Natural Sciences

Mathematical Modelling in Biology and Medicine (2020/1)

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Module TitleMathematical Modelling in Biology and Medicine Credit Value15
Module CodeNSCM005 Module ConvenorProfessor Krasimira Tsaneva
Duration: Term 1 2 3
No. of weeks 11
Number students taking module (anticipated) 25
Module description

This is an advanced module in mathematical modelling applied to biology and medicine that focuses on modern applications of mathematical techniques to cutting-edge research in these areas. It will introduce you to advanced topics in biochemical networks, physiology, epidemiology and biomedical data analysis. The module is run as a combination of lectures and hands-on computational modelling sessions, and may also involve laboratory visits.

This module provides you with small-group teaching across a selection of advanced topics, reflecting the research interests of the staff involved. The syllabus consists of three short courses, each taught as a self-contained set comprising four lectures together with four workshops/tutorials. In order to take this module, you must ensure that you have completed module ECM2702 Differential Equations.

This is an optional module for final year students of MSci Natural Sciences, and is also an optional module for Third Year Mathematics, Computer Science and Physics undergraduates.

Module aims

This module aims to introduce you to some of the advanced mathematical and computational modelling methods that are currently used in modern mathematical biology research. It will give you experience of hands-on modelling approaches, and develop an interdisciplinary viewpoint of biology. In this module, you will put into practice the knowledge you have acquired so far in your degree programme, and engage with modern scientific developments in an expanding and increasingly important field of study.

As part of this module, you will develop your skills in several of the following areas: literature review; project planning; experimentation and analysis; interpretation of results; and technical report writing.

INTENDED LEARNING OUTCOMES (ILOs) (see assessment section below for how ILOs will be assessed)

On successful completion of this module, you should be able to:

Module Specific Skills and Knowledge:

  • 1. Build computational/mathematical models that can capture biological phenomena and guide experimental studies (through hypothesis generation, experimental validation, etc.)
  • 2. Analyse models and experimental data using appropriate tools/techniques
  • 3. Critically evaluate and analyse the module content within the context of wider reading to develop an overarching view of the interconnectedness of the subject and its interdisciplinary nature
  • 4. Recognise and exploit any connections between taught materials and project material
  • 5. Engage in targeted research and reading for personal development and future educational requirements, in addition to reading material primarily for assessment purposes

Discipline Specific Skills and Knowledge:

  • 6. Apply a range of computational and mathematical methods to model diverse biological phenomena
  • 7. Combine experimental and theoretical concepts, literature and ideas
  • 8. With reference to primary literature, evaluate how research developments in applied mathematics and computer science drive the subject forward and, where appropriate, the social, technological and commercial impacts they have
  • 9. Analyse in detail essential facts and theory in advanced areas of mathematical biology
  • 10. Analyse and evaluate independently a range of research-informed examples from the literature into written work
  • 11. With limited guidance, deploy established techniques of analysis and enquiry used in mathematical biology at the research level

Personal and Key Transferable/Employment Skills and Knowledge:

  • 12. Communicate effectively with scientists possessing experimental backgrounds
  • 13. Think creatively and beyond traditional discipline boundaries
  • 14. Successfully communicate arguments, evidence and conclusions using written means in a manner appropriate to the intended audience
  • 15. Devise and sustain, with little guidance, a logical and reasoned argument with sound, convincing conclusions
  • 16. Analyse and evaluate appropriate data with very limited guidance

SYLLABUS PLAN - summary of the structure and academic content of the module

Each topic is a self-contained short course lasting 8 hours, with its own specific syllabus available in separate documentation on the associated ELE page for this module. Three topics will run each academic year depending on demand and staffing. Topics may include the following:

  • Mathematical modelling of gene-regulatory/metabolic networks;
  • Mathematical modelling of excitable physiological systems;
  • Uncertainty quantification in biomedical modeling;
  • Disease dynamics on complex networks;
  • Mathematical models of hormone signalling.
LEARNING AND TEACHING
LEARNING ACTIVITIES AND TEACHING METHODS (given in hours of study time)
Scheduled Learning and Teaching ActivitiesGuided independent studyPlacement / study abroad
241260
DETAILS OF LEARNING ACTIVITIES AND TEACHING METHODS
CategoryHours of study timeDescription
Scheduled learning and teaching12Lectures
Scheduled learning and teaching12Tutorials or workshops
Guided independent study126Additional reading; model development; computational methods
ASSESSMENT
FORMATIVE ASSESSMENT - for feedback and development purposes; does not count towards module grade
Form of assessmentSize of the assessment (eg length / duration)ILOs assessedFeedback method
Non-assessed problems and summary materials provided for self-checking purposesOngoingAllOral in class
SUMMATIVE ASSESSMENT (% of credit)
CourseworkWritten examsPractical exams
10000
DETAILS OF SUMMATIVE ASSESSMENT
Form of assessment% of creditSize of the assessment (eg length / duration)ILOs assessedFeedback method
Problem set 1501500 words equivalentAllDetailed feedback sheet
Problem set 2501500 words equivalentAllDetailed feedback sheet
DETAILS OF RE-ASSESSMENT (where required by referral or deferral)
Original form of assessmentForm of re-assessmentILOs re-assessedTimescale for re-assessment
Problem set 1Problem setAllAugust Ref/Def period
Problem set 2Problem setAllAugust Ref/Def period
RE-ASSESSMENT NOTES

Deferral – if you miss an assessment deadline for certificated reasons judged acceptable by the Mitigation Committee, you will normally be either deferred in the assessment, or an extension may be granted. The mark given for a re-assessment taken as a result of deferral will not be capped and will be treated as if it were your first attempt at the assessment.

Referral – if you have failed the module overall (i.e. obtained a final overall module mark of less than 50%) you will be required to complete a further problem set. The mark given for a re-assessment taken as a result of referral will count for 100% of the final mark and will be capped at 50%.

RESOURCES
INDICATIVE LEARNING RESOURCES - The following list is offered as an indication of the type & level of information that you are expected to consult. Further guidance will be provided by the Module Convener

Reading list for this module:

  • Klipp E, Liebermeister W, Wierling C, Kowald A, Lehrach H, Herwig R. Systems Biology: A Textbook. Wiley (2009).
  • Alon U. An Introduction to Systems Biology: Design Principles of Biological Circuits. Chapman and Hall (2006).
  • Strogatz SH. Nonlinear Dynamics and Chaos: With Applications to Physics, Biology, Chemistry and Engineering. Perseus Books (2000).
  • Britton NF. Essential Mathematical Biology. Springer (2005).

More specialised reading lists will be provided at the start of each short course.

Module has an active ELE page?

Yes

Web based and electronic resources
Other resources

 

CREDIT VALUE 15 ECTS VALUE

7.5

PRE-REQUISITE MODULES

MTH2003 Differential Equations

CO-REQUISITE MODULES

PHY 1026PHY1026 Mathematics for Physicists; PHY2025 Mathematics with Physical Applications

NQF LEVEL (FHEQ)

7

AVAILABLE AS DISTANCE LEARNING?

No

ORIGIN DATE

01/12/2015

LAST REVISION DATE

24/03/2020

KEY WORDS SEARCH

Mathematical Biology; Systems Biology; Synthetic Biology; Biomedical Modelling; Mathematical Biomedicine; Mathematical Physiology