Finding new structural and sequence attributes to predict possible disease association of single amino acid polymorphism (SAP) | Zendy

Zhiqiang Ye | Zendy; Shuqi Zhao | Zendy; Ge Gao | Zendy; Xiao Liu | Zendy; Robert Langlois | Zendy; Hui Lü | Zendy; Liping Wei | Zendy

Open Access

Finding new structural and sequence attributes to predict possible disease association of single amino acid polymorphism (SAP)

Author(s) -

Zhiqiang Ye,

Shuqi Zhao,

Ge Gao,

Xiao Liu,

Robert Langlois,

Hui Lü,

Liping Wei

Publication year - 2007

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btm119

Subject(s) - web server , classifier (uml) , support vector machine , computational biology , computer science , single nucleotide polymorphism , web site , data mining , genetic association , biology , machine learning , artificial intelligence , bioinformatics , genetics , the internet , genotype , gene , world wide web

The rapid accumulation of single amino acid polymorphisms (SAPs), also known as non-synonymous single nucleotide polymorphisms (nsSNPs), brings the opportunities and needs to understand and predict their disease association. Currently published attributes are limited, the detailed mechanisms governing the disease association of a SAP remain unclear and thus, further investigation of new attributes and improvement of the prediction are desired.

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