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CH925 - Computational Modelling

  • Module code: CH925
  • Module name: Computational Modelling
  • Department: Chemistry
  • Credit: 10

Content and teaching | Assessment | Availability

Module content and teaching

Principal aims

This module aims at a basic understanding of fundamental numerical methods applied to biological problems. We will concentrate on modelling dynamical systems in time and space, e.g. chemical kinetics, interacting and competing species, pattern formation in development. In the accompanying computer practical different numerical algorithms will be implemented in Matlab and thoroughly evaluated. Each student will give a short presentation (10 min) on selected topics in computational modelling or on example solutions to problems discussed in the practical.

Principal learning outcomes

"(a) Subject knowledge and understanding Students will learn fundamental numerical methods for root finding, solving single and multivariable ordinary and partial differential equations. They will understand how to use numerical methods to solve particular biological problems arising in population dynamics, chemical reaction kinetics and pattern formation (reaction diffusion systems). The will develop a critical awareness of current best practice in application of numerical methods to a range of problems in research at the physical/life sciences interface. (b) Key Skills: Key skills students acquire will allow them to: Classify mathematical problems and choose appropriate numerical methods, derive basic numerical methods from first principles, discuss in detail truncation and round-off errors, efficiently solve problems on the computer using Matlab. They will be able to critically assess when a given approach might be appropriate and when it should be avoided. (c) Cognitive Skills: The students will be aware of how important it is to understand numerical methods and their prerequisites in detail in order to ensure that a solution can be approximated at all and to gauge the trade-off between speed and accuracy. They will learn how to use numerical approaches to interpret data from a range of different areas and to aid their critical interpretation of such data. (d) Subject-Specific/Professional Skills Students will be able to apply the learnt methods to solve computational problems and quantitatively analyse experimental data, as required in most research projects undertaken by Systems Biology or MOAC students. They will be able to choose appropriate methods for a problem and use them to solve or at least take them a stage closet to a solution. They will be able to independently analyse the needs of a problem and plan how to tackle it using numerical methods."

Timetabled teaching activities

Lectures for the module 20 hours; Workshops for the module 10 hours; Seminars for the module 8 hours; Total contact hours 38 hours.

Departmental link

Module assessment

Assessment group Assessment name Percentage
10 CATS (Module code: CH925-10)
C (Assessed/examined work) Assessed work 50%
  Examination (locally held) 50%
VA (Visiting students only) 100% assessed (part year) visiting 100%

Module availability

This module is available on the following courses:

  • PG Taught Mathematical Biology and Biophysical Chemistry (F1P4) - Year 1
Optional Core
  • Postgraduate Taught Molecular Analytical Science (F1PL) - Year 1
  • MSc in Communicating Multidisciplinary Science (F1PA) - Year 1
  • MSc in Chemistry with Scientific Writing (F1PB) - Year 1
  • Postgraduate Taught Scientific Research and Communication (F1PE) - Year 1
  • Postgraduate Taught Scientific Research and Communication (F1PE) - Year 2
  • Postgraduate Taught Analytical Science: Methods and Instrumental Techniques (F1PG) - Year 1
  • Postgraduate Taught Analytical Science: Methods and Instrumental Techniques (F1PG) - Year 2
  • Postgraduate Taught Analytical Science: Methods and Instrumental Techniques (F1PG) - Year 3
  • Postgraduate Taught Analytical Science and Instrumentation (F1PY) - Year 1