Mutagenic probability estimation of chemical compounds by a novel molecular electrophilicity vector and support vector machine | Zendy

Mingyue Zheng | Zendy; Zhiguo Liu | Zendy; Chunxia Xue | Zendy; Weiliang Zhu | Zendy; Kaixian Chen | Zendy; Xiaomin Luo | Zendy; Hualiang Jiang | Zendy

Open Access

Mutagenic probability estimation of chemical compounds by a novel molecular electrophilicity vector and support vector machine

Author(s) -

Mingyue Zheng,

Zhiguo Liu,

Chunxia Xue,

Weiliang Zhu,

Kaixian Chen,

Xiaomin Luo,

Hualiang Jiang

Publication year - 2006

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/btl352

Subject(s) - electrophile , support vector machine , vector (molecular biology) , computer science , estimation , algorithm , data mining , chemistry , artificial intelligence , organic chemistry , biochemistry , engineering , gene , systems engineering , recombinant dna , catalysis

Mutagenicity is among the toxicological end points that pose the highest concern. The accelerated pace of drug discovery has heightened the need for efficient prediction methods. Currently, most available tools fall short of the desired degree of accuracy, and can only provide a binary classification. It is of significance to develop a discriminative and informative model for the mutagenicity prediction.

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