A new approach to the assessment of the quality of predictions of transcription factor binding sites Export

@article{citeulike:2814662, abstract = {In this paper, we describe a novel method called Secondary Verification which assesses the quality of predictions of transcription factor binding sites. This method incorporates a distribution of prediction scores over positive examples (i.e. the actual binding sites) and is shown to be superior to p-value, routinely used statistical significance assessment, which uses only a distribution of prediction scores over background sequences. We also discuss how to integrate both distributions into a framework called Secondary Verification Assessment method which evaluates the quality of a model of a transcription factor. Based on that we create a hybrid representation of a transcription factor: we select the description (with or without dependencies) which is best for the transcription factor considered.}, author = {Nowakowski, Szymon and Tiuryn, Jerzy}, citeulike-article-id = {2814662}, citeulike-linkout-0 = {http://dx.doi.org/10.1016/j.jbi.2006.07.001}, citeulike-linkout-1 = {http://www.sciencedirect.com/science/article/B6WHD-4KFTY07-1/1/1c415f086fa8e242c1411b23eb67e8cc}, doi = {10.1016/j.jbi.2006.07.001}, journal = {Journal of Biomedical Informatics}, keywords = {evaluation}, month = {April}, number = {2}, pages = {139--149}, posted-at = {2008-05-20 03:16:24}, priority = {2}, title = {A new approach to the assessment of the quality of predictions of transcription factor binding sites}, url = {http://dx.doi.org/10.1016/j.jbi.2006.07.001}, volume = {40}, year = {2007} }

TY - JOUR ID - citeulike:2814662 L3 - citeulike-article-id:2814662 N2 - In this paper, we describe a novel method called Secondary Verification which assesses the quality of predictions of transcription factor binding sites. This method incorporates a distribution of prediction scores over positive examples (i.e. the actual binding sites) and is shown to be superior to p-value, routinely used statistical significance assessment, which uses only a distribution of prediction scores over background sequences. We also discuss how to integrate both distributions into a framework called Secondary Verification Assessment method which evaluates the quality of a model of a transcription factor. Based on that we create a hybrid representation of a transcription factor: we select the description (with or without dependencies) which is best for the transcription factor considered. IS - 2 JF - Journal of Biomedical Informatics EP - 149 TI - A new approach to the assessment of the quality of predictions of transcription factor binding sites VL - 40 SP - 139 KW - evaluation AU - Nowakowski, Szymon AU - Tiuryn, Jerzy PY - 2007/04// UR - http://dx.doi.org/10.1016/j.jbi.2006.07.001 ER -