Overlap-Based Similarity Metrics for Motif Search in DNA Sequences
ICONIP '09 Proceedings of the 16th International Conference on Neural Information Processing: Part II
Scalable parallel word search in multicore/multiprocessor systems
The Journal of Supercomputing
MISCORE: mismatch-based matrix similarity scores for DNA motif detection
ICONIP'08 Proceedings of the 15th international conference on Advances in neuro-information processing - Volume Part I
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Motivation: Most of the available tools for transcription factor binding site prediction are based on methods which assume no sequence dependence between the binding site base positions. Our primary objective was to investigate the statistical basis for either a claim of dependence or independence, to determine whether such a claim is generally true, and to use the resulting data to develop improved scoring functions for binding-site prediction. Results: Using three statistical tests, we analyzed the number of binding sites showing dependent positions. We analyzed transcription factor–DNA crystal structures for evidence of position dependence. Our final conclusions were that some factors show evidence of dependencies whereas others do not. We observed that the conformational energy (Z-score) of the transcription factor–DNA complexes was lower (better) for sequences that showed dependency than for those that did not (P Availability: http://promoterplot.fmi.ch/cgi-bin/dep.html Contact: edward.oakeley@fmi.ch Supplementary information: Supplementary data (1, 2, 3, 4, 5, 6, 7 and 8) are available at Bioinformatics online.