Inherent limitations of probabilistic models for protein-DNA binding specificity

被引:13
|
作者
Ruan, Shuxiang
Stormo, Gary D. [1 ]
机构
[1] Washington Univ, Sch Med, Dept Genet, St Louis, MO 63110 USA
基金
美国国家卫生研究院;
关键词
TRANSCRIPTION-FACTOR-BINDING; QUANTITATIVE SPECIFICITY; BIOPHYSICAL APPROACH; INFORMATION-CONTENT; COMPUTER METHODS; SEQUENCE; SITES; SELEX; SEQ; IDENTIFICATION;
D O I
10.1371/journal.pcbi.1005638
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
The specificities of transcription factors are most commonly represented with probabilistic models. These models provide a probability for each base occurring at each position within the binding site and the positions are assumed to contribute independently. The model is simple and intuitive and is the basis for many motif discovery algorithms. However, the model also has inherent limitations that prevent it from accurately representing true binding probabilities, especially for the highest affinity sites under conditions of high protein concentration. The limitations are not due to the assumption of independence between positions but rather are caused by the non-linear relationship between binding affinity and binding probability and the fact that independent normalization at each position skews the site probabilities. Generally probabilistic models are reasonably good approximations, but new high-throughput methods allow for biophysical models with increased accuracy that should be used whenever possible.
引用
收藏
页数:15
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