Applied bioinformatics for the identification of regulatory elements Export

@article{appBio, abstract = {The compilation of multiple metazoan genome sequences and the deluge of large-scale expression data have combined to motivate the maturation of bioinformatics methods for the analysis of sequences that regulate gene transcription. Historically, these bioinformatics methods have been plagued by poor predictive specificity, but new bioinformatics algorithms that accelerate the identification of regulatory regions are drawing disgruntled users back to their keyboards. However, these new approaches and software are not without problems. Here, we introduce the purpose and mechanisms of the leading algorithms, with a particular emphasis on metazoan sequence analysis. We identify key issues that users should take into consideration in interpreting the results and provide an online training example to help researchers who wish to test online tools before taking an independent foray into the bioinformatics of transcription regulation.}, author = {Wasserman, Wyeth W. and Sandelin, Albin}, citeulike-article-id = {455154}, citeulike-linkout-0 = {http://dx.doi.org/10.1038/nrg1315}, citeulike-linkout-1 = {http://dx.doi.org/10.1038/nrg1315}, day = {01}, doi = {10.1038/nrg1315}, issn = {1471-0056}, journal = {Nature Reviews Genetics}, keywords = {regulatory\_elements}, month = {April}, number = {4}, pages = {276--287}, posted-at = {2009-09-23 16:23:37}, priority = {2}, publisher = {Nature Publishing Group}, title = {Applied bioinformatics for the identification of regulatory elements}, url = {http://dx.doi.org/10.1038/nrg1315}, volume = {5}, year = {2004} }

TY - JOUR ID - appBio L3 - citeulike-article-id:455154 N2 - The compilation of multiple metazoan genome sequences and the deluge of large-scale expression data have combined to motivate the maturation of bioinformatics methods for the analysis of sequences that regulate gene transcription. Historically, these bioinformatics methods have been plagued by poor predictive specificity, but new bioinformatics algorithms that accelerate the identification of regulatory regions are drawing disgruntled users back to their keyboards. However, these new approaches and software are not without problems. Here, we introduce the purpose and mechanisms of the leading algorithms, with a particular emphasis on metazoan sequence analysis. We identify key issues that users should take into consideration in interpreting the results and provide an online training example to help researchers who wish to test online tools before taking an independent foray into the bioinformatics of transcription regulation. IS - 4 JF - Nature Reviews Genetics SN - 1471-0056 EP - 287 TI - Applied bioinformatics for the identification of regulatory elements PB - Nature Publishing Group VL - 5 SP - 276 KW - regulatory_elements AU - Wasserman, Wyeth AU - Sandelin, Albin PY - 2004/04/01/ UR - http://dx.doi.org/10.1038/nrg1315 ER -