AS6007 - Bioinformatics and Bioanalytical Techniques (2017/18)
|Module specification||Module approved to run in 2017/18|
|Module title||Bioinformatics and Bioanalytical Techniques|
|Module level||Honours (06)|
|Credit rating for module||30|
|School||School of Human Sciences|
|Total study hours||300|
|Running in 2017/18||
The module will use online public databases and software to extract, analyse and interpret nucleic acid and protein sequences and to model the structures of RNA and protein sequences. Genomics in particular pharmacogenomics and phylogeny are covered. Additionally, it will review advanced bioanalytical techniques, including hybrid techniques, used in the analysis, detection and quantification of molecules in biological and other relevant systems.
Prior learning requirements
AS5005 Molecules of Heredity and Defence, CH5007 Bioanalytical Science
The aims of this module are aligned with the qualification descriptors within the Quality Assurance Agency’s, Framework for Higher Education Qualifications. The module aims to : provide familiarity with the primary and secondary databases used to analyse DNA, RNA and protein sequence, expression and structure, within and across genomes; develop informatics’ skills for extracting, analysing and presenting data to extract biological knowledge; apply the principles of macromolecular, and in particular protein structure, to the building of molecular models using modelling and graphics software; understand the importance of protein-protein interactions and protein-drug interactions by applying molecular modelling techniques; develop students’ understanding of advanced bioanalytical techniques and enable students to determine which analytical technique is suitable for a particular type of sample; reinforce and build on analysis skills introduced in CH5007 to enable students to interpret more advanced data, particularly spectra and chromatograms and to solve defined problems; give students practical experience in selected analytical techniques. This module aims to provide students with the qualities and transferable skills necessary for employment requiring: the exercise of initiative and personal responsibility; decision-making in complex and unpredictable contexts; and, the learning ability needed to undertake appropriate further training of a professional or equivalent nature.
The primary and secondary databases in biology including protein and gene sequences, protein structures, genome databases, disease databases - content, structure of files, links and other information.
Software for sequence analysis, including screening gene and protein databases, comparison of sequences, identification of functional domains, classification, phylogenetic analysis, RNA structure prediction.
Principles of protein architecture – review the role of non-covalent forces in the formation of secondary, tertiary and quaternary structures; protein folds and domains; folding and stability; membrane proteins; protein movement; protein complexes.
Software for analysis of known protein and nucleic acid structure.
Modelling protein structure; structure prediction by homology modelling; other approaches to prediction; probing active sites; protein interaction with other biomolecules; both proteins and drugs in particular. Protein-protein interactions and systems biology.
Development and application of modern analytical instrumentation. Validation of analytical measurements. Quality assurance, quality control and SOPs. Chromatographic techniques not included in MP501: size exclusion chromatography, affinity chromatography and ion exchange chromatography.
Atomic spectroscopy. Instrumentation and applications. Atomic absorption spectroscopy: hollow cathode lamps; pneumatic nebulisers; the air-acetylene flame as an atom cell for atomic absorption. Inductively coupled plasma (ICP), arcs, sparks and other discharges as atom cells. X-ray techniques including x-ray fluorescence. Hybrid techniques: Gas chromatography with mass spectrometric detection (GC-MS), liquid chromatography with mass spectrometric detection (LC-MS), inductively coupled plasma with mass spectrometric detection (ICP-MS). Applications to include metal analysis by ICP-MS; selective and sensitive detection of analytes using GC-FTIR. Mass spectrometry: electron impact ionisation fragmentation patterns and their use in structural elucidation of a molecule. Proteomics and metabolomics; analysis using LC-MS; to include a case study on the detection of phytoestrogens in urine. Methods for the detection of drugs of abuse using amphetamines as an example: to include fluorescence polarisation immunoassay (FPIA) and identification of amphetamines by mass spectrometry. Biosensors with a focus on the development of the glucose biosensor and future development of implantable biosensors. Raman spectroscopy: Mechanism of generation of Raman spectra, comparison of Raman and IR data. Autoanalysers
To reinforce and develop analysis skills introduced in CH5007; there will be an emphasis on analysis of data: HPLC chromatograms, including troubleshooting – how to achieve good separation on HPLC; GC-MS data; LC-MS spectra; NMR spectra
Learning and teaching
Students will be presented with material in interactive teacher-lead activities in the form of lectures, and IT tutorials. Student learning time will be used for class assignments, data analysis and preparation for coursework assignments .
Students will be allowed the opportunity to acquire knowledge of the subject material through teacher-led activities in the form of lectures and tutorials and practicals. This will be supported by the use of directed reading and the provision of web-based material. Students' abilities to seek, handle and interpret information will be developed through tutorial exercises. Students' abilities to think critically and produce solutions will be developed through the presentation of a practical laboratory report and data evaluation exercises encountered in tutorials. Students will be expected to reflect on taught material in order to demonstrate their understanding of the principles and practices of modern bioanalytical techniques
On successful completion of this module students will be able to:
- Critically analyse the type of information contained within different primary and secondary databases and be able to extract appropriate biological information.
- Select appropriate software for informatic analysis and present the output in a useful form with biological context.
- Evaluate the important factors which determine the structure of, and interactions between, different types of biological molecules.
- Analyse standalone structures and complexes between different structures utilising graphics and modelling software.
- Critically analyse results obtained from the running of bioinformatics programs
- Critically evaluate the principles and practice of selected bioanalytical techniques;
- Discuss critically the impact of these techniques in the analysis of a variety of different sample matrices;
- Evaluate and interpret HPLC chromatograms and GC-MS data;
Complete analyses with due attention to quality control, evaluate the data obtained and communicate results effectively.
The module will be assessed by means of four coursework components, which will provide formative as well as summative assessment. The module must be passed overall with a pass mark of 40%.
The first assignment (25% of the overall module mark) will involve the use of software to analyse gene and protein primary structure. The second assignment (25% of the overall mark) will involve the use of modelling and graphics software to predict and display protein structures and explore interactions of proteins with ligands, drugs or other biomolecules. The third assignment is a time constrained problem solving exercise.
The students’ abilities to interpret information, to think critically and then to present solutions will be assessed by a time-constrained problem solving exercise (10%). This will be in the form of a seen research article or set of data (e.g. HPLC chromatograms; GC-MS data; NMR spectra) on which the students will be required to answer unseen questions.
A full written practical report (15%) will assess the students’ abilities to carry out an analysis, acquire data and interpret their own and fellow students’ data and evaluate the suitability of the analytical technique employed.
An end-of-module examination (25%) will assess the students' critical analysis of the subject material and their ability to communicate this in written form.
To pass the module, students need to achieve a minimum aggregate mark of 40%. There will be an attendance requirement for the practical sessions. If the module is passed on reassessment, then the maximum mark awarded will be 40%.
|Data Analysis 1||1,2,3,5|
|Data Analysis 2||1,2,3,4,5|
|Problem Solving Exercise||6,7,8,9|
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.
Harris, D C. (2010) Quantitative Chemical Analysis, 8th edition, W H Freeman and Co. New York, USA
Hodgman, C., French, A. and Westhead D.R. (2009) Bioinformatics (Instant Notes) BIOS Scientific Publishers.
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.
Rubinson K A and Rubinson J F (2000) Contemporary Instrumental Analysis
Prentice-Hall, New Jersey, USA.
Williams, D and Fleming I. (2008) Spectroscopic Methods in Organic Chemistry, 6th edition, McGraw-Hill Higher Education, Maidenhead, UK
Zvelebil, M. and Baum J.O. (2008) Understanding Bioinformatics, Garland Science.
Plus numerous websites – as detailed in module booklet.