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Course module: B-MCOBI17
B-MCOBI17
Master Level Computational Biology
Course info
Course codeB-MCOBI17
ECTS Credits7.5
Category / LevelM (Master)
Course typeCourse
Language of instructionDutch, English
Offered byFaculty of Science; Graduate School of Life Sciences; Graduate School of Life Sciences;
Contact personprof. dr. P. Hogeweg
Telephone+31 30 2533692
E-mailP.Hogeweg@uu.nl
Lecturers
Lecturer
prof. dr. P. Hogeweg
Feedback and availability
Other courses by this lecturer
Contactperson for the course
prof. dr. P. Hogeweg
Other courses by this lecturer
Teaching period
2  (12/11/2018 to 01/02/2019)
Teaching period in which the course begins
2
Time slotBC: See 'Help'
Study mode
Full-time
RemarkSend an e-mail to: p.hogeweg@uu.nl for enrollment.
Enrolment periodfrom 17/09/2018 up to and including 30/09/2018
Course application processadministratie onderwijsinstituut
Enrolling through OSIRISNo
Enrolment open to students taking subsidiary coursesNo
Pre-enrolmentNo
Waiting listNo
Course placement processdocent
Aims
After completing the module the student is able to:
 
  • knows how computational models of dynamical systems can be used to investigate biological processes. (e.g.topics mentioned in 3).
    In particular;• the need of computational models• how to formulate computational models• how to analyze computational models• how to interpret results of computational models
  • knows implicit assumptions of various model formalisms.
    In particular:• ODE and PDE.• FSM and CA• event based models (e.g. Gillespie)• individual (particle) based models• evolutionary models
  • knows basic theory derived from computational modeling of• network dynamics (e.g. cell cycle, cell differentiation).
    In particular:• spatial pattern formation (e.g. spiral and chaotic waves)• multilevel evolution (genome evolution, eco-evolutionary dynamics)• multilevel morphogenesis (from genes, to cells to tissues to organism)
  • able to understand current literature using modeling. In particular• extracting the bottom line• evaluating the explicit and implicit assumptions of the models• relating the discussion to the theoretical knowledge gained in 3
Content
During the course, the emphasis will be on composing and analysing exact models based on specific hypotheses. The results of the analyses offer an understanding of the original biological system. The models studied address fundamental questions from a variety of biological fields, including: 

* Multi-level evolution:
 - pre-biotic evolution
 - eco-evolutionary dynamics and spatial pattern formation
 - genome evolution (e.g. interaction between gene regulation and evolution)
* Developmental dynamics:
 - pattern formations
 - morphogenesis and mechanical interactions between cells
 - evolution and morphogenesis
Immune system dynamics:
 - self/non-self discrimination
 - host-pathogen co-evolution
Behaviour:
 - self-structuring through local interactions
 - interface between learning and evolution
 
A number of different model formalisms are used, namely:
    * (Non-linear) differential/difference equations (ODE and PDE)
    * Cellular automata machines
    * Individually oriented models
    * Evolutionary computation
 
After completion the course, the student: 
  1. knows how computational models of dynamical systems can be used to investigate biological processes. (e.g.  topics mentioned in 3). In particular;
    • the need of computational models
    • how to formulate computational models
    • how to analyze computational models
    • how to interpret results of computational models
  2. knows  implicit assumptions of various model formalisms. In particular:
    • ODE and PDE.
    • FSM and CA
    • event based models (e.g. Gillespie)
    • individual (particle) based models
    • evolutionary models
  3. knows  basic theory derived from computational modeling of
    • network dynamics (e.g. cell cycle, cell differentiation). In particular:
    • spatial pattern formation (e.g. spiral and chaotic waves)
    • multilevel evolution (genome evolution, eco-evolutionary dynamics)
    • multilevel morphogenesis (from genes, to cells to tissues to organism)
  4. able to understand current literature using modeling. In particular
    • extracting the bottom line
    • evaluating the explicit and implicit assumptions of the models
    • relating the discussion to the theoretical knowledge gained in 3.
 
Competencies
-
Entry requirements
You must meet the following requirements
  • Enrolled for a degree programme of faculty Faculty of Science
  • Assigned study entrance permit for the master
Prerequisite knowledge
Modeling requires some knowledge, contact the coordinator. Modeling requires some knowledge.
Required materials
-
Recommended materials
Software
Linux
Instructional formats
Computer practical

Lecture

Seminar

Tests
Final result
Test weight100
Minimum grade-

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Kies de Nederlandse taal