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

An application of machine learning algorithms enables prediction of the functional context of transcription factor binding sites in the human genome

Plot of the distribution of global and local contexts in the 375 sequences (red squares) selected from the 'positive' set of ChIP-chip results reported by Odom

[11] versus all 10,852 sequences from the 'negative' (not binding; H13K_noHNF4) set (green dots) reported for the same experiment. The selected sequences are characterized by the highest global and local context scores whereas the majority of the 'negative' sequences are characterized by low values for these two scores. The vertical and horizontal lines show two thresholds chosen for the global context score (0.28) and the local context score (0.18).<p><b>Copyright information:</b></p><p>Taken from "Genome wide prediction of HNF4α functional binding sites by the use of local and global sequence context"</p><p>http://genomebiology.com/2008/9/2/R36</p><p>Genome Biology 2008;9(2):R36-R36.</p><p>Published online 21 Feb 2008</p><p>PMCID:PMC2374721.</p><p></p