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 2023/24, 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
(
 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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