Comparative and Evolutionary Genomics
| Code | School | Level | Credits | Semesters |
| LIFE4141 | Life Sciences | 4 | 20 | Autumn UK |
- Code
- LIFE4141
- School
- Life Sciences
- Level
- 4
- Credits
- 20
- Semesters
- Autumn UK
Summary
This module will cover concepts of evolutionary biology and bioinformatics including alignment, phylogeny, pan genomes, population genomics and comparative genomics.
Weeks 1-6 inclusive UG and MSc and Weeks 7-10 MSc with the following content:
Week 1: Intro to genomics and comparative genomics.
Week 2: Homology and alignment (concepts and algorithms)
Week 3: Modelling evolution and molecular clocks
Week 4: Phylogeny reconstruction
Week 5: Statistics (confidence metrics) for phylogeny and interpretations.
Week 6: Evolution of mtDNA and its applications
Week 7: Maximum likelihood and Bayesian inference
Week 8: Networks and Pangenomes in comparative and evolutionary biology
Week 9: Population genomics in evolutionary biology 1
Week 10: Population genomics in evolutionary biology 2
Target Students
This module is for MSc Bioinformatics students.
Classes
This module may be delivered through lectures, seminars, workshops and labs etc
Assessment
- 50% Coursework 1: Students will complete an analysis relevant to the course. The coursework will be submitted in the form of a written report with a word count limit of 3000 words. Associated software and data generated for the coursework will be submitted to GitHub for assessment.
- 50% Exam 1 (1-hour): Students will be assessed in an exam on methods and approaches to analysis of evolutionary genomics and bioinformatics.
Assessed by end of autumn semester
Educational Aims
This course will be focussed on methods for understanding evolution in large data sets. Students will be introduced to current tools and techniques in this area, particularly focussed on large data sets and genome level information.Learning Outcomes
- A student who successfully completes this programme should have detailed knowledge and awareness of the basic principles and concepts of comparative and evolutionary biology including biology, computer science and statistics.
- A student successfully completing this programme should acquire an understanding of the intersection of life and information sciences.
- Successful students will be able to understand, assess and assist in the application of bioinformatics methods and workflows to a diverse range of problems in the biological sciences.
- A successful student will be able to communicate with both biologists and informaticians/computer scientists.