Undergraduate Course: Computational Biology and Systems Biology 3 (IBMS09009)
|School||Deanery of Biomedical Sciences
||College||College of Medicine and Veterinary Medicine
|Credit level (Normal year taken)||SCQF Level 9 (Year 3 Undergraduate)
||Availability||Not available to visiting students
|Summary||Computational models of biological systems are used both in basic research and in applied medical and pharmaceutical settings. This course introduces the principles of computational biology and systems biology, and equips students with the skills needed to build, validate, and use models of biological systems, following standards for model quality and reproducibility.
Computational models of biological systems are used both in basic research and in applied medical and pharmaceutical settings. This course introduces the principles of computational biology and systems biology, and equips students with the skills needed to build, validate, and use models of biological systems, following standards for model quality and reproducibility.
Entry Requirements (not applicable to Visiting Students)
||Other requirements|| None
Course Delivery Information
|Academic year 2022/23, Not available to visiting students (SS1)
|Learning and Teaching activities (Further Info)
Lecture Hours 18,
Seminar/Tutorial Hours 3,
Supervised Practical/Workshop/Studio Hours 48,
Feedback/Feedforward Hours 1,
Programme Level Learning and Teaching Hours 4,
Directed Learning and Independent Learning Hours
|Assessment (Further Info)
|Additional Information (Assessment)
||- SAQ written exam (individual; 50%)«br /»
- Course project (individual; 50%)«br /»
||There will be a formative mid-semester assessment with an SAQ format, helping students prepare for the final exam.
Students receive formative feedback on their proposed project by the end of the week 4 hackathon.
Additional feedback will be given throughout the course during practical sessions, individual catch-up sessions and on online discussion forums.
|No Exam Information
On completion of this course, the student will be able to:
- Describe the key principles of computational modelling in life sciences.
- Develop and implement appropriate models for specific biological systems, and be aware of their capabilities and limitations.
- Adhere to common standards of model description, sharing and storage in databases.
|Graduate Attributes and Skills
||This course develops the following graduate skills and attributes:
General professional skills: Time management, project management, independence, curiosity, selfmotivation, ability to complete projects, critical thinking, dedication, analytical reasoning, scientific creativity.
Computational and Bioinformatics Skills: Ability to use scientific and statistical analysis software packages, ability to use standard languages and protocols, retrieving and manipulating data from public repositories; expertise in common bioinformatics software packages, tools, and algorithms.
Biology: Molecular biology, cell biology, biochemistry, systems biology, cancer, infection, neuroscience.
Statistics and Mathematics: Probability theory, differential equations and parameter estimation, graph theory.
|Keywords||computational modelling,systems biology,synthetic biology
|Course organiser||Dr Gediminas Luksys
Tel: (0131 6)50 3525
|Course secretary||Miss Natasha Goldie