Course details


BIF Acad. year 2021/2022 Summer semester 5 credits

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.


Deputy Guarantor

Language of instruction



Examination (written)

Time span

26 hrs lectures, 12 hrs pc labs, 14 hrs projects

Assessment points

58 exam, 16 mid-term test, 12 labs, 14 projects




Hon Jiří, Ing. (DIFS FIT BUT)
Musil Miloš, Ing. (DIFS FIT BUT)
Puterová Janka, Ing. (DIFS FIT BUT)

Subject specific learning outcomes and competences

Students will be able to take advantages of large biological database and design new efficient algorithms for their analysis.

Generic learning outcomes and competences

Understanding the relations between computers (computing) and selected molecular processes.

Learning objectives

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.

Why is the course taught

Biological data analysis requires a knowledge of basic bioinformatics algorithms and tools (sequence alignment, phylogenetic tree construction, assembling/mapping of sequencing data, etc.). The goal of this course is to provide this information for the students and prepare them for a future profession in the area of bioinformatics.

Study literature

  • 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.

Fundamental literature

  • Supratim Choudhuri: Bioinformatics for Beginners: Genes, Genomes, Molecular Evolution, Databases and Analytical Tools, ISBN: 978-0124104716, Academic Press, 2014
  • 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.

Syllabus of lectures

  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

Syllabus of computer exercises

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

Syllabus - others, projects and individual work of students

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

Progress assessment

Mid-term exam, project, computer lab assignments.

Controlled instruction

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.

Exam prerequisites



Tuelecturelectures A113 13:0014:50 1MIT 2MIT NBIO xx
Thucomp.lablectures N203 08:0009:50 1MIT 2MIT xx

Course inclusion in study plans

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