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Genome wide prediction of HNF4alpha functional binding sites by the use of local and global sequence context.


ABSTRACT: We report an application of machine learning algorithms that enables prediction of the functional context of transcription factor binding sites in the human genome. We demonstrate that our method allowed de novo identification of hepatic nuclear factor (HNF)4alpha binding sites and significantly improved an overall recognition of faithful HNF4alpha targets. When applied to published findings, an unprecedented high number of false positives were identified. The technique can be applied to any transcription factor.

SUBMITTER: Kel AE 

PROVIDER: S-EPMC2374721 | biostudies-literature | 2008

REPOSITORIES: biostudies-literature

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Genome wide prediction of HNF4alpha functional binding sites by the use of local and global sequence context.

Kel Alexander E AE   Niehof Monika M   Matys Volker V   Zemlin Rüdiger R   Borlak Jürgen J  

Genome biology 20080221 2


We report an application of machine learning algorithms that enables prediction of the functional context of transcription factor binding sites in the human genome. We demonstrate that our method allowed de novo identification of hepatic nuclear factor (HNF)4alpha binding sites and significantly improved an overall recognition of faithful HNF4alpha targets. When applied to published findings, an unprecedented high number of false positives were identified. The technique can be applied to any tra  ...[more]

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