Discriminative motif discovery in DNA and protein sequences using the DEME algorithm.
Discriminative motif discovery in DNA and protein sequences using the DEME algorithm.
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DOI：
10.1186/1471-2105-8-385
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发表时间：
2007-10-15
影响因子：
3
通讯作者：
Bailey TL
中科院分区：
文献类型：
--
作者：
Redhead E;Bailey TL
基序发现旨在检测一组未对齐的 DNA 或蛋白质序列中短的、高度保守的模式。判别性基序发现算法旨在通过利用第二组序列并仅搜索可以区分两组序列的模式来提高基序发现的灵敏度和选择性。判别性基序发现的潜在应用包括发现 ChIP 芯片数据中的转录因子结合位点基序，以及使用来自嗜热和嗜温生物体的直系同源蛋白组寻找与热稳定性有关的蛋白质基序。我们描述了 DEME，一种用于蛋白质和 DNA 序列的判别基序发现算法。 DEME 的输入是两组序列；一个“正”集和一个“负”集。 DEME 使用概率模型表示模体，并使用全局和局部搜索的新颖组合来找到最佳区分两组序列的模体。 DEME 在判别性基序查找器中是独一无二的，因为它在蛋白质基序列上使用信息丰富的贝叶斯先验，使其能够纳入残基特征的先验知识。我们还介绍了四个合成的判别性主题发现问题，这些问题旨在评估各种生物动机环境中的判别性主题发现者。我们使用这些合成问题和两个生物学问题来测试 DEME：在 ChIP 芯片数据中寻找酵母转录因子结合基序，以及寻找区分嗜热和嗜温直系同源蛋白组的基序。使用人工数据，我们表明，当存在“诱饵”基序或“负”序列中存在基序变体时，DEME 比非歧视性方法更有效。通过真实数据，我们表明 DEME 在发现酵母转录因子结合基序方面与非歧视性算法一样好，但并不比它们更好。我们还表明 DEME 可以找到信息丰富的热稳定性蛋白质基序。独立程序 DEME 的二进制文件可免费供学术使用，可在以下位置获取：
Motif discovery aims to detect short, highly conserved patterns in a collection of unaligned DNA or protein sequences. Discriminative motif finding algorithms aim to increase the sensitivity and selectivity of motif discovery by utilizing a second set of sequences, and searching only for patterns that can differentiate the two sets of sequences. Potential applications of discriminative motif discovery include discovering transcription factor binding site motifs in ChIP-chip data and finding protein motifs involved in thermal stability using sets of orthologous proteins from thermophilic and mesophilic organisms. We describe DEME, a discriminative motif discovery algorithm for use with protein and DNA sequences. Input to DEME is two sets of sequences; a "positive" set and a "negative" set. DEME represents motifs using a probabilistic model, and uses a novel combination of global and local search to find the motif that optimally discriminates between the two sets of sequences. DEME is unique among discriminative motif finders in that it uses an informative Bayesian prior on protein motif columns, allowing it to incorporate prior knowledge of residue characteristics. We also introduce four, synthetic, discriminative motif discovery problems that are designed for evaluating discriminative motif finders in various biologically motivated contexts. We test DEME using these synthetic problems and on two biological problems: finding yeast transcription factor binding motifs in ChIP-chip data, and finding motifs that discriminate between groups of thermophilic and mesophilic orthologous proteins. Using artificial data, we show that DEME is more effective than a non-discriminative approach when there are "decoy" motifs or when a variant of the motif is present in the "negative" sequences. With real data, we show that DEME is as good, but not better than non-discriminative algorithms at discovering yeast transcription factor binding motifs. We also show that DEME can find highly informative thermal-stability protein motifs. Binaries for the stand-alone program DEME is free for academic use and is available at
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影响因子：
14.9
作者：
Frith, MC;Hansen, U;Weng, ZP
通讯作者：
Weng, ZP
影响因子：
3
作者：
Marks, Hendrik;Ren, Xin-Ying;Sandbrink, Hans;van Hulten, Marielle C. W.;Vlak, Just M.
通讯作者：
Vlak, Just M.
影响因子：
4.8
作者：
Krig, Sheryl R.;Jin, Victor X.;Farnham, Peggy J.
通讯作者：
Farnham, Peggy J.
DOI：
10.1016/j.bbrc.2004.09.212
发表时间：
2004-12-03
影响因子：
3.1
作者：
Akerman, M;Shaked-Mishan, P;Zilberstein, D
通讯作者：
Zilberstein, D
影响因子：
1.7
作者：
Buhler, J;Tompa, M
通讯作者：
Tompa, M