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

Trey Ideker | Zendy; Janusz Dutkowski | Zendy; Leroy Hood | Zendy

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

Author(s) -

Trey Ideker,

Janusz Dutkowski,

Leroy Hood

Publication year - 2011

Publication title -

cell

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 26.304

H-Index - 776

eISSN - 1097-4172

pISSN - 0092-8674

DOI - 10.1016/j.cell.2011.03.007

Subject(s) - boosting (machine learning) , integrator , signal processing , implementation , noise (video) , computer science , signal (programming language) , biology , artificial intelligence , machine learning , digital signal processing , telecommunications , computer hardware , bandwidth (computing) , image (mathematics) , programming language

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.

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