Postgraduate Course: Credits Awarded for Taught Courses [University of Glasgow] Foundations of Bioinformatics BIOL5170 (MCLM11046)
Course Outline
School | Deanery of Molecular, Genetic and Population Health Sciences |
College | College of Medicine and Veterinary Medicine |
Credit level (Normal year taken) | SCQF Level 11 (Postgraduate) |
Availability | Not available to visiting students |
SCQF Credits | 15 |
ECTS Credits | 7.5 |
Summary | This is a placeholder course, designed to record marks for the University of Glasgow part of the programme, PRPHDISPME1F: Precision Medicine (PhD with Integrated Study)
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Course description |
Please see [University of Glasgow] Foundations of Bioinformatics BIOL5170
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Entry Requirements (not applicable to Visiting Students)
Pre-requisites |
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Co-requisites | |
Prohibited Combinations | |
Other requirements | None |
Course Delivery Information
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Academic year 2020/21, Not available to visiting students (SS1)
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Quota: None |
Course Start |
Flexible |
Timetable |
Timetable |
Learning and Teaching activities (Further Info) |
Total Hours:
150
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Programme Level Learning and Teaching Hours 3,
Directed Learning and Independent Learning Hours
147 )
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Assessment (Further Info) |
Written Exam
0 %,
Coursework
100 %,
Practical Exam
0 %
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Additional Information (Assessment) |
Please see [University of Glasgow] Foundations of Bioinformatics BIOL5170 for Components of Assessment
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Feedback |
Not entered |
No Exam Information |
Learning Outcomes
On completion of this course, the student will be able to:
- Critically compare molecular characteristics of the genome, transcriptome, proteome and metabolome, and integrate evidence from the literature to explain the links between these domains;
- Assess and critically compare the ways in which trees can be used to show relationships between entities;
- Plan a statistical approach to analysing a dataset and critically discuss how biological inferences can be made from such tests
- Creatively apply and critically compare a variety of approaches to the organisation, presentation and comparison of molecular data
- Use computer programming environments to execute a planned statistical analysis
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Additional Information
Graduate Attributes and Skills |
Not entered |
Keywords | Not entered |
Contacts
Course organiser | Dr Susan Farrington
Tel: (0131) 332 2471
Email: Susan.Farrington@ed.ac.uk |
Course secretary | Miss Susan Mitchell
Tel: (0131 6)51 7891
Email: Susan.Mitchell@ed.ac.uk |
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