Bioinformatics Data sources & Sequence analysis: Databases and data availability. Using sequence data for analysis – sequence searching methods, multiple sequence alignments, residue conservation, Protein domains and families.
Protein Bioinformatics Methods: Protein structure and function prediction. Prediction of binding sites/interfaces with small ligands and with other proteins. Bioinformatics analyses using protein data.
Genomics: An introduction to the analysis of genomic data, primarily focussing on the data available from genome sequencing – how it can be used to study genetic variants and compare genomes (i.e. comparative and functional genomics).
Total contact hours: 32
Private study hours: 118
Total study hours: 150
Workshop (20% - short answer questions)
Assignment (80% - 2000 words)
a. Lesk A, Introduction to Bioinformatics, 5th Edition, Oxford University Press, 2019
b. Lesk A, Introduction to Genomics, 3rd Edition, OUP, 2017
Additionally selected peer-reviewed research and review papers will be recommended.
See the library reading list for this module (Canterbury)
The intended subject specific learning outcomes. On successfully completing the module students will be able to:
Use DNA/protein databases, sequence searching methods, generate multiple sequence alignments, analyse residue conservation.
Use bioinformatics methods to analyse and model protein structure, function and interactions with small ligands and with other proteins.
Understand genomics approaches including – genome sequencing, comparative and functional genomics.
The intended generic learning outcomes. On successfully completing the module students will be able to use:
Bioinformatics skills for data retrieval and analysis across the biosciences' disciplines. Data retrieval/analysis are generic to all numerate subjects.
Transferable skills including written communication (technical reports and a coursework project).
Analytical skills including analysis and presentation of data, writing of reports and a project (coursework).
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