Pevzner P A, Sze S H
Department of Mathematics, University of Southern California, Los Angeles 90089-1113, USA.
Proc Int Conf Intell Syst Mol Biol. 2000;8:269-78.
Signal finding (pattern discovery in unaligned DNA sequences) is a fundamental problem in both computer science and molecular biology with important applications in locating regulatory sites and drug target identification. Despite many studies, this problem is far from being resolved: most signals in DNA sequences are so complicated that we don't yet have good models or reliable algorithms for their recognition. We complement existing statistical and machine learning approaches to this problem by a combinatorial approach that proved to be successful in identifying very subtle signals.
信号发现(在未比对的DNA序列中发现模式)是计算机科学和分子生物学中的一个基本问题,在定位调控位点和药物靶点识别方面有重要应用。尽管有许多研究,但这个问题远未得到解决:DNA序列中的大多数信号非常复杂,以至于我们还没有用于识别它们的良好模型或可靠算法。我们通过一种组合方法对该问题现有的统计和机器学习方法进行补充,该组合方法在识别非常细微的信号方面已被证明是成功的。