A hypothesis-based approach for identifying the binding specificity of regulatory proteins from chromatin immunoprecipitation data. Export

@article{citeulike:502986, abstract = {MOTIVATION: Genome-wide chromatin-immunoprecipitation (ChIP-chip) detects binding of transcriptional regulators to DNA in vivo at low resolution. Motif discovery algorithms can be used to discover sequence patterns in the bound regions that may be recognized by the immunoprecipitated protein. However, the discovered motifs often do not agree with the binding specificity of the protein, when it is known. RESULTS: We present a powerful approach to analyzing ChIP-chip data, called THEME, that tests hypotheses concerning the sequence specificity of a protein. Hypotheses are refined using constrained local optimization. Cross-validation provides a principled standard for selecting the optimal weighting of the hypothesis and the ChIP-chip data and for choosing the best refined hypothesis. We demonstrate how to derive hypotheses for proteins from 36 domain families. Using THEME together with these hypotheses, we analyze ChIP-chip datasets for 14 human and mouse proteins. In all the cases the identified motifs are consistent with the published data with regard to the binding specificity of the proteins.}, author = {Macisaac, Kenzie D. and Gordon, D. Benjamin and Nekludova, Lena and Odom, Duncan T. and Schreiber, Joerg and Gifford, David K. and Young, Richard A. and Fraenkel, Ernest}, citeulike-article-id = {502986}, citeulike-linkout-0 = {http://dx.doi.org/10.1093/bioinformatics/bti815}, citeulike-linkout-1 = {http://bioinformatics.oxfordjournals.org/cgi/content/abstract/22/4/423}, citeulike-linkout-2 = {http://www.ingentaconnect.com/content/oup/cabios/2006/00000022/00000004/art00423}, citeulike-linkout-3 = {http://view.ncbi.nlm.nih.gov/pubmed/16332710}, citeulike-linkout-4 = {http://www.hubmed.org/display.cgi?uids=16332710}, day = {15}, doi = {10.1093/bioinformatics/bti815}, issn = {1367-4803}, journal = {Bioinformatics (Oxford, England)}, keywords = {transcription\_factors}, month = {February}, number = {4}, pages = {423--429}, posted-at = {2009-10-30 13:17:51}, priority = {2}, publisher = {Oxford University Press}, title = {A hypothesis-based approach for identifying the binding specificity of regulatory proteins from chromatin immunoprecipitation data.}, url = {http://dx.doi.org/10.1093/bioinformatics/bti815}, volume = {22}, year = {2006} }

TY - JOUR ID - citeulike:502986 L3 - citeulike-article-id:502986 N2 - MOTIVATION: Genome-wide chromatin-immunoprecipitation (ChIP-chip) detects binding of transcriptional regulators to DNA in vivo at low resolution. Motif discovery algorithms can be used to discover sequence patterns in the bound regions that may be recognized by the immunoprecipitated protein. However, the discovered motifs often do not agree with the binding specificity of the protein, when it is known. RESULTS: We present a powerful approach to analyzing ChIP-chip data, called THEME, that tests hypotheses concerning the sequence specificity of a protein. Hypotheses are refined using constrained local optimization. Cross-validation provides a principled standard for selecting the optimal weighting of the hypothesis and the ChIP-chip data and for choosing the best refined hypothesis. We demonstrate how to derive hypotheses for proteins from 36 domain families. Using THEME together with these hypotheses, we analyze ChIP-chip datasets for 14 human and mouse proteins. In all the cases the identified motifs are consistent with the published data with regard to the binding specificity of the proteins. IS - 4 JF - Bioinformatics (Oxford, England) SN - 1367-4803 EP - 429 TI - A hypothesis-based approach for identifying the binding specificity of regulatory proteins from chromatin immunoprecipitation data. PB - Oxford University Press VL - 22 SP - 423 KW - transcription_factors AU - Macisaac, Kenzie AU - Gordon, Benjamin AU - Nekludova, Lena AU - Odom, Duncan AU - Schreiber, Joerg AU - Gifford, David AU - Young, Richard AU - Fraenkel, Ernest PY - 2006/02/15/ UR - http://dx.doi.org/10.1093/bioinformatics/bti815 ER -