HEL-8023 Genomics in Clinical and Biomedical Research - 5 ECTS
PhD students or holders of a Norwegian master´s degree of five years or 3+ 2 years (or equivalent) may be admitted. PhD students must upload a document from their university stating that they are registered PhD students. This group of applicants does not have to prove English proficiency and are exempt from semester fee.
Holders of a Master´s degree must upload a Master´s Diploma with Diploma Supplement / English translation of the diploma. Applicants from listed countries must document proficiency in English. To find out if this applies to you see the following list:https://www.nokut.no/en/surveys-and-databases/nokuts-country-database/GSU-list/
For more information on accepted English proficiency tests and scores, as well as exemptions from the English proficiency tests, please see the following document: Proficiency in English - PhD level studies
For more information on accepted English proficiency tests and scores, as well as exemptions from the English proficiency tests, please see the following document:https://uit.no/Content/254419/PhD_EnglishProficiency_100913.pdf
The course has a capacity of 12 students. If there are less than 8 applicants, the course will be cancelled.
If there are more applicants than available spaces in the course, students will be given priority from category 1 to 4:
1. PhD students, research fellows and students participating in the Student Research Programme at UiT The Arctic University of Norway.
2. Participants in the Associate Professor Programme.
3. PhD students and students at a Medical Student Research Programme at other universities.
4. People who have minimum a master's degree or equivalent, but have not been admitted to a PhD programme.
Recommended prerequisites: Basic course in statistics (bachelor's level).
Note that if fewer than 8 participants have applied to the course, the course will be cancelled.
Topic in advanced genomic analysis in a medical translation perspective.
The content will be in three parts:
- The various genomic analysis techniques that are applied are reviewed and their theoretical foundation layed out. General thermes: Introduction to the technology and methods of analysis. (Sequencing (mainly the Illumnia technology), microarray and qPCRarray analysis, bioinformatic analyses and statistics (by use of Bioconductor R statistical language: preprocessing and normalization, alignment, Principal Component Analysis (PCA) and Partial Least Square Regression (PLS), clustering analysis, annotation &, pathway analysis, Gene Set Enrichment Analysis (GSEA), including handling of various databases and software tools).
- Examples from medical research on issues derived from clinical medicine where genomic analyses is applied.
- 'Hands-on' data analyses and statistical analyses of data generated through sequencing and microarray/PCRarray are including in this topic.
The students should be able to:
- assess the importance of the human genome in a molecular biology perspective as well as in the medical perspective on clinical issues.
- chose methodology that is applied to genomic analyzes within medical research based on the method's theoretical foundation.
The students should acquire to:
- apply these methods in their own studies.
- discuss current errors and limitations.
- evaluate the results, as well as assess the need for methodological development, and to actively participate in such efforts.
The students should be able to:
- understand scientific studies within the medical disciplines where genomic methods are applied.
Work requirements: Attendance at all practical lectures.
Examination and assessment:
Three-hour written exam (theory) and an one hour oral exam (presentation of a published manuscript with discussion). Both exams are weighted equally and are considered accordingly. The exams are graded with character A-F, where F is not passed.
The exam will be held in English.
There will not be given re-sit examination
- About the course
- Campus: Tromsø |
- ECTS: 5
- Course code: HEL-8023
- Responsible unit
- Department of Clinical Medicine