图 书 馆
抗癌药物活性的结构输出预测Structured Output Prediction of Anti-Cancer Drug Activity |
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| 课程网址: | http://videolectures.net/prib2010_rousu_sopa/ |
| 主讲教师: | Juho Rousu |
| 开课单位: | 赫尔辛基大学 |
| 开课时间: | 2010-10-14 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | We present a structured output prediction approach for classifying potential anti-cancer drugs. Our QSAR model takes as input a description of a molecule and predicts the activity against a set of cancer cell lines in one shot. Statistical dependencies between the cell lines are encoded by a Markov network that has cell lines as nodes and edges represent similarity according to an auxiliary dataset. Molecules are represented via kernels based on molecular graphs. Margin-based learning is applied to separate correct multilabels from incorrect ones. The performance of the multilabel classification method is shown in our experiments with NCI-Cancer data containing the cancer inhibition potential of drug-like molecules against 59 cancer cell lines. In the experiments, our method outperforms the state-of-the-art SVM method. |
| 关 键 词: | 抗癌药物; 癌细胞系; 马尔可夫网络 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2019-09-14：lxf |
| 阅读次数: | 55 |