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DEGREE REGULATIONS & PROGRAMMES OF STUDY 2015/2016

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DRPS : Course Catalogue : Deanery of Molecular, Genetic and Population Health Sciences : Molecular and Clinical Medicine

Postgraduate Course: Bioinformatics and Data Management (MCLM11008)

Course Outline
SchoolDeanery of Molecular, Genetic and Population Health Sciences CollegeCollege of Medicine and Veterinary Medicine
Credit level (Normal year taken)SCQF Level 11 (Postgraduate)
Course typeOnline Distance Learning AvailabilityNot available to visiting students
SCQF Credits10 ECTS Credits5
SummaryBioinformatics is at the interface between two of the most influential scientific fields. An appreciation of computational and biological sciences, in particular the terminology employed in both fields, is essential for those working at such an interface.
In this course, we aim to cover the following:
The concepts of computer science that relate to problems in biological sciences
Commercial and academic perspectives on bioinformatics
The impact of bioinformatics on the methodologies used in biological science
The influence biological science has on computing science
Course description Not entered
Entry Requirements (not applicable to Visiting Students)
Pre-requisites Co-requisites
Prohibited Combinations Other requirements None
Course Delivery Information
Academic year 2015/16, Not available to visiting students (SS1) Quota:  None
Course Start Semester 2
Timetable Timetable
Learning and Teaching activities (Further Info) Total Hours: 100 ( Seminar/Tutorial Hours 5, Online Activities 100, Feedback/Feedforward Hours 40, Formative Assessment Hours 12, Summative Assessment Hours 10, Revision Session Hours 8, Programme Level Learning and Teaching Hours 2, Directed Learning and Independent Learning Hours 0 )
Assessment (Further Info) Written Exam 0 %, Coursework 100 %, Practical Exam 0 %
Additional Information (Assessment) Online participation: 25%
Individual project: 25%
Reflective portfolio: 30%
Case scenarios: 20%
Feedback Not entered
No Exam Information
Learning Outcomes
On completion of this course, the student will be able to:
  1. Describe the main computational algorithms used in the analysis of biological sequences
  2. Discuss the practical limitations of sequence analysis methods and contrast the methods available
  3. Appraise common biological data sources and the key contributing error/noise sources in such data
  4. Recognise experimental design in biology as critical to subsequent data analysis and representation in bioinformatics
  5. Critically evaluate research literature in the field
Reading List
None
Additional Information
Graduate Attributes and Skills Not entered
KeywordsClinical trials, bioinformatics, data management
Contacts
Course organiserMiss Michelle Evans
Tel: 0131 537 3326
Email: michelle.evans@ed.ac.uk
Course secretaryMrs Danielle Marlow
Tel: 0131 537 3798
Email: Danielle.Wilson@ed.ac.uk
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