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Cursus: B-B3COMB10
B-B3COMB10
Computationele biologie
Cursus informatie
CursuscodeB-B3COMB10
Studiepunten (EC)7,5
Cursusdoelen
Computational Biology uses computer modeling to investigate biological problems. The course teaches a variety of modeling techniques and techniques to analyse the model behaviour. Moreover, biological theory obtained by computational modeling is examined.
Inhoud
Deze cursus wordt gegeven in het Engels.

Ingangseisen
Verplichte voorkennis is de eerstejaars cursus Systeembiologie. Sterk aanbevolen wordt om voorafgaand aan de cursus de niveau 2 cursus Theoretische ecologie te volgen. Studenten met vergelijkbare kennis kunnen ook toegelaten worden.
 
Studiepad
De cursus Computationele biologie bied je een sterke theoretische ondersteuning in de Moleculaire en Ecologische richtingen.
 
Inhoud
During the course, the emphasis will be on composing exact models, based on specific hypotheses. The models are analyzed, the results yielding insights in the original biological system. The models that are studied address fundamental questions from a variety of biological fields, among which:

Evolutionary dynamics
  • eco-evolutionary dynamics and spatial pattern formation,
  • host-pathogen co-evolution,
  • genome evolution, e.g. interaction between gene regulation and evolution,
  • evolution of complexity, robustness and evolvability.
Developmental dynamics (from genes to organisms) (plant and animal models will be used)
  • pattern formation,
  • cell differentiation,
  • morphogenesis and mechanical interactions between cells,
  • EVO-DEVO (evolution of development).
Network dynamics)
  • gene regulation and metabolic networks,
  • RNA interference.
Behaviour
  • behavioral self-structuring through local interactions,
  • interface between learning and evolution.
 (Spatial) pattern formation and emergent properties are common themes emphasised in all these areas and the related general theory is introduced as a separate module.
A number of different model formalisms are used, namely:
  • non-linear differential/difference equations (ODE and MAPs),
  • reaction Diffusion Systems (PDE),
  • Cellular automata machines,
  • event based models,
  • individually oriented models,
  • evolutionary computation,
  • hybrid models using several combinations of the above formalisms.
 Analysis tools include bifurcation analysis, sensitivity analysis, and various pattern analysis techniques.
 
Werkvormen
A typical day starts with lectures, followed by computational modeling excercises, including a miniproject, about which a report is to be writen. iterature will be handed out related to the computer excercises , and at the end of the course, literature seminars are given by the students.
 
Toetsing
The student's final mark is based on primarily the written exam; and rounded off based on the literature seminar and the miniproject report
 
Studiemateriaal
  • Practicum handleidingen, sheets en literatuur,
  • Op de computers maak je gebruik van LINUX.
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