Discovering motifs with transcription factor domain knowledge. Export

@article{citeulike:1901986, abstract = {We introduce a new motif-discovery algorithm, DIMDom, which exploits two additional kinds of information not commonly exploited: (a) the characteristic pattern of binding site classes, where class is determined based on biological information about transcription factor domains and (b) posterior probabilities of these classes. We compared the performance of DIMDom with MEME on all the transcription factors of Drosophila with at least one known binding site in the TRANSFAC database and found that DOMDom outperformed MEME with 2.5 times the number of successes and 1.5 times in the accuracy in finding binding sties and motifs.}, address = {Department of Computer Science, University of Hong Kong, Pokfulam, Hong Kong, China.}, author = {Leung, H. C. and Chin, F. Y. and Chan, B. M.}, citeulike-article-id = {1901986}, citeulike-linkout-0 = {http://view.ncbi.nlm.nih.gov/pubmed/17990511}, citeulike-linkout-1 = {http://www.hubmed.org/display.cgi?uids=17990511}, issn = {1793-5091}, journal = {Pac Symp Biocomput}, keywords = {motif-discovery, tfbs, tool}, pages = {472--483}, posted-at = {2007-11-12 08:50:57}, priority = {4}, title = {Discovering motifs with transcription factor domain knowledge.}, url = {http://view.ncbi.nlm.nih.gov/pubmed/17990511}, year = {2007} }

TY - JOUR ID - citeulike:1901986 L3 - citeulike-article-id:1901986 N2 - We introduce a new motif-discovery algorithm, DIMDom, which exploits two additional kinds of information not commonly exploited: (a) the characteristic pattern of binding site classes, where class is determined based on biological information about transcription factor domains and (b) posterior probabilities of these classes. We compared the performance of DIMDom with MEME on all the transcription factors of Drosophila with at least one known binding site in the TRANSFAC database and found that DOMDom outperformed MEME with 2.5 times the number of successes and 1.5 times in the accuracy in finding binding sties and motifs. JF - Pac Symp Biocomput SN - 1793-5091 AD - Department of Computer Science, University of Hong Kong, Pokfulam, Hong Kong, China. EP - 483 TI - Discovering motifs with transcription factor domain knowledge. SP - 472 KW - motif-discovery KW - tfbs KW - tool AU - Leung, HC AU - Chin, FY AU - Chan, BM PY - 2007/// UR - http://view.ncbi.nlm.nih.gov/pubmed/17990511 ER -