A graph-based motif detection algorithm models complex nucleotide dependencies in transcription factor binding sites.
A graph-based motif detection algorithm models complex nucleotide dependencies in transcription factor binding sites.
复制标题
基于图的基序检测算法模拟了转录因子结合位点中复杂的核苷酸依赖性。
DOI：
10.1093/nar/gkl585
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发表时间：
2006
影响因子：
14.9
通讯作者：
Brutlag, Douglas L.
中科院分区：
文献类型：
--
作者：
Naughton, Brian T.;Fratkin, Eugene;Batzoglou, Serafim;Brutlag, Douglas L.
Given a set of known binding sites for a specific transcription factor, it is possible to build a model of the transcription factor binding site, usually called a motif model, and use this model to search for other sites that bind the same transcription factor. Typically, this search is performed using a position-specific scoring matrix (PSSM), also known as a position weight matrix. In this paper we analyze a set of eukaryotic transcription factor binding sites and show that there is extensive clustering of similar k-mers in eukaryotic motifs, owing to both functional and evolutionary constraints. The apparent limitations of probabilistic models in representing complex nucleotide dependencies lead us to a graph-based representation of motifs. When deciding whether a candidate k-mer is part of a motif or not, we base our decision not on how well the k-mer conforms to a model of the motif as a whole, but how similar it is to specific, known k-mers in the motif. We elucidate the reasons why we expect graph-based methods to perform well on motif data. Our MotifScan algorithm shows greatly improved performance over the prevalent PSSM-based method for the detection of eukaryotic motifs.
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DOI：
10.1016/s0097-8485(96)80004-0
发表时间：
1996-03-01
期刊：
COMPUTERS & CHEMISTRY
影响因子：
--
作者：
Gribskov, M;Robinson, NL
通讯作者：
Robinson, NL
影响因子：
3.9
作者：
GOJOBORI, T;LI, WH;GRAUR, D
通讯作者：
GRAUR, D
影响因子：
14.9
作者：
Bulyk, ML;Johnson, PLF;Church, GM
通讯作者：
Church, GM
影响因子：
56.9
作者：
Bertone, P;Stolc, V;Snyder, M
通讯作者：
Snyder, M
影响因子：
5.8
作者：
Stormo, GD
通讯作者：
Stormo, GD