生物機器學習

課程概述與目標: This course is devoted to introducing and developing some effective and efficient machine learning methods for solving computational biology problems, such as bioimage informatics, medical Informatics, genomics and transcriptomics. At the same time, novel machine learning methods are presented. This course should help shed some light on exciting fields, and should be especially useful to professionals in Bioinformatics and Machine Learning. The major topics are as follows: Introduction to machine learning Computational Methodologies .k-Nearest neighbor .Decision trees .Artificial neural networks .Support vector machines (SVM) .WEKA - Machine Learning Tool .etc. Roles of machine learning in: .Artificial intelligence .Image processing .Pattern recognition .Simulation and modeling Applications with case study: Life and medical sciences .bioimage informatics .medical Informatics .microarray data analysis .genomics and transcriptomics .AI modeling

計算機概論和程式編寫能力

引導同學搜尋網路學術公布之生物醫學資料庫,應用於課堂教授的機器學習工具進行課程演練,學習應用操作與結果分析,以E3學習平台作為存放執行程式與繳交結果。專題實作可以1-3位同學為一組,須付出心力完成專題,進而獲益良多。

課堂講授、作業操練、專題實作、上台報告與討論 課堂參與和作業35%,期中專題報告30%,期末專題口頭和書面報告35%

1. Haifeng Li, Applications of Machine Learning Techniques to Bioinformatics, VDM Verlag, ISBN 3639054407, 2008. 2. S. Mitra, S. Datta, T. Perkins and G. Michailidis, Introduction to Machine Learning and Bioinformatics, New York: Chapman & Hall/CRC Press, ISBN 978-1584886822, 2008. 3. Analysis of biological data, edited by S. Bandyopadhyay, U. Maulik and J. T. L. Wang, World Scientific, 2007.

地點

賢齊館412室

時間

課程時間下課後或另約時間

聯絡方式

syho@nctu.edu.tw