DD2435 Mathematical Modelling of Biological Systems 9.0 credits

Neuronnäts- och biomodellering

The course focuses on mathematical modelling and computer simulation of nerve cells, neuronal networks and other physiological and biochemical structures and processes.

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Course information

Content and learning outcomes

Course contents *

Methods for mathematical modelling and computer simulation of biological processes and functions. Of primary concern is the nervous system (nerve cells and neuronal networks) but other systems are also treated. Intracellular processes like biochemical networks, enzyme kinetics, cell signalling, genetic networks and switches are treated, as well as biological morphogenesis and some current theories of biological perception, learning and memory.

Intended learning outcomes *

After the course, the student should be able to

  • explain the useage of, and the assumptions behind biophysical and biochemical models and methods
  • compute basic biophysical and biochemical entities in stochiometry, ion statics and ion dynamics, diffusion and cell compartments
  • exemplify the usage of continous, stochastic or boolean models
  • explain models for synapes and their plasticity and of networks of neurons
  • use and develop simulation programs for genetic, biochemical, and neural networks

so that the student

  • is able to explain the useage of, and the assumptions behind biological models
  • in the working life can perform biological modeling and simulation work

Course Disposition

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Literature and preparations

Specific prerequisites *

Single course students: 90 university credits including 45 university credits in Mathematics or Information Technology. English B, or equivalent.

Recommended prerequisites

The mandatory courses for D, E, and F in mathematics, numerical analysis and computer science or the equivalent. Recommended the courses: DD2400 Cellular and Molecular Biology and DD2401 Neuroscience or the equivalent.


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Meddelas senast 4 veckor före kursstart på kursens hemsida. Föregående läsår användes D. Johnston & S. Miao-Sin Wu: Fundamentals of cellular neurophysiology, MIT Press.

Examination and completion

Grading scale *

A, B, C, D, E, FX, F

Examination *

  • LAB1 - Laboratory Work, 1.5 credits, Grading scale: P, F
  • PRO2 - Project, 3.0 credits, Grading scale: P, F
  • TEN2 - Examination, 4.5 credits, Grading scale: A, B, C, D, E, FX, F

Based on recommendation from KTH’s coordinator for disabilities, the examiner will decide how to adapt an examination for students with documented disability.

The examiner may apply another examination format when re-examining individual students.

In this course all the regulations of the code of honor at the School of Computer science and Communication apply, see: http://www.kth.se/csc/student/hederskodex/1.17237?l=en_UK.

Other requirements for final grade *

Examination (TEN2; 4,5 university credits).
Laboratory assignments (LAB1; 1,5 university credits). Project assignment (PRO2; 3 university credits.).

Opportunity to complete the requirements via supplementary examination

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Opportunity to raise an approved grade via renewed examination

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Erik Fransén

Arvind Kumar

Further information

Course web

Further information about the course can be found on the Course web at the link below. Information on the Course web will later be moved to this site.

Course web DD2435

Offered by

EECS/Intelligent Systems

Main field of study *

Computer Science and Engineering, Information Technology, Information and Communication Technology

Education cycle *

Second cycle

Add-on studies

Please discuss with the instructor.


Alexander Kozlov (akozlov@kth.se) tel: 070 759 6583; alt - Erik Fransén (erikf@csc.kth.se) tel: 08/790 6902

Ethical approach *

  • All members of a group are responsible for the group's work.
  • In any assessment, every student shall honestly disclose any help received and sources used.
  • In an oral assessment, every student shall be able to present and answer questions about the entire assignment and solution.

Supplementary information

The course overlaps to a large extent with DA7048 and can not be conbined with that course.

In this course, the EECS code of honor applies, see: