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用于蛋白质的MAVL/StickWRLD:可视化蛋白质序列家族以检测非一致性特征。

MAVL/StickWRLD for protein: visualizing protein sequence families to detect non-consensus features.

作者信息

Ray William C

机构信息

Children's Research Institute and The Department of Pediatrics, The Ohio State University, 700 Children's Drive, Columbus, OH 43205, USA.

出版信息

Nucleic Acids Res. 2005 Jul 1;33(Web Server issue):W315-9. doi: 10.1093/nar/gki374.

Abstract

A fundamental problem with applying Consensus, Weight-Matrix or hidden Markov models as search tools for biosequences is that there is no way to know, from the model, if the modeled sequences display any dependencies between positional identities. In some instances, these dependencies are crucial in correctly accepting or rejecting other sequences as members of the family. MAVL (multiple alignment variation linker) and StickWRLD provide a web-based method to visually survey the model-training sequences to discover and characterize possible dependencies. Initially introduced for nucleic acid sequences, with MAVL/StickWRLD, it is easy to distinguish typical DNA or RNA structural dependencies in input families, identify mixed populations of distinct subfamilies, or discover novel dependencies that result from binding interactions or other selective pressures [W. Ray (2004) Nucleic Acids Res., 32, W59-W63]. Since the announcement of MAVL/StickWRLD for nucleic acids, one of the most requested new features has been the extension of this visualization method to support protein alignments. We are pleased to report that this extension has been successful, that the basic visualization has been augmented in several ways to enhance protein viewing, and that the results with protein alignments are even more dramatic than with NA alignments. MAVL/StickWRLD can be accessed at http://www.microbial-pathogenesis.org/stickwrld/.

摘要

将一致性模型、权重矩阵模型或隐马尔可夫模型用作生物序列搜索工具的一个基本问题是,从模型本身无法得知所建模的序列在位置一致性之间是否存在任何依赖性。在某些情况下,这些依赖性对于正确接受或拒绝其他序列作为该家族的成员至关重要。MAVL(多序列比对变异连接子)和StickWRLD提供了一种基于网络的方法,用于直观地审视模型训练序列,以发现并描述可能存在的依赖性。MAVL/StickWRLD最初是针对核酸序列引入的,利用它很容易区分输入家族中典型的DNA或RNA结构依赖性、识别不同亚家族的混合群体,或者发现由结合相互作用或其他选择压力导致的新依赖性[W. 雷(2004年)《核酸研究》,32卷,W59 - W63页]。自从宣布将MAVL/StickWRLD用于核酸序列以来,最受期待的新功能之一就是将这种可视化方法扩展到支持蛋白质比对。我们很高兴地报告,这个扩展已经成功实现,基本的可视化在几个方面得到了增强以改善蛋白质查看效果,并且蛋白质比对的结果比核酸比对的结果更显著。可通过http://www.microbial-pathogenesis.org/stickwrld/访问MAVL/StickWRLD。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b4ed/1160135/df77e9b212c8/gki374f1.jpg

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