NFYA09016U Biological Networks (BioNet)

Volume 2014/2015
Education
BSc Programme in Physics
Content

The purpose of this course is to give the student a basic understanding of life as a physical system. A system that can be modeled in much the same way as other physics systems, with the additional complications that a living system is build of many different parts. Parts which are put together in a network by the historical process of evolution. Emphasis is put on modeling, with the aim to teach the students how to construct and analyze dynamic models.
The course is an introduction to physics of living systems. It deals with modeling of biological networks, from both a functional and an evolutionary perspective. Topics include basic concepts from molecular biology, physics of gene regulation, models for decision processes inside cells, bi-stability in genetic systems, response dynamics, oscillations, networks, and evolution on both microscopic and macroscopic scale

Learning Outcome

 

Skills

 

  • Understand the central dogma, DNA-->RNA-->Proteins and will be able to write equations and algorithms associated to each of the steps. Such models involves stochastic molecular events and knowledge of timescales associated to basic processes inside a living cell.
  • Understand how the same genome can give rise to widely different genetic activity. Such epigenetics is an important part of life-death decisions in the microbial world, as well as for the development of multicellularity.
  • Understand principles for gene regulation, meaning that the central dogma is supplemented with numerous back-arrows. An important part of being alive is feedback, and the student should know about feedback associated to both metabolism, and feedback associated to stress.
  • Understand and model shock responses and conditions for obtaining oscillations inside living cells. This include feedback from stress to the regulation of proteins that counteracts the stress.
  • Understand networks, and what makes networks relevant for dealing with biological systems. This include both transcription regulatory networks, and their coupling to the production line networks of metabolism.
  • Know about evolution in terms of models for how it could have formed the living world. In particular to know about models for evolving molecular networks inside an evolving species, as well as a minimal model for co-evolving animal species.
  • Knowledge about tools to construct quantitative models for living systems, and thereby increase the students intuition about modeling as a scientific method.

Knowledge
The student will obtain knowledge about networks and information processing in living systems, including physics of gene regulation, dynamics on biological networks and dynamics of evolution. The gained understanding will center around the following fundamental equations and algorithms:

  • Monods Growth law
  • gene activity as function of protein regulatory input
  • time for a protein to find specific site in a cell
  • event driven simulation for gene expression
  • equations for bi-stability using positive feedback
  • equations for metabolic fluxes and their regulation
  • equations for signal spreading and robustness in sbstract networks
  • equation for push-pull reactions in signalling cascades
  • equation for adaptive responses
  • agent based simulation of excitable media
  • agent based model for punctuated co-evolution of life

Competences
This course makes the student able to adapt knowledge from both introductory biophysics and cellbiology into a new, specialized topic, the physics of life viewed as biological network.
The course gives the student competencies to make and evaluate dynamical models, a useful tool in this topic, but which also has applications in other branches of physics and science in general.

Kim Sneppen: "Models of Life: Dynamics and Regulation in Biological Systems"

Notes available at the homepage: cmol.nbi.dk/kursus/

Lectures and exercise sessions
  • Category
  • Hours
  • Exam
  • 0,5
  • Lectures
  • 28
  • Practical exercises
  • 28
  • Theory exercises
  • 149,5
  • Total
  • 206,0
Credit
7,5 ECTS
Type of assessment
Oral examination, 25 min
No preparation time
Aid
Without aids
Marking scale
7-point grading scale
Censorship form
No external censorship
Several internal examiners
Criteria for exam assesment

See "learning outcome"