一种用于定位和分析核酸中蛋白质结合序列基序的通用程序。
A general procedure for locating and analyzing protein-binding sequence motifs in nucleic acids.
作者信息
O'Neill M C
机构信息
Department of Biological Sciences, University of Maryland, Baltimore County, 1000 Hilltop Circle, Baltimore, MD 21250, USA.
出版信息
Proc Natl Acad Sci U S A. 1998 Sep 1;95(18):10710-5. doi: 10.1073/pnas.95.18.10710.
Abstract
In the last decade, two tools, one drawn from information theory and the other from artificial neural networks, have proven particularly useful in many different areas of sequence analysis. The work presented herein indicates that these two approaches can be joined in a general fashion to produce a very powerful search engine that is capable of locating members of a given nucleic acid sequence family in either local or global sequence searches. This program can, in turn, be queried for its definition of the motif under investigation, ranking each base in context for its contribution to membership in the motif family. In principle, the method used can be applied to any binding motif, including both DNA and RNA sequence families, given sufficient family size.
摘要
在过去十年中，有两种工具，一种源自信息论，另一种源自人工神经网络，已在序列分析的许多不同领域证明特别有用。本文所展示的工作表明，这两种方法可以以一种通用方式结合起来，生成一个非常强大的搜索引擎，该引擎能够在局部或全局序列搜索中定位给定核酸序列家族的成员。反过来，可以查询该程序对所研究基序的定义，根据每个碱基在上下文中对基序家族成员资格的贡献进行排名。原则上，只要有足够的家族规模，所使用的方法可应用于任何结合基序，包括DNA和RNA序列家族。
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