Cancer Genomics
Ph.D. -course
- ECTS credits
- 3
- Teaching semesters
- Autumn, Spring
- Course code
- CCBIO906
- Number of semesters
- 1
- Resources
- Schedule
Course description
Course content
Learning outcomes
Upon completing this course the candidate should have:
Knowledge regarding
- What kinds of mutations may predispose for, contribute to, or appear during cancer development
- How these variants can be detected by NGS methods and be analysed bioinformatically
- How to employ these methods to stratify patients both diagnostically and therapeutically
- The different implications of the same aberrations depending on tissue type
- Ethical and legal regulations regarding genetic analyses of patient samples
Skills
- Can formulate problems, select methods and plan NGS analyses on samples from cancer patients
- Be able to assess the expediency and application of different NGS methods in cancer diagnostics and research
- To know the contact points for NGS analysis and data storage and analysis in Bergen
- Be able to communicate relevant literature and methods concerning cancer genomics
General Competency
- Be able to evaluate how knowledge about genome aberrations can help in understanding tumor biological mechanisms and as a guide to improved diagnosis, targeted treatment and follow up of cancer patients.
Study period
Credits (ECTS)
Course location
Language of instruction
Course registration and deadlines
Registration through Studentweb for UiB students. Deadline is September 1, 2023.
External participants may apply for a place at the course here: https://fsweb.no/soknadsweb/login.jsf
Deadline is September 1, 2023.
If you don't need the 3 ECTS (studiepoeng) registered as part of an education/degree, and just want to join the lectures for professional update, you register through this link: https://skjemaker.app.uib.no/view.php?id=15180189
Deadline is October 9, 2023. Note that registration might be closed earlier when fully booked.
Pre-requirements
Master's degree or equivalent education level is required, with the exception of students on the Medical Student Research Programme.
Recommended Previous Knowledge
Part of training component
Form of assessment
To pass the course, the candidate must:
- Prepare questions upfront of the course
- Participate during at least 90% of the course
- Prepare for and actively participate in the group work
- Submit a written one-page group work assignment
Grading scale:
Pass / Fail
Course overlap
Who may participate
Programme
4 full days with lectures and seminars
Group discussions with individual presentations
Reading curriculum (see mandatory reading)
The program can be read here:
Academic responsible
Lecturers
Reading list
The literature curriculum can be found here: