Application of machine learning approaches on quantitative structure activity relationships

著录项

• 来源
  《Computational Intelligence in Bioinformatics and Computational Biology, 2009. CIBCB '09》|2009年|255-262|共8页
• 会议地点 Nashville TN(US);Nashville TN(US)
• 作者

  Butkiewicz M.; Mueller R.; Selic D.; Dawson E.; Meiler J.;

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• 作者单位

  Center for Struct. Biol., Vanderbilt Univ., Nashville, TN;

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• 会议组织
• 原文格式 PDF
• 正文语种
• 中图分类
• 关键词

  decision trees; drugs; learning (artificial intelligence); medical computing; neural nets; support vector machines; ANN; SVM; area under the curve; artificial neural networks; biological activity; chemical structure; machine learning; metabotropic glutamate receptor 5; quantitative structure activity relationships; schizophrenia; Artificial Neural Network (ANN); Decision Trees (DT); Support Vector Machine (SVM); area under the curve (AUC); high-throughput screening (HTS); quantitative structure activity relationship;

  机译：决策树;药物;学习（人工智能）;医学计算;神经网络;支持向量机;人工神经网络;支持向量机;曲线下的区域;人工神经网络;生物活性;化学结构;机器学习;代谢型谷氨酸受体5;定量结构活动关系;精神分裂症;人工神经网络（ANN）;决策树（DT）;支持向量机（SVM）;曲线下面积（AUC）;高通量筛选（HTS）;定量结构活动关系;