Course detail


FIT-BIFAcad. year: 2018/2019

This course introduces students to basic principles of molecular biology, present algorithms pro biological data analysis, describes their time complexity and shows direction how to design the new methods very effectively. Particularly, the following algorithms will be discussed: methods for sequence alignment, evolutionary models, construction of phylogenetic trees, algorithms for gene identification using machine learning and approaches for prediction of 2D and 3D protein structure. Lectures will be supplement with practical examples using available biological databases.

Learning outcomes of the course unit

Students will be able to take advantages of large biological database and design new efficient algorithms for their analysis.
Understanding the relations between computers (computing) and selected molecular processes.


Not applicable.


Not applicable.

Recommended optional programme components

Not applicable.

Recommended or required reading

Jacques Cohen: Bioinformatics - An introduction for Computer Scientists, ACM Computing Surveys, 2004, Vol. 36, No. 2, p. 122-158.
Jean-Michel Claverie, Cedric Notredame: Bioinformatics for Dummies, ISBN: 0-7645-1696-5, Wiley Publishing, Inc., 2003.
Yi-Ping Phoebe Chen: Bioinformatics Technologies, ISBN: 3540208739, Springer, 2005.
Alberts, Bray, Johnson, Lewis, Raff, Roberts, Walter: Základy buněčné biologie, ISBN: 80-902906-0-4, Espero Publishing, 1998.
Dan K. Krane, Michael L. Raymer: Fundamental Concepts of Bioinformatics, ISBN: 0-8053-4633-3, Benjamin Cummings 2003.
Neil C. Jones, Pavel A. Pevzner: An Introduction to Bioinformatics Algorithms, ISBN: 0262101068, MIT Press, 2004.
Andreas D. Baxevanis, B. F. Francis Ouellette: Bioinformatics: A Practical Guide to the Analysis of Genes and Proteins, ISBN: 0-471-47878-4, Wiley-Interscience, 2005.

Planned learning activities and teaching methods

Not applicable.

Assesment methods and criteria linked to learning outcomes

Mid-term exam, project, computer lab assignments.
Exam prerequisites:

Language of instruction


Work placements

Not applicable.


To understand the principles of molecular biology. To perceive the basic used algorithms and to well informed about relevant biological databases. To be able to design new effective methods for biological data analysis.

Specification of controlled education, way of implementation and compensation for absences

Presence in any form of instruction is not compulsory. An absence (and hence loss of points) can be compensated in the following ways: 

  1. presence in another laboratory group dealing with the same task. 
  2. showing a summary of results to the tutor at the next lab. 
  3. sending a short report (summarizing the results of the missed lab and answering the questions from the assignment) to the tutor, in 14 days after the missed lab.

Classification of course in study plans

  • Programme IT-MGR-2 Master's

    branch MPV , any year of study, summer semester, 5 credits, elective
    branch MGM , any year of study, summer semester, 5 credits, elective
    branch MSK , any year of study, summer semester, 5 credits, elective
    branch MIS , any year of study, summer semester, 5 credits, elective
    branch MBS , any year of study, summer semester, 5 credits, elective
    branch MIN , any year of study, summer semester, 5 credits, elective
    branch MMM , any year of study, summer semester, 5 credits, elective
    branch MBI , 1. year of study, summer semester, 5 credits, compulsory

Type of course unit



26 hours, optionally

Teacher / Lecturer


  1. Introduction to bioinformatics
  2. Basis of molecular biology
  3. Tools of molecular biology
  4. Biological databases
  5. Sequence alignment, dynamic programing, BLAST, FASTA
  6. Evolutionary models
  7. Construction of phylogenetic trees
  8. DNA assembling
  9. Genomics and gene searching
  10. Proteins and their prediction
  11. Computation of RNA secondary structure
  12. Proteomics, regulatory networks
  13. Polymorphism of genes

Exercise in computer lab

12 hours, compulsory

Teacher / Lecturer


  1. Biological databases
  2. Analysis of genome sequences
  3. Sequence alignment
  4. Phylogenetic trees
  5. Gene prediction
  6. Protein structure analysis


14 hours, compulsory

Teacher / Lecturer


A project will be assigned to each student. Implementation, presentation and documentation of the project will be evaluated.