string

Tan Xu

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Yong-Hong Zhang

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P2860

Common inherited variation in mitochondrial genes is not enriched for associations with type 2 diabetes or related glycemic traits

Biological, clinical and population relevance of 95 loci for blood lipids

Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources

Bioinformatics enrichment tools: paths toward the comprehensive functional analysis of large gene lists

Identifying leukocyte gene expression patterns associated with plasma lipid levels in human subjects

Genetic variants underlying risk of endometriosis: insights from meta-analysis of eight genome-wide association and replication datasets

Discovery and refinement of loci associated with lipid levels.

GATES: a rapid and powerful gene-based association test using extended Simes procedure

STRING v9.1: protein-protein interaction networks, with increased coverage and integration

A modified Bonferroni method for discrete data.

P304

219-230

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P31

scholarly article

P356

10.2217/PGS.15.164

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P433

http://www.w3.org/2001/XMLSchema#string

P478

http://www.w3.org/2001/XMLSchema#string

P50

Xing-bo Mo

P577

2016-01-25T00:00:00Z

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P698

26807482

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P921

bioinformatics