Method

Genome wide prediction of HNF4α functional binding sites by the use of local and global sequence context

Alexander E Kel¹ , Monika Niehof² , Volker Matys¹ , Rüdiger Zemlin² and Jürgen Borlak²

¹  BIOBASE GmbH, Halchtersche Str., 38304 Wolfenbüttel, Germany

²  Fraunhofer Institute of Toxicology and Experimental Medicine, Center for Drug Research and Medical Biotechnology, Nikolai-Fuchs-Str., 30625 Hannover, Germany

author email corresponding author email

Genome Biology 2008, 9:R36doi:10.1186/gb-2008-9-2-r36

Published:	21 February 2008

Subject areas: Bioinformatics, Molecular biology, Methods

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)4α binding sites and significantly improved an overall recognition of faithful HNF4α targets. When applied to published findings, an unprecedented high number of false positives were identified. The technique can be applied to any transcription factor.