Human-Associated Microbial Signatures: Examining Their Predictive Value

被引：101

作者：

Knights, Dan ^{[2
]}

Parfrey, Laura Wegener ^{[1
]}

Zaneveld, Jesse ^{[3
]}

Lozupone, Catherine ^{[1
]}

Knight, Rob ^{[1
,4
]}

机构：

[1] Univ Colorado, Dept Chem & Biochem, Boulder, CO 80309 USA

[2] Univ Colorado, Dept Comp Sci, Boulder, CO 80309 USA

[3] Univ Colorado, Dept Mol Cellular & Dev Biol, Boulder, CO 80309 USA

[4] Howard Hughes Med Inst, Chevy Chase, MD 20815 USA

来源：

CELL HOST & MICROBE | 2011年 / 10卷 / 04期

关键词：

CLASSIFICATION; BARRIER;

D O I：

10.1016/j.chom.2011.09.003

中图分类号：

Q93 [微生物学];

学科分类号：

071005 ; 100705 ;

摘要：

Host-associated microbial communities are unique to individuals, affect host health, and correlate with disease states. Although advanced technologies capture detailed snapshots of microbial communities, high within- and between-subject variation hampers discovery of microbial signatures in diagnostic or forensic settings. We suggest turning to machine learning and discuss key directions toward harnessing human-associated microbial signatures.

引用

页码：292 / 296

页数：5

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