Gwybodaeth Modiwlau

Module Identifier
Module Title
Bioinformatics and Functional Genomics
Academic Year
Semester 1
Other Staff

Course Delivery

Delivery Type Delivery length / details
Lecture 24 x 1 Hour Lectures
Workshop 6 x 2 Hour Workshops


Assessment Type Assessment length / details Proportion
Semester Assessment Human genome essay.  10%
Semester Assessment Transcriptomics poster.  10%
Semester Assessment Comparative genomics workshop.  10%
Semester Assessment Metabolomics workshop.  10%
Semester Assessment SNP marker workshop.  10%
Semester Assessment Microsatellite marker workshop.  10%
Semester Exam 2 Hours   Essay question paper.  40%
Supplementary Assessment Students must take elements of assessment equivalent to those that led to failure of the module.  60%
Supplementary Exam 2 Hours   Students must take elements of assessment equivalent to those that led to failure of the module.  40%

Learning Outcomes

On successful completion of this module students should be able to:

1. Communicate a theoretical experience of using genomics and related databases to analyse gene and genome inter-relationships.

2. Demonstrate an understanding of the basic technological principles of transcriptome, proteome and metabolome analysis.

3. Describe the current methodologies for prediction of the structural relationships of proteins.

4. Evaluate the value and constraints associated with the study of model systems for functional genomics.

5. Discuss the range of computational methods being used to interpret functional genomics data.

6. Appreciate current research strategies for gene discovery and determining gene function (functional genomics) and biological data analysis and interpretation (bioinformatics).

7. Describe the role that genomics and bioinformatics has to play in modern medicine and fundamental research.

8. Demonstrate skills and knowledge of the concepts underlying database access, sequence analysis, protein classification and functional assignment.

Brief description

This module is an integrated series of lectures, seminars and workshops covering the modern discipline of Functional Genomics. Functional Genomics has been defined as 'The development and application of global (genome-wide or system-wide) experimental approaches to assess gene function by making use of the information and reagents provided by genome sequencing and mapping. Functional genomics employs novel technologies for genome-wide analysis supported by IT. This involves experimental and computational methods. High throughput experimental technologies based on measuring gene expression, protein structure and metabolomics are being used to generate large datasets to aid understanding of gene function. Powerful information systems are required for the efficient management and integration of the experimental data. The results emerging from these analyses will inform new predictive strategies to identify new and useful genes and potential drug targets, understand gene behaviour, and develop novel therapeutic products.


The lectures will cover the following topics:
  • An Introduction to Functional genomics
  • The Human Genome Project
  • Development of genomics resources
  • Genome mapping strategies
  • Model systems for functional genomics
  • Introduction to 'Omic' technologies
  • Methodologies for predicting gene function
  • Transcriptomcs
  • High throughput Screening
  • Proteomics
  • Metabolomics
  • Systems Biology
  • Specific examples of the application of genomics and bioinformatics to ongoing research at Aberystwyth
The lectures will be complemented by 4 computer workshops focusing on

  • Analyzing transcriptomic data
  • Protein modeling and secondary structure prediction
  • Interrogating metabolomic data
  • Mapping genes using single nucleotide polymorphisms.

Module Skills

Skills Type Skills details
Application of Number Students will have opportunity to collect and interpret data in practical classes with respect to quality and quantity. This will include the Application of statistically-based web tools for analysis of “omic data to interpret, derive hypotheses and criticize. Feedback on this will be provided with the returned assignment.
Communication Students will develop effective listening skills for the lectures. Students will develop effective written communication skills in practical class write-ups. Feedback on this will be provided with returned assignment.
Improving own Learning and Performance Student's ability to devise and monitor time management, learning and performance skills throughout module via attending lectures and practical classes.
Information Technology Students will develop skills in accessing the web for information sources and free software for functional genomic analyses and data display.
Personal Development and Career planning
Problem solving Students will develop skills in lectures. Practicals will be designed to allow students to gain experience in extracting and interpreting data. Feedback on will be provided with the returned assignment.
Research skills Practical classes will develop skills in the extractions and analysis of data from web-accessible databases and the critical evaluation of data. Feedback will be provided with returned assignments.
Subject Specific Skills Accessing, assimilating and storing information via remote computer servers.
Team work


This module is at CQFW Level 6