計算生物學-建模與預測
Computaional Biology:Modeling and Prediction
| 節 | 週三 |
|---|---|
5 13:20–14:10 | 計算生物學-建模與預測 BI303 3 節連堂 |
6 14:20–15:10 | |
7 15:30–16:20 |
* 根據陽明交大上課時間表所列
The course introduces the basic concepts and methods of mathematic modeling, computational prediction and analysis, as well as their biomedical applications. Some case studies of biomedical applications are used to illustrate the modeling and prediction technologies. Students can learn and understand the course through step by step homework and a term project.
Machine Learning Programming
Teaching assistants will assist in providing programming tools and facilitating assignment discussions.
Attendance and participation (10%) Homework (40%) Midterm exam (15%) Term project (35%)
- Introduction to mathematical modeling, computational technology, and applications
- ○ Computational Methods and Optimization algorithm ○ Modeling Types: Classification, Regression, Survival Analysis ○ Data Types: Data, Signals, Images
- Applications of Bioinformatics and Medicine
| 週次 | 主題 |
|---|---|
| 第 1 週 | Machine learning concepts |
| 第 2 週 | Programming and tools Databases |
| 第 3 週 | Application examples |
| 第 4 週 | Genetic Algorithm and optimization AI modeling |
| 第 5 週 | Intelligent Genetic Algorithm Orthogonal Simulated Annealing |
| 第 6 週 | Orthogonal Particle Swarm Optimization Evolutionary Fuzzy Classifiers |
| 第 7 週 | Evolutionary Fuzzy Neural Network Evolutionary Support Vector Machine |
| 第 8 週 | Midterm exam |
| 第 9 週 | Evolutionary Hidden Markov Model Evolutionary Cox-regression Model |
| 第 10 週 | Microarray and RNA-seq Analysis |
| 第 11 週 | Signature identification |
| 第 12 週 | Protein-DNA binding prediction |
| 第 13 週 | AI-assisted prediction system (1) |
| 第 14 週 | AI-assisted prediction system (2) |
| 第 15 週 | Oral presentation of term project |
| 第 16 週 | Oral presentation of term project |
1. Machine Learning, Tom M. Mitchell, ISBN:0-07-115467-1 2. Introduction to Evolutionary Computing, A.E. Eiben and J.E. Smith, ISBN:3-540-40184-9 3. Pattern Classification, Richard O. Duda, Peter E. Hart and David G. Stork, ISBN:0-471-05669-3 4. Related papers
- 地點
- 賢齊館 412室
- 時間
- Wensday 10:00-12:00
- 聯絡方式
- syho@nycu.edu.tw