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DRPS : Course Catalogue : School of Biological Sciences : Postgraduate

Postgraduate Course: Comparative and Evolutionary Genomics (PGBI11115)

Course Outline
SchoolSchool of Biological Sciences CollegeCollege of Science and Engineering
Credit level (Normal year taken)SCQF Level 11 (Postgraduate) AvailabilityNot available to visiting students
SCQF Credits10 ECTS Credits5
SummaryThe course covers primary genome annotation, including protein-coding and RNA genes in prokaryotes and eukaryotes; predicting gene/protein families across species; genome and gene-family phylogenies; reconciling gene and species trees; rDNA variation and evolution (partial SNPs or pSNPs); homology - orthologs, paralogs and xenologs; whole-genome comparison of large genomes; and pan-genomes and applications. Lectures are supplemented by on-line exercises and tutorials and in-course assignments.
Course description Detailed Programme
Week 1. Genome annotation 1: protein-coding genes (gene finding, ab-initio and homology-based; prokaryotes and eukaryotes; TBLASTN and BRAKER software). Lecture on principles, algorithms, sources of data and interpretation of evidence; computer-based practical class.
Week 2. Genome annotation 2: visualisation, manual refinement, functional noncoding DNA (Artemis software; RFAM database). Lecture on principles, sources of data and interpretation of evidence; computer-based practical class.
Week 3. Predicting gene/protein families across species (beginning with genome-wide protein sets; OrthoMCL and OrthoFinder software). Lecture on algorithms; computer-based practical class. Formative assessment set.
Week 4. Genome and gene-family phylogenies (multiple alignment and phylogeny reconstruction; MAFFT and IQ-TREE software). Lecture on algorithms; computer-based practical class. Formative assessment hand-in.
Week 5. Reconciling gene and species trees (Notung software). Lecture on concepts and algorithms; computer-based practical class. Coursework assignment set.
Week 6. Homology - orthologs, paralogs and xenologs 1 (including sub-types of paralog and xenolog; Notung software). Lecture on concepts and case-studies of biomedical relevance; computer-based practical class.
Week 7. Homology - orthologs, paralogs and xenologs 2 (Notung software). Lecture on algorithms, batch analyses and highways of horizontal gene transfer; computer-based practical class. Formative assessment returned with feedback.
Week 8. rDNA variation and evolution. Guest lecturer (from Quadram Institute Bioscience). Lecture and computer-based practical class.
Week 9. Q&A tutorial. Students can raise questions about coursework, course content and exams. No practical class.
Week 10. Pan-genomes and applications ("core" and "dispensable" components; "guilt by association" functional predictions from phylogenetic profiles and correlated gain/loss of genes). Lecture on algorithms; computer-based practical class.
Entry Requirements (not applicable to Visiting Students)
Pre-requisites Co-requisites
Prohibited Combinations Other requirements There is no formal pre-requisite for this course. However, students must have experience of the Linux command-line. This may be obtained, for example, by taking Bioinformatics Programming and System Management (PGBI11095) in Semester 1; or by Introduction to Bioinformatics for Life Scientists (PGBI11117) taken concurrently in Semester 2; or by previous experience.
Course Delivery Information
Academic year 2019/20, Not available to visiting students (SS1) Quota:  42
Course Start Semester 2
Timetable Timetable
Learning and Teaching activities (Further Info) Total Hours: 100 ( Lecture Hours 10, Supervised Practical/Workshop/Studio Hours 18, Programme Level Learning and Teaching Hours 2, Directed Learning and Independent Learning Hours 70 )
Assessment (Further Info) Written Exam 50 %, Coursework 50 %, Practical Exam 0 %
Additional Information (Assessment) In-course continuous assessment (50%). Exam (50%).
Feedback Written feedback will be provided for both ICA and exam.
Exam Information
Exam Diet Paper Name Hours & Minutes
Main Exam Diet S2 (April/May)2:00
Learning Outcomes
On completion of this course, the student will be able to:
  1. choose and apply algorithms and software to compare genome sequences, to make discoveries of evolutionary and/or functional importance.
  2. have enhanced competence and skills in bioinformatics.
Learning Resources
Additional Information
Graduate Attributes and Skills Computational thinking. Computer literacy. Bioinformatics. Interdisciplinarity.
Additional Class Delivery Information Weekly lectures (~1 hour) and practical classes (~2 hours) will include time to comment on whole-class performance.
KeywordsMSc Bioinformatics
Course organiserDr Daniel Barker
Tel: (0131 6)51 7812
Course secretaryMs Louise Robertson
Tel: (0131 6)50 5988
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