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从结构特征预测DNA结合蛋白

Prediction of DNA-binding proteins from structural features
课程网址: http://videolectures.net/mlsb2010_szaboova_pdna/  
主讲教师: Andrea Szabova
开课单位: 布拉格捷克技术大学
开课时间: 2010-11-08
课程语种: 英语
中文简介:
我们使用基于逻辑的机器学习来区分DNA结合蛋白和非结合蛋白。我们将先前提出的粗粒度特征(如偶极矩)与自动构建的结构(空间)特征相结合。仅基于结构特征的预测已经提高了先前粗粒度特征工作中实现的最先进的预测精度。当使用两个特征类别的组合时,准确度会进一步提高。有助于准确预测的一个重要因素是,结构特征不是布尔特征,而是通过计算其在学习示例中的出现次数来解释。
课程简介: We use logic-based machine learning to distinguish DNAbinding proteins from non-binding proteins. We combine previously suggested coarse-grained features (such as the dipole moment) with automatically constructed structural (spatial) features. Prediction based only on structural features already improves on the state-of-the-art predictive accuracies achieved in previous work with coarse-grained features. Accuracies are further improved when the combination of both feature categories is used. An important factor contributing to accurate prediction is that structural features are not Boolean but rather interpreted by counting the number of their occurences in a learning example.
关 键 词: 机器学习; 粗粒度特征; 自动构建
课程来源: 视频讲座网
数据采集: 2023-07-24:chenjy
最后编审: 2023-07-24:chenjy
阅读次数: 20