nsSNPAnalyzer: identifying disease-associated nonsynonymous single nucleotide polymorphisms.

nsSNPAnalyzer: identifying disease-associated nonsynonymous single nucleotide polymorphisms.
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DOI:
10.1093/nar/gki372
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发表时间:
2005-07-01
影响因子:
14.9
通讯作者:
Cui Y
Cui Y
中科院分区:
生物学2区
文献类型:
--
作者:
Bao L;Zhou M;Cui Y

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非同义单核苷酸多态(NsSNPs)广泛存在于基因组中,与遗传性疾病密切相关。为了便于从大量中性的nsSNP中识别与疾病相关的nsSNP,重要的是开发计算工具来预测nsSNP的表型效应(疾病相关与中性)。为此目的开发的基于网络的软件nsSNPAnalyzer从查询nsSNP中提取结构和进化信息,并使用一种名为随机森林的机器学习方法来预测nsSNP的表型效应。NsSNPAnalyzer服务器位于。
Nonsynonymous single nucleotide polymorphisms (nsSNPs) are prevalent in genomes and are closely associated with inherited diseases. To facilitate identifying disease-associated nsSNPs from a large number of neutral nsSNPs, it is important to develop computational tools to predict the nsSNP's phenotypic effect (disease-associated versus neutral). nsSNPAnalyzer, a web-based software developed for this purpose, extracts structural and evolutionary information from a query nsSNP and uses a machine learning method called Random Forest to predict the nsSNP's phenotypic effect. nsSNPAnalyzer server is available at .
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发表时间: 2002-09-01
影响因子: 14.9
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