Boosting Signal-to-Noise in Complex Biology: Prior Knowledge Is Power

被引：124

作者：

Ideker, Trey ^{[1
,2
,3
]}

Dutkowski, Janusz ^{[1
,2
]}

Hood, Leroy ^{[4
]}

机构：

[1] Univ Calif San Diego, Dept Med, San Diego, CA 92093 USA

[2] Univ Calif San Diego, Dept Bioengn, San Diego, CA 92093 USA

[3] Univ Calif San Diego, Inst Genom Med, San Diego, CA 92093 USA

[4] Inst Syst Biol, Seattle, WA 98103 USA

来源：

CELL | 2011年 / 144卷 / 06期

关键词：

REGULATORY NETWORKS; MODELS; YEAST; CELL;

D O I：

10.1016/j.cell.2011.03.007

中图分类号：

Q5 [生物化学]; Q7 [分子生物学];

学科分类号：

071010 ; 081704 ;

摘要：

A major difficulty in the analysis of complex biological systems is dealing with the low signal-to-noise inherent to nearly all large biological datasets. We discuss powerful bioinformatic concepts for boosting signal-to-noise through external knowledge incorporated in processing units we call filters and integrators. These concepts are illustrated in four landmark studies that have provided model implementations of filters, integrators, or both.

引用

页码：860 / 863

页数：4

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