Protein Crystallization Prediction with a Combined Feature Set
學年 97
學期 1
發表日期 2008-12-16
作品名稱 Protein Crystallization Prediction with a Combined Feature Set
作品名稱（其他語言）
著者 Hsu, Hui-huang; Wang, Shiang-ming
作品所屬單位 淡江大學資訊工程學系
出版者 IEEE Communication Society
會議名稱 Proceedings of the 5th International Conference on Innovations in Information Technology (Innovations 2008)
會議地點 Al Ain, United Arab Emirates
摘要 Using X-ray crystallography to determine the 3D structure of a protein is a costly and time-consuming process. One of the major reasons is that the protein needs to be purified and crystallized first, and the failure rate of protein crystallization is quite high. Thus it is desired to use a computational method to predict protein crystallizability based on the primary structure information before the whole process starts. This can dramatically lower the average cost for protein structure determination. In this paper, we investigated the feature sets used in previous research. The support vector machine (SVM) was chosen as the predictor. Different weightings are set for the penalty parameters of the two classes to deal with the imbalanced data problem. As a result, a combined set of features is able to produce better results, especially on the specificity.
關鍵字
語言 en
收錄於
會議性質 國際
校內研討會地點
研討會時間 20081216~20081218
通訊作者
國別 ARE
公開徵稿
出版型式
出處 Proceedings of the 5th International Conference on Innovations in Information Technology (Innovations 2008), pp.702-706
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