Bi3443 Optimalisation in Computational Biology

Faculty of Science
Spring 2009
Extent and Intensity
2/0/0. 2 credit(s) (plus extra credits for completion). Type of Completion: zk (examination).
Teacher(s)
prof. Ing. Jiří Holčík, CSc. (lecturer)
Guaranteed by
prof. RNDr. Ladislav Dušek, Ph.D.
RECETOX – Faculty of Science
Contact Person: prof. Ing. Jiří Holčík, CSc.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
Course objectives
The course will provide students with basic facts about optimizing methods and algorithms for the cases of continuous and discrete objective functions used in solving optimizing problems in biology and medicine. At the end of the course students should be able to understand, apply, and design, resp. conventient optimizing method for solving their practical tasks.
Syllabus
  • 1. Basic terms. Unconstrained and constrained optimizing algorithms. 2. Structure of optimizing methods. Ad hoc methods. Properties of optimizing algorithms. 3. Gradient methods. Method of deepest descent and its properties. 4. Newton's method. Quasi-Newton methods. 5. Conjugate optimizing methods. 6. Linear programming. Simplex method. 7. Linear programming. Non-simplex methods. 8. Combinatorial optimization. Simulated Annealing. 9. Stochastic optimization. 10. Genetic algorithms. 11. Artificial neural networks in optimization. 12. Hierarchical and multicriterial optimization.
Literature
  • Pardalos,P.M., Resende,M.G.C.: Handbook of Applied Optimization. New York, Oxford Univ. Press 2002.
  • Fletcher,R. Practical Methods of Optimization. (2nd Edition), Chichester, J.Wiley&Sons 2003
  • Chong,E.K.P, Zak,S.H.: An Introduction to Optimization. New York, J.Wiley & Sons 2001
Assessment methods
oral examination
Language of instruction
Czech
Further Comments
The course is taught annually.
The course is taught: every week.

  • Enrolment Statistics (recent)
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