This module aims to provide students with knowledge and competence in the use of computational tools relevant to the biotechnology field. This module introduces practical issues of computer-based handling and interpretation of biomolecular and genomic datasets. Students will utilise bioinformatics tools, web apps and databases and deploy them to make useful predictions about sequences with unknown structures and functions. Recent computational advances in protein engineering and enzyme design will be explored along with the use of computational design tools.
Week 1-2: Introduction to Bioinformatics
- Definition of bioinformatics and computational biology
- Applications of bioinformatics in biotechnology
- Introduction to various databases, tools, and web apps such as NCBI, BLAST, Ensembl, UniprotKB, and others.
Week 3: Sequence Analysis and Alignment
- Sequence analysis using computational tools
- Pairwise and multiple sequence alignment
- Global and local pairwise alignment
- Multiple sequence alignment using web apps and tools such as Clustal Omega and MUSCLE.
- Introduction to R
Week 4-5: Prediction of Protein Structure and Function
- Introduction to protein structure and function prediction
- Methods for predicting protein secondary and tertiary structures
- Web apps and tools for protein structure prediction, such as Phyre2 and Swiss-Model.
Week 6: Protein Structure Visualization and Analysis
- Introduction to protein structure visualization and analysis
- Use of the RCSB PDB resource
- Interactive biomolecular structure visualization with Pymol
- Structural analysis of protein families and prediction of protein flexibility using web apps and tools such as DynaMut and RAMPAGE.
Week 7-8: Comparative Modelling and Structure Validation
- 3D protein structure prediction using fold recognition and target-template alignment
- Use of Ramachandran plots to convey information about favourable energy geometries in predicted protein models
- Structure validation techniques and tools such as MolProbity and Verify3D.
Week 9-10: Computational ‘Omics’ for Biotechnology
- Introduction to computational tools applied to ‘omic’ technologies.
- Web apps and tools such as KEGG and DAVID for pathway analysis and functional annotation.
Week 11-12: Protein Engineering
- Overview of computational protein engineering methods, including site-directed mutagenesis and de novo design.
- Introduction to rational design of enzymes using tools such as Rosetta and Foldit.
The content of this module will be delivered by way of lectures/workshops . Practical workshops will be delivered through computer based sessions.
Using case studies and journals the students will be introduced to recent developments in the field. By analysing scientific articles, the students will also develop critical generic skills. In addition, important transferable skills such as communication skills, critical thinking and group work will be developed.
| Module Content & Assessment | |
|---|---|
| Assessment Breakdown | % |
| Other Assessment(s) | 100 |