Content and teaching | Assessment | Availability

Module content and teaching

Principal aims

"The course is designed to develop student research skills in the area of computational biology. Students will become aware of the elements of research, including appraising the literature, developing novel approaches, assessing results and drawing conclusions that they will be able to set against the current field. The module will allow students to be original in their application of knowledge to the solution of new, research-led problems. The course will cover topics of computational cell biology and bioinformatics. Students will be introduced to computational modelling of dynamic cellular processes and some techniques from the theory of dynamical systems used for analysing these models. Emphasis will be placed on areas of great current interest such as neural systems, cell signalling, and calcium dynamics. Students will also be introduced to some key problems in bioinformatics, the models used to formally describe these problems, and algorithmic approaches used to solve them. Students will be expected to show how the theory of machine learning serves as framework and a foundation for the efficient organisation, analysis and retrieval of large amounts of data; and to understand how the nature of the biological problems to be ""solved"" relate to the computational methods used to ""solve"" them. "

Principal learning outcomes

By the end of the module: the student should be familiar with principles used in modelling dynamic phenomena in cells and methods that are used to analyse computational models; should understand basic research methods in bioinformatics; the student should understand the data structure (databases) used in bioinformatics and interpret the information (especially: find genes; determine their functions), understand and be aware of current research and problems relating to the area of their research project, to be able to critically evaluate the literature and identify the most important body of work; the student should be aware of the range of technologies available to computer scientists in bioinformatics; the module the student should able to carry out data mining gene and protein expression patterns and modelling cellular interactions and processes; the student should have been able to develop their key numerate, literate, IT and communication skills, write a high quality report including an appraisal of the literature, methods, results, discussion and conclusion.

Timetabled teaching activities

20 one-hour lectures plus 10 one-hour seminars

Departmental link

http://www2.warwick.ac.uk/fac/sci/dcs/teaching/modules/cs904

Module assessment

Assessment group	Assessment name	Percentage
15 CATS (Module code: CS904-15)
C1 (Assessed/examined work)	Assessed Course Work	50%
	Examination - Main Summer Exam Period (weeks 4-9)	50%
	Assessed Course Work	50%
	Examination - Main Summer Exam Period (weeks 4-9)	50%

Module availability

This module is available on the following courses:

Core

N/A

Optional Core

N/A

Optional

• Undergraduate Discrete Mathematics (G4G3) - Year 4
• Undergraduate Computer Science MEng (G503) - Year 4
• MEng Computer Science (with intercalated year) (G504) - Year 5