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HHsenser:使用隐马尔可夫模型-隐马尔可夫模型比较进行详尽的传递性轮廓搜索。

HHsenser: exhaustive transitive profile search using HMM-HMM comparison.

作者信息

Söding Johannes, Remmert Michael, Biegert Andreas, Lupas Andrei N

机构信息

Department of Protein Evolution, Max-Planck-Institute for Developmental Biology, Spemannstrasse 35, 72076 Tübingen, Germany.

出版信息

Nucleic Acids Res. 2006 Jul 1;34(Web Server issue):W374-8. doi: 10.1093/nar/gkl195.

Abstract

HHsenser is the first server to offer exhaustive intermediate profile searches, which it combines with pairwise comparison of hidden Markov models. Starting from a single protein sequence or a multiple alignment, it can iteratively explore whole superfamilies, producing few or no false positives. The output is a multiple alignment of all detected homologs. HHsenser's sensitivity should make it a useful tool for evolutionary studies. It may also aid applications that rely on diverse multiple sequence alignments as input, such as homology-based structure and function prediction, or the determination of functional residues by conservation scoring and functional subtyping.HHsenser can be accessed at http://hhsenser.tuebingen.mpg.de/. It has also been integrated into our structure and function prediction server HHpred (http://hhpred.tuebingen.mpg.de/) to improve predictions for near-singleton sequences.

摘要

HHsenser是首个提供详尽中间轮廓搜索的服务器,它将此与隐马尔可夫模型的成对比较相结合。从单个蛋白质序列或多序列比对开始,它可以迭代地探索整个超家族,产生极少的假阳性或不产生假阳性。输出结果是所有检测到的同源物的多序列比对。HHsenser的灵敏度使其成为进化研究的有用工具。它还可能有助于依赖多样的多序列比对作为输入的应用,例如基于同源性的结构和功能预测,或通过保守性评分和功能亚型确定功能残基。可通过http://hhsenser.tuebingen.mpg.de/访问HHsenser。它也已集成到我们的结构和功能预测服务器HHpred(http://hhpred.tuebingen.mpg.de/)中,以改进对近单拷贝序列的预测。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ccda/1538784/4fe9ef495e61/gkl195f1.jpg

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