基于分子碎片树方法预测化合物致癌性(英文)
文献类型：会议论文
| 作者 | 王雍; 芦静; 郑明月 ; 沈倩诚; 罗小民; 朱维良; 蒋华良; 陈凯先
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| 出版日期 | 2011-08-05 |
| 关键词 | Carcinogenicity Structural alert Modulating factor Frequent subgraph mining Molecular fragments tree Statistical significance Skin sensitization |
| 页码 | 1 |
| 英文摘要 | Carcinogenicity is an important toxicological endpoint that poses the highest concern for human health.In this study,we develop a method that extracts structural alerts(SAs) and modulating factors of carcinogens based on pure statistical analyses.Firstly,Gaston algorithm,as a frequent subgraph mining method,detects efficiently substructures of any size,shape,and level of chemical details.Then,building and pruning of a molecular fragments tree select SAs with statistical significance in binomial test.Finally,modulating factors that are able to destroy the carcinogenicity potential of SAs are extracted by three self-defining rules.The results highlight that this method is a preferable method with higher accuracy,and the selected SAs are usable for prediction as well as interpretation.Moreover,our method can extract SAs from database using an automated and unbiased manner which has no use of a priori knowledge of mechanism of action, and are conveniently employed by a user. |
| 会议录 | 第十一届全国计算（机）化学学术会议论文摘要集
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| 文献子类 | Article |
| 语种 | 英语 |
| 资助项目 | Hi-TECH Research and Development Program of China[2006AA020402] ; National S&T Major Project[2009ZX09301-001] ; National S&T Major Project[2009ZX09501-001] ; the State Key Program of Basic Research of China[2009CB918502] |
| 源URL | [http://119.78.100.183/handle/2S10ELR8/267258]  |
| 专题 | 药物发现与设计中心 |
| 作者单位 | 中国科学院上海药物研究所,药物发现与设计中心,上海 201203, 中国. |
| 推荐引用方式 GB/T 7714 | 王雍,芦静,郑明月,等. 基于分子碎片树方法预测化合物致癌性(英文)[C]. 见:. |
入库方式： OAI收割
来源：上海药物研究所
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