Bioinformatics is a rapidly evolving interdisciplinary field that combines biology, statistics, and computer science to analyze and interpret complex biological data. This course provides essential concepts, methods, and computational tools widely used in modern bioinformatics research. Through hands-on workshops with bioinformatics software and techniques, the course develops practical skills to address real-world research challenges and apply these tools effectively to scientific research.

Course Modules

1. Foundational Skills: Statistics, R programming, and command-line tools
2. Molecular Evolution: Sequence alignment and phylogenetic analysis
3. Next Generation Sequencing (NGS): Genome assembly, annotation, and metagenomics
4. Special topics in Bioinformatics

Course selection: This is a Type 3 course. Here are the instructions to sign up for the waiting list (willingness)

Poll everywhere

• Understand bioinformatics as an interdisciplinary field and effectively communicate with researchers from different backgrounds
• Evaluate and identify appropriate bioinformatics tools and software for research purposes
• Develop analytical problem-solving skills in bioinformatics and integrate multiple bioinformatics techniques to extract information from biological data
• Work collaboratively in an interdisciplinary team to solve challenges in biological research

• This course is conducted entirely in English, and all materials are provided in English only
• No formal prerequisites are required for this course, but recommend basic knowledge of molecular biology, genetics, and statistics, along with introductory programming experience in R or similar languages
• Academic integrity is strictly enforced: Any form of cheating or plagiarism in assignments, exams, or assessments constitutes serious academic misconduct and will be handled according to university policy

The expected study time outside of class per week varies depending on the student's background: The expected study time outside of class varies based on prior experience:

• With relevant background: approximately 3-6 hours per week
• Without prior experience: approximately 4-8 hours per week or more

These estimates assume efficient use of study time on course materials. Additional time may be required for tasks such as debugging basic syntax errors, troubleshooting software issues, or inefficient study approaches like tackling advanced problems without mastering fundamentals or spending excessive time on unnecessary details - be aware of these obstacles and allocate extra time if needed.