BM7121 - Genetic and Genomic Informatics (2022/23)
| Module specification | Module approved to run in 2022/23 | ||||||||||||
| Module title | Genetic and Genomic Informatics | ||||||||||||
| Module level | Masters (07) | ||||||||||||
| Credit rating for module | 20 | ||||||||||||
| School | School of Human Sciences | ||||||||||||
| Total study hours | 200 | ||||||||||||
|
|||||||||||||
| Assessment components |
|
||||||||||||
| Running in 2022/23(Please note that module timeslots are subject to change) |
|
Module summary
This module applies in silico approaches to explore the relationship between genotype and phenotype in the context of human disease and health. It includes an analysis of the influence of genetic variation in human populations to the penetrance of disease phenotype and to responses to environment, lifestyle and therapy. It runs in the Spring semester and is assessed by two pieces of coursework and a presentation. There are no pre-requisites other than satisfaction of general entry requirements.
Prior learning requirements
Module aims
Syllabus
Genome structure; physical and molecular approaches to gene mapping;
Genome databases and software;
Genome diversity, single nucleotide polymorphisms, haplotype mapping, functional analysis of polymorphisms using relevant databases and software;
Linkage analysis; mapping of complex traits;
Functional genomics – expression profiling, proteomics, metabolomics; databases and software;
Interaction between genome and environment – pharmacogenomics, foetal programming and nutrition, behaviour.
(LO1-3)
Balance of independent study and scheduled teaching activity
Students will be directed in their learning through a programme of lectures, and tutorials / IT sessions focussing on real-world case studies and problems, and an oral presentation. In addition there will be directed learning in preparation for and / or reflection on, lectures, tutorials and an oral presentation; directed learning for preparation for two pieces of coursework; and self-directed learning. Students will develop their knowledge and understanding of the subject, IT skills and their ability to apply their knowledge to real-world problems.
Learning and teaching
Learning outcomes
On successful completion of this module students will be able to:
1. Show a thorough understanding of the structure of the human genome and genome variation between individuals;
2. Demonstrate a comprehensive ability to extract, analyse and accurately interpret data on gene and genome variation from primary databases;
3. Demonstrate a thorough understanding of methodology for mapping genes to complex traits and demonstrate a high level of competency in the utilisation of selected genomic and related databases and software to extract, analyse and present data that explores the relationship between genotype and phenotype in health and disease;
Assessment strategy
The module will be summatively assessed by two pieces of coursework that will test the ability of students to extract data and knowledge applied to a contemporary problem, and include the use of IT skills acquired through the module (50% each).
To pass the module students must achieve a minimum aggregate mark of 50%
Component Learning outcomes
Data analysis report 1 1,2
data analysis report 2 3