Programme Features
The Bioinformatics programme will be subsumed into BBiomedSc (JS6949). For more details, please refer to here.
The Bioinformatics programme at HKUMed nurtures the next generation of global leaders in the fields of biomedical data science and digital healthcare technology. Students are well-equipped to excel in diverse career paths within the healthcare, public health services and research profession and beyond, or pursue innovative entrepreneurship.
As a cutting-edge discipline, data science is now central to modern biomedical research and healthcare innovation. Our BSc(Bioinformatics) programme provides related essential training for future leaders in this wide-ranging field, particularly the high-impact biomedical big data applications, inclusive of genomics, precision medicine, single-cell analysis, multi-omic systems biology, digital health technology, mobile health, artificial intelligence (AI) analysis of medical imaging data, electronic health record analysis, and global health and epidemiology.
“Genome sequencing data not only allows us to identify targeted therapies for cancer patients, but also provides clues for the origin of their tumour.”
Dr. Jason W.H. Wong
Associate Professor and BSc(Bioinformatics) Programme Co-Director
The design of our BSc(Bioinformatics) curriculum is tailored to match a wide spectrum of personal interests with diverse career aspirations of being modern bioinformatics practitioners. The scope of their roles ranges from being biomedical researchers skilled at performing analysis with bioinformatics tools (bioinformatics users), to computational biologists capable of performing large-scale data analyses to solve biological questions (bioinformatics scientists), to software developers proficient inbuilding innovative computational or statistical tools for biomedical applications (bioinformatics engineers).
This programme is designed with a four-year curriculum covering a series of anchoring courses at different year levels, which enable the vertical and horizontal integration of various level courses from diverse disciplines, especially on essential statistical data analysis skills, key algorithms for biomedical informatics and fundamental concepts in modern genomic and health technology across. With great flexibility, the curriculum also allows students to take a multitude of disciplinary elective courses in biomedical sciences, statistics, computer science and biomedical engineering.
“Bioinformatics skills are critical to develop innovative digital technology for a healthier future.”
Dr Joshua W.K. Ho
Associate Professor and BSc(Bioinformatics) Programme Co-Director
Over the four-year curriculum, students are required to complete courses worth 240 credits comprising 96 credits from major courses, 36 credits from Common Core courses, and 18 credits from Language Enhancement courses, plus the remaining 90 credits from minors and electives.
Programme Structure
Core Courses for Bioinformatics Major
The core courses feature four categories: anchoring, foundation, project and disciplinary elective courses.
Anchoring Courses
Three anchoring courses are the centre-piece of the four-year programme. These courses adopt a case-based problem-solving approach to support interdisciplinary integration of subject-specific content at each year level (horizontal integration), while providing a consistent backbone for the curriculum across different year levels (vertical integration). Here are the compulsory anchoring courses:
- Introduction to Biomedical Data Science
- Artificial Intelligence in Medicine
- Big Data in Biomedical Informatics
Foundation Courses
Most of these courses to be taken in Years 1 and 2 of the programme focus on concepts and practical skills in basic bioinformatics topics, such as biochemistry, mathematics, statistics and computer programming. The completion of the following foundation courses is necessary:
- Perspectives in Biochemistry
- Computer Programming
- University Mathematics II
- Multivariable Calculus and Linear Algebra
- Probability and Statistics I
- Probability and Statistics II
Project: Capstone Experience
Each student is required to carry out an in-depth year-long research project in a specialised field of bioinformatics under the guidance of a supervisor who will provide a continuous performance assessment.
Disciplinary ‘Data Science Laboratory’ Courses
Taking an experiential learning approach, two innovative ‘Data Science Laboratory’ courses are offered to allow students to acquire hands-on computer programming and data analysis skills, apart from reinforcing the underlying principles of mathematical, statistical and algorithmic concepts through tailored dry-lab practical classes in genomics and digital health.
Students are required to complete either one of the following courses or both:
- Genome Sequencing and Analysis
- Digital Health
Disciplinary Elective Courses
A wide range of specialised courses in bioinformatics, biomedical sciences, statistics and computer science can be selected to fulfil the disciplinary elective requirements. Students are required to take three to four courses from a choice of over 20 courses. Some examples of bioinformatics courses include:
- Structural Bioinformatics
- Biomedical Software Systems
- Global Health Informatics
- Biomedical Image Informatics
Minor Options & Electives Courses
Students can plan their optional and elective studies with the remaining 90 credits in various manners. They may opt to take a minor and/or electives offered within the BSc(Bioinformatics) curriculum or offered in other curricula. The minor options offered in the BSc(Bioinformatics) curriculum include:
Minor in Digital Health
Example courses:
- Artificial Intelligence in Medicine
- Digital Health
- Biomedical Signals Processing and Modelling in Biomedical Applications
Minor in Biomedical Data Science
Example courses:
- Sequence Bioinformatics
- Global Health Informatics
- Statistical Machine Learning
Professional Recognition & Career Prospects
(Graduates with bioinformatics skills are of very high demand in the healthcare sector)
BSc(Bioinformatics) graduates will possess practical and transferable interdisciplinary skills highly applicable and widely used in the research and development, hospitals and the healthcare industry and beyond, both locally and internationally, which meet the growing demand for biotechnology and big data expertise in local and international research centres, as well as growing demand for the clinical and public health data analysis in the hospital and healthcare sector.
Here are some examples of tasks that our graduates can manage:
- Interpreting genetic testing results from patients and reporting findings to help clinicians to make treatment decisions.
- Identifying patterns in epidemic outbreak-based electronic records of passengers on public transport in order to guide pandemic prevention strategies.
- Predicting how novel compounds interact with proteins to help identify new targeted therapies for diseases.