Document Detail


SySAP: a system-level predictor of deleterious single amino acid polymorphisms.
MedLine Citation:
PMID:  22183811     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
Single amino acid polymorphisms (SAPs), also known as non-synonymous single nucleotide polymorphisms (nsSNPs), are responsible for most of human genetic diseases. Discriminate the deleterious SAPs from neutral ones can help identify the disease genes and understand the mechanism of diseases. In this work, a method of deleterious SAP prediction at system level was established. Unlike most existing methods, our method not only considers the sequence and structure information, but also the network information. The integration of network information can improve the performance of deleterious SAP prediction. To make our method available to the public, we developed SySAP (a System-level predictor of deleterious Single Amino acid Polymorphisms), an easy-to-use and high accurate web server. SySAP is freely available at http://www.biosino.org/ SySAP/ and http://lifecenter.sgst.cn/SySAP/.
Authors:
Tao Huang; Chuan Wang; Guoqing Zhang; Lu Xie; Yixue Li
Publication Detail:
Type:  Journal Article; Research Support, Non-U.S. Gov't     Date:  2011-12-19
Journal Detail:
Title:  Protein & cell     Volume:  3     ISSN:  1674-8018     ISO Abbreviation:  Protein Cell     Publication Date:  2012 Jan 
Date Detail:
Created Date:  2012-02-08     Completed Date:  2012-06-15     Revised Date:  2014-03-13    
Medline Journal Info:
Nlm Unique ID:  101532368     Medline TA:  Protein Cell     Country:  Germany    
Other Details:
Languages:  eng     Pagination:  38-43     Citation Subset:  IM    
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MeSH Terms
Descriptor/Qualifier:
Amino Acids / genetics*
Computational Biology / methods*
Conserved Sequence
Databases, Protein
Humans
Internet*
Polymorphism, Single Nucleotide / genetics*
Reproducibility of Results
Software*
Chemical
Reg. No./Substance:
0/Amino Acids

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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