module specification

BM7027 - Bioinformatics and Molecular Modelling (2017/18)

Module specification Module approved to run in 2017/18
Module title Bioinformatics and Molecular Modelling
Module level Masters (07)
Credit rating for module 20
School School of Human Sciences
Total study hours 170
126 hours Guided independent study
44 hours Scheduled learning & teaching activities
Assessment components
Type Weighting Qualifying mark Description
Coursework 50%   Data Analysis 1
Coursework 50%   Data Analysis 2
Running in 2017/18
Period Campus Day Time Module Leader
Autumn semester North Friday Morning

Module summary

The module uses online databases and software to extract, analyse and interpret DNA and protein sequences and to model structures of proteins.

Prior learning requirements

Standard entry requirement: lower second first degree, or equivalent, in Biomedical Science, Biochemistry or a related subject.

Module aims

This module aims to:

  • Provide familiarity with the primary databases and common software packages used to analyse DNA, RNA and protein sequence, expression and structure, within and across genomes;
  • Develop informatic skills for extracting, analysing and presenting data to extract biological knowledge;
  • Apply the principles of macromolecular, and in particular protein, structure to the building f molecular models using modelling and graphics software;
  • Examine applications of modelling with emphasis on understanding the interactions between proteins and other molecules of biological or synthetic origin.


Primary and secondary databases in areas of biology, genetics, pharmaceutical science and biomedical science including gene and protein sequence databases, 3-D structure databases, genome databases and disease databases.
Application of online servers to sequence alignment and analysis of gene and protein databases, RNA structure prediction, molecular modelling and phylogenetic classification and pharmacogenomics  analysis. Docking and drug design.

Learning and teaching

Students will be presented with material in interactive teacher-led activities in the form of lectures and computer-based tutorial sessions. Student learning time will be used for assignments, data analysis and the preparation of coursework assignments.

PDP: on completion of this module students will write an evaluation of how the module allowed them to develop skills in data-mining, knowledge extraction and presentation in bioinformatics.

Learning outcomes

After completing the module students should have developed:

  • An advanced systematic knowledge of the theoretical aspects of bioinformatics and molecular modelling and an up-to-date knowledge of current developments and knowledge in this area;
  • An ability to apply knowledge learnt to bioinformatics and molecular modelling problems involving the extraction, analysing and presentation of data as appropriate;
  • Intellectual skills, through reflection and through practice by engagement with the module learning materials.

Assessment strategy

Module is assessed by two coursework components which provide formative as well as summative assessment. Module must be passed overall with pass mark of 50%.


Attwood T.K. and Parry-Smith D.J. (2001) Introduction to Bioinformatics, (1st Edition) Pearson Education.
Baxevanis A.D. and Ouellette B.F.F. (eds.) (2005) Bioinformatics.  A Practical Guide to the Analysis of Genes and Proteins,  (3rd edition) John Wiley.
Bishop M.J. (ed.) (1999) Genetics Databases, Academic Press.
Bourne P.E. and Weissig H. (eds.) (2003) Structural Bioinformatics, Wiley Europe.
Branden C. and Tooze J. (1999) Introduction to Protein Structure, (2nd edition) Garland Publishing.
Bromham, L.  (2008)  Reading the Story in DNA a beginner’s guide to molecular evolution.  Oxford University Press.
Brown, S.M. (2000) Bioinformatics: A Biologists Guide to Biocomputing and the Internet.  Eaton.
Campbell A.M. and Heyer L.J. (2006) Discovering Genomics, Proteomics and Bioinformatics (2nd Edition) Pearson Benjamin Cummings.
Dardel, F. and Kepes, F. (2006) Bioinformatics: Genomics and post-genomics, Wiley.
Fersht A. (1999) Structure and Mechanism in Protein Science. W.H. Freeman and Co.
Gibas C. and Jambeck P. (2001) Developing Bioinformatics Computer Skills. O’Reilly and Associates Inc.
Gopal, S., Haake, A., Jones, R.P. and Tymann, P. (2009) Bioinformatics: A Computing Perspective, McGraw-Hill.
Higgins D. and Taylor W. (Eds.) (2000) Bioinformatics: Sequence, Structure and Databanks: a Practical Approach, Oxford University Press.
Hodgman, C., French, A. and Westhead D.R. (2009) Bioinformatics (Instant Notes) BIOS Scientific Publishers.
Kleanthous C. (ed.) (2000) Protein-Protein Recognition. Frontiers in Molecular Biology. Oxford University Press.
Krane D.E. and Raymer M.L. (2002) Fundamental Concepts of Bioinformatics, Benjamin Cummings.
Leach A.R. (2001) Molecular Modelling. Principles and Applications (2nd Edition). Longman.
Lesk A.M. (2008) Introduction to Bioinformatics (3rd Edition), Oxford University Press.
Lesk A.M. (2010) Introduction to Protein Science: Architecture, Function and Genomics, (2nd Edition) Oxford University Press.
Mount, D.W. (2004) Bioinformatics; Sequence and Genome Analysis (2nd Edition) CSHL Press.
Pevsner, J. (2009) Bioinformatics and Functional Genomics, 2nd Edition, Wiley-Blackwell.
Sternberg, M.J. ed. (1996) Protein Structure Prediction – A Practical Approach, Oxford University Press.
Zvelebil, M. and Baum J.O. (2008)  Understanding Bioinformatics, Garland Science.