Limitations and potentials of current motif discovery algorithms.
Limitations and potentials of current motif discovery algorithms.
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DOI：
10.1093/nar/gki791
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发表时间：
2005
影响因子：
14.9
通讯作者：
Kihara D
中科院分区：
文献类型：
--
作者：
Hu J;Li B;Kihara D
重新鉴定基因调控元件（如转录因子结合位点）的计算方法已被证明对破译遗传调控网络是有用的。然而，尽管有大量的算法可用，但它们的优缺点还没有得到充分的了解。在这里，我们设计了一套全面的性能指标，并使用大肠杆菌RegulonDB生成的大型数据集对五种现代基于序列的motif发现算法进行了基准测试。分析了影响预测精度、可扩展性和可靠性的因素。结果表明，核苷酸和结合位点水平的准确性非常低，而基序水平的准确性相对较高，这表明该算法通常可以捕获输入序列中至少一个正确的基序。为了从一种或多种算法的多次运行中利用不同的预测，开发了一种共识集成算法，通过提高灵敏度和特异性，该算法比基本算法提高了6-45%。我们的研究说明了现有的基于序列的基序发现算法的局限性和潜力。利用所揭示的潜力，讨论了进一步改进的几个有希望的方向。由于基于序列的算法是大多数现代motif发现算法的基础，因此本文建议对它们进行实质性的改进。
Computational methods for de novo identification of gene regulation elements, such as transcription factor binding sites, have proved to be useful for deciphering genetic regulatory networks. However, despite the availability of a large number of algorithms, their strengths and weaknesses are not sufficiently understood. Here, we designed a comprehensive set of performance measures and benchmarked five modern sequence-based motif discovery algorithms using large datasets generated from Escherichia coli RegulonDB. Factors that affect the prediction accuracy, scalability and reliability are characterized. It is revealed that the nucleotide and the binding site level accuracy are very low, while the motif level accuracy is relatively high, which indicates that the algorithms can usually capture at least one correct motif in an input sequence. To exploit diverse predictions from multiple runs of one or more algorithms, a consensus ensemble algorithm has been developed, which achieved 6–45% improvement over the base algorithms by increasing both the sensitivity and specificity. Our study illustrates limitations and potentials of existing sequence-based motif discovery algorithms. Taking advantage of the revealed potentials, several promising directions for further improvements are discussed. Since the sequence-based algorithms are the baseline of most of the modern motif discovery algorithms, this paper suggests substantial improvements would be possible for them.