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Syllabus for

Academic year
FFR110 - Computational biology
Beräkningsbiologi
 
Syllabus adopted 2020-02-20 by Head of Programme (or corresponding)
Owner: MPCAS
7,5 Credits
Grading: TH - Pass with distinction (5), Pass with credit (4), Pass (3), Fail
Education cycle: Second-cycle
Major subject: Bioengineering, Chemical Engineering, Engineering Physics
Department: 16 - PHYSICS


Teaching language: English
Application code: 11117
Open for exchange students: Yes
Block schedule: C

Module   Credit distribution   Examination dates
Sp1 Sp2 Sp3 Sp4 Summer course No Sp
0199 Examination 7,5c Grading: TH   7,5c    

In programs

MPCAS COMPLEX ADAPTIVE SYSTEMS, MSC PROGR, Year 1 (compulsory)
MPENM ENGINEERING MATHEMATICS AND COMPUTATIONAL SCIENCE, MSC PROGR, Year 1 (compulsory elective)
MPENM ENGINEERING MATHEMATICS AND COMPUTATIONAL SCIENCE, MSC PROGR, Year 2 (elective)
MPHPC HIGH-PERFORMANCE COMPUTER SYSTEMS, MSC PROGR, Year 1 (elective)

Examiner:

Kristian Gustafsson

  Go to Course Homepage


Eligibility

General entry requirements for Master's level (second cycle)
Applicants enrolled in a programme at Chalmers where the course is included in the study programme are exempted from fulfilling the requirements above.

Specific entry requirements

English 6 (or by other approved means with the equivalent proficiency level)
Applicants enrolled in a programme at Chalmers where the course is included in the study programme are exempted from fulfilling the requirements above.

Course specific prerequisites

Analysis in one variable, linear algebra, basic skills in analysis in several variables, and programming.

Aim

The aim of the course is to introduce students to the mathematical modeling of biological systems. The emphasis is on macroscopic phenomena such as population growth, morphogenesis and spreading of infectious diseases. Also microscopic phenomena are introduced, such as biochemical reactions, population genetics, and molecular evolution. A major topic is the role played by chance in the dynamics of biological systems, giving rise to stochastic fluctuations that must be described with statistical methods. The goal is to introduce mathematicians, physicists, and engineers to current important questions in Biology that require quantitative methods to solve.

Learning outcomes (after completion of the course the student should be able to)

explain what can be expected of mathematical models of biological systems, and what cannot be expected

decide whether deterministic or stochastic models are required in a given context

simulate deterministic and stochastic models for biological systems on a computer, and understand and describe the implications of the results clear and logical fashion

understand the purpose and predictive power of models of evolution

reflect ethical aspects especially regarding population genetics


Content

Continuous and discrete population dynamics. Competition between species. Stochastic models for population growth.

Biochemical reactions. Reaction-diffusion systems. Morphogenesis. Traveling waves. Deterministic vs. stochastic models for chemical reactions.

Models for disease spreading- Deterministic and stochastic models.

Population genetics.

Synchronisation of oscillators in biological systems.

Organisation

Lectures, set of homework problems, examples classes, and written exam.

Literature

Lecture notes will be made available.

Recommended additional material:
J. D. Murray, Mathematical Biology, 3rd edition, Springer, Berlin (2002)

Original research papers


Examination including compulsory elements

The final grade is based on three sets of homework assignments (60%) and a written examination (40%).


Published: Mon 28 Nov 2016.