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Application of a simple likelihood ratio approximant to protein sequence classification

机译:简单似然比在蛋白质序列分类中的应用

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摘要

Motivation: Likelihood ratio approximants (LRA) have been widely used for model comparison in statistics. The present study was undertaken in order to explore their utility as a scoring (ranking) function in the classification of protein sequences. Results: We used a simple LRA-based on the maximal similarity (or minimal distance) scores of the two top ranking sequence classes. The scoring methods (Smith-Waterman, BLAST, local alignment kernel and compression based distances) were compared on datasets designed to test sequence similarities between proteins distantly related in terms of structure or evolution. It was found that LRA-based scoring can significantly outperform simple scoring methods.
机译:动机:似然比近似值(LRA)已被广泛用于统计中的模型比较。进行本研究是为了探索它们在蛋白质序列分类中作为评分(排序)功能的效用。结果:我们基于两个排名最高的序列类的最大相似度(或最小距离)得分使用了简单的LRA。在设计用于测试在结构或进化上密切相关的蛋白质之间的序列相似性的数据集上,比较了评分方法(Smith-Waterman,BLAST,局部比对核和基于压缩的距离)。发现基于LRA的评分可以明显优于简单的评分方法。

著录项

  • 来源
    《Bioinformatics》 |2006年第23期|p. 2865-2869|共5页
  • 作者单位

    Int Ctr Genet Engn & Biotechnol, Bioinformat Grp, I-34012 Trieste, Italy;

    Hungarian Acad Sci, Res Grp Artificial Intelligence, H-6720 Szeged, Hungary;

    Univ Szeged, H-6720 Szeged, Hungary;

    Hungarian Acad Sci, Biol Res Ctr, Bioinformat Grp, H-6701 Szeged, Hungary;

  • 收录信息 美国《科学引文索引》(SCI);美国《化学文摘》(CA);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 生物科学;
  • 关键词

    DATABASE;

    机译:数据库;
  • 入库时间 2022-08-17 23:49:54

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