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Genome Biology

, 7:R102

First Online: 01 November 2006Received: 20 June 2006Revised: 29 August 2006Accepted: 01 November 2006

Abstract

Comprehensive mapping of transcription factor binding sites is essential in postgenomic biology. For this, we propose a mining approach combining noisy data from ChIP chromatin immunoprecipitation-chip experiments with known binding site patterns. Our method BoCaTFBS uses boosted cascades of classifiers for optimum efficiency, in which components are alternating decision trees; it exploits interpositional correlations; and it explicitly integrates massive negative information from ChIP-chip experiments. We applied BoCaTFBS within the ENCODE project and showed that it outperforms many traditional binding site identification methods for instance, profiles.

Electronic supplementary materialThe online version of this article doi:10.1186-gb-2006-7-11-r102 contains supplementary material, which is available to authorized users.

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Autor: Lu-yong Wang - Michael Snyder - Mark Gerstein

Fuente: https://link.springer.com/



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