A new approach to the assessment of the quality of predictions of transcription factor binding sites.
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.
Nowakowski
Szymon
S
Institute of Informatics, Warsaw University, ul. Banacha 2, 02-097 Warszawa, Poland. s.nowakowski@mimuw.edu.pl <s.nowakowski@mimuw.edu.pl>
Tiuryn
Jerzy
J
D000465:Algorithms; D001483:Base Sequence; D001665:Binding Sites; D008969:Molecular Sequence Data; D011485:Protein Binding; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D016415:Sequence Alignment / Q000379:methods*; D017422:Sequence Analysis, DNA / Q000379:methods*; D014157:Transcription Factors / Q000737:chemistry* / Q000235:genetics*
D014157:Transcription Factors