教學目標:
This course discusses design of advanced machine learning algorithms for biomedical applications. It is expected that the students have taken the “bioinformatics algorithm” course and are familiar with calculus and probability.

週次 主 題
1 Introduction
2 The conventional kernel density estimators
3 The relaxed variable kernel density estimator
4 The relaxed variable kernel density estimator
5 Machine learning with the RVKDE
6 Machine learning with the RBF network
7 Machine learning with the SVM
8 Analysis of protein tertiary substructures
9 Advanced clustering algorithms for protein sequence analysis
10 Prediction of polypeptide motifs
11 Prediction of protein structures
12 Advanced algorithms for protein docking
13 The EM algorithm
14 Bayesian network
15 Feature selection
16 Critical issues for modern bioinformatics applications
17 Critical issues for modern bioinformatics applications