| Course Name |
(中) 翻轉教室：精準醫學大數據平台玩上手(1329) |
| (Eng.) Flipped classroom: To get the Hang of Big Data Platform of Precision Medicine |
| Offering Dept |
Department of Post-Baccalaureate Medicine |
| Course Type |
Elective |
Credits |
2 |
Teacher |
LIN, HUNG-YU ect. |
| Department |
Department of Post-Baccalaureate Medicine/Undergraduate |
Language |
English |
Semester |
2025-FALL |
| Course Description |
This course centers on precision medicine research and is built upon the comprehensive required curriculum of the post-baccalaureate medical program. It aims to train students to apply big-data analytical techniques to precision oncology research and to translate basic medical knowledge into clinically translatable cancer research outcomes, with emphasis on research design, clinical interpretation, ethics and regulations, academic writing, and scientific communication.
Integration and application of basic medical sciences: the course deeply integrates required knowledge from anatomy (tumor anatomical structures), physiology (cancer pathophysiological mechanisms), biochemistry (tumor metabolic reprogramming pathways), and immunology (tumor immune microenvironment). Through large-scale analyses of cancer transcriptomics, proteomics, and metabolomics, students will learn to develop multidimensional integrative research models spanning molecular levels to the tumor microenvironment. Combined with pathological principles of tumor grading and staging, the course supports precise molecular subtyping of cancers, prognostic prediction, and assessment of treatment response.
Clinical translational linkage: the course places special emphasis on the ability to translate basic tumor research findings into clinical applications. By integrating pharmacological mechanisms of anticancer drugs with clinical practice knowledge from medical oncology and surgical oncology, students will learn to use database-derived data to evaluate anticancer efficacy and to develop promising personalized cancer treatment strategies. |
| Prerequisites |
|
self-directed learning in the course |
Y |
| Relevance of Course Objectives and Core Learning Outcomes(%) |
Teaching and Assessment Methods for Course Objectives |
| Course Objectives |
Competency Indicators |
Ratio(%) |
Teaching Methods |
Assessment Methods |
| Centered on precision medicine, this course integrates students' knowledge from required subjects—including Anatomy, Physiology, Biochemistry, Immunology, Pathology, Pharmacology, and Internal Medicine & Surgery—into practical skills for precision oncology research design, data analysis, and clinical translation. The objective is to cultivate students who can communicate within multidisciplinary teams, design and execute high-quality oncology research, and ultimately produce publishable academic work. |
| 2.Medical knowledge |
| 4.Practice-based learning and improvement |
| 5.Professionalism |
|
|
| topic Discussion/Production |
| Exercises |
| Discussion |
| Practicum |
| Lecturing |
|
| Written Presentation |
| Attendance |
| Oral Presentation |
| Assignment |
| Study Outcome |
| Internship |
|
| Course Content and Homework/Schedule/Tests Schedule |
| Week |
Course Content |
| Week 1 |
Academic Applications of Precision Medicine Big Data Platforms
|
| Week 2 |
Exploring the Clinical Diagnostic Potential of Genes (Overall Clinical Population) |
| Week 3 |
Exploring the Clinical Diagnostic Potential of Genes (Considering Different Clinical Populations) (I) |
| Week 4 |
Exploring the Clinical Diagnostic Potential of Genes (Considering Different Clinical Populations) (II) |
| Week 5 |
Exploring the Clinical Prognostic Value of Genes (Overall Clinical Population) |
| Week 6 |
Exploring the Clinical Prognostic Value of Genes (Considering Different Clinical Populations) |
| Week 7 |
Exploring the Clinical Prognostic Value of Genes (Considering Tumor Immunology) |
| Week 8 |
Mid-term Project Presentation |
| Week 9 |
Exploring Genes as Therapeutic Targets (Pharmacogenomics) (I) |
| Week 10 |
Exploring Genes as Therapeutic Targets (Pharmacogenomics) (II) |
| Week 11 |
Exploring Genes and the Tumor Microenvironment: Displaying Heatmaps and Presenting Correlation Scatter Plots (I) |
| Week 12 |
Exploring Genes and the Tumor Microenvironment: Displaying Heatmaps and Presenting Correlation Scatter Plots (II) |
| Week 13 |
Exploring Molecular Mechanisms: Co-expressed Gene Clusters and Functional Enrichment Analysis |
| Week 14 |
Abstract Writing and Poster Creation (I) |
| Week 15 |
Abstract Writing and Poster Creation (II) |
| Week 16 |
Final Project Presentation |
self-directed
learning |
02.Viewing multimedia materials related to industry and academia.
03.Preparing presentations or reports related to industry and academia.
|
|
| Evaluation |
(1) Assessment for this course will be based on a midterm report and a final report.
(2) Grading: midterm report 40%, final report 40%, regular attendance and participation 20%. |
| Textbook & other References |
Online Bioinformatics & Data Analysis Tools：
http://ualcan.path.uab.edu/cgi-bin/ualcan-res-mir.pl
https://www.proteinatlas.org/
https://kmplot.com/analysis/
https://tnmplot.com/analysis/
http://www.linkedomics.org/login.php
|
| Teaching Aids & Teacher's Website |
| Instructor-prepared course materials are available for download on iLearning. |
| Office Hours |
| Please contact the instructor to schedule an appointment. |
| Sustainable Development Goals, SDGs(Link URL) |
| 03.Good Health and Well-Being | include experience courses：N |
|