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DD2435 Mathematical Modelling of Biological Systems 9.0 hp

Course memo Autumn 2022-50098

Version 1 – 09/09/2022, 3:50:05 PM

Course offering

biomod22 (Start date 29/08/2022, English)

Language Of Instruction

English

Offered By

EECS/Intelligent Systems

Course memo Autumn 2022

Course presentation

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

Headings denoted with an asterisk ( * ) is retrieved from the course syllabus version Autumn 2021

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

Learning activities

The course consists of three parts

  • Labs - laboratory works (LAB1)
  • Exam - written examination (TEN2)
  • Project - group project (PRO2)

Detailed plan

Period 1 includes lectures 1-8, written examination based on the material of lectures 1-8 and laboratory works 1, 2 and 4 (or 3 for students after course DD2401 Neuroscience).

Period 2 consists of a reading project (or a small modeling study), as well as lectures 9-10 and laboratory 5. Students following the course DA7048 at SU skip the lectures and the lab.

Exam result, graded A-E, determines the course result provided other parts are completed.

Preparations before course start

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.

Literature

No information inserted

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.

Other requirements for final grade

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

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.

Further information

No information inserted

Round Facts

Start date

29 Aug 2022

Course offering

  • biomod22 Autumn 2022-50098

Language Of Instruction

English

Offered By

EECS/Intelligent Systems

Contacts