Gene annotation bias impedes biomedical research

被引：95

作者：

Haynes, Winston A. ^{[1
,2
,3
]}

Tomczak, Aurelie ^{[1
,2
]}

Khatri, Purvesh ^{[1
,2
]}

机构：

[1] Stanford Univ, Stanford Inst Immun Transplantat & Infect, Stanford, CA 94305 USA

[2] Stanford Univ, Dept Med, Stanford Ctr Biomed Informat Res, Stanford, CA 94305 USA

[3] Stanford Univ, Biomed Informat Training Program, Stanford, CA 94305 USA

来源：

SCIENTIFIC REPORTS | 2018年 / 8卷

基金：

美国国家科学基金会;

关键词：

EXPRESSION; ONTOLOGY; ASSOCIATIONS; RESOURCE; TOOL;

D O I：

10.1038/s41598-018-19333-x

中图分类号：

O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

We found tremendous inequality across gene and protein annotation resources. We observed that this bias leads biomedical researchers to focus on richly annotated genes instead of those with the strongest molecular data. We advocate that researchers reduce these biases by pursuing data-driven hypotheses.

引用

页数：7

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