| Relevance of Course Objectives and Core Learning Outcomes(%) |
Teaching and Assessment Methods for Course Objectives |
| Course Objectives |
Competency Indicators |
Ratio(%) |
Teaching Methods |
Assessment Methods |
1.Sample reparation
2.Protein digestion
3.Data analysis of proteomics
|
|
|
| topic Discussion/Production |
| Discussion |
| Lecturing |
|
| Written Presentation |
| Attendance |
| Quiz |
|
| Course Content and Homework/Schedule/Tests Schedule |
| Week |
Course Content |
| Week 1 |
Introduction of Proteomics |
| Week 2 |
How and why proteomics? |
| Week 3 |
Liquid chromatography/Mass spectrometer
|
| Week 4 |
Discussion/homework
|
| Week 5 |
Data-dependent acquisition (DDA)
|
| Week 6 |
Data-independent acquisition (DIA)
|
| Week 7 |
Proteomic Data analysis
|
| Week 8 |
Review
|
| Week 9 |
Midterm Exam
|
| Week 10 |
Discussion for Midterm Exam
|
| Week 11 |
Quantitative proteomic analysis
|
| Week 12 |
Proteomics Software: Xcalibur
|
| Week 13 |
Software: UniQua and MASCOT search engine
|
| Week 14 |
In-solution digestion workshop
|
| Week 15 |
Experiment
|
| Week 16 |
Final Report |
self-directed
learning |
03.Preparing presentations or reports related to industry and academia.
|
|
| Evaluation |
| Scoring by commentator |
| Textbook & other References |
|
| Teaching Aids & Teacher's Website |
| https://www.yinglanchen.com/ |
| Office Hours |
| Contact via email |
| Sustainable Development Goals, SDGs(Link URL) |
| 01.No Poverty 04.Quality Education | include experience courses：N |
|