Course detail

Bioinformatics

FIT-IV108Acad. year: 2021/2022

An advanced course in bioinformatics (lecture and computer lab) building upon elementary mol.biology and/or bioinformatics courses.

State doctoral exam - topics:

  1. Searching in biological sequences (types of searches, principles, and applications)
  2. Comparison of biological sequences (pairwise and multiple sequence alignment and their applications)
  3. Genomes, their structure, and DNA sequence analysis
  4. Analysis and prediction of RNA structure
  5. DNA sequencing technologies (principles and applications)
  6. Structure and function of proteins
  7. Protein sequence analysis (domain detection, structure prediction, analysis of correlated mutations)
  8. Special DNA structures (triplex, quadruplex), repetitive and mobile DNA, the human genome
  9. Biological and bioinformatics databases (e.g., GenBank, UniProt, RefSeq, PDB, Gene ontology)
  10. Computational tools (e.g., BLAST, BLAT, RF/Bioconductor, Biomart, genomic browsers) and data formats (e.g., FASTA, FASTQ, SAM, VCF, GFF3, PDB) used in molecular biology and bioinformatics

Language of instruction

Czech

Number of ECTS credits

0

Mode of study

Not applicable.

Guarantor

Ing. Matej Lexa, Ph.D.

Department

Faculty of Informatics MU (FI MU)

Learning outcomes of the course unit

At the end of the course, the students will:
  • understand the inner workings of selected algorithms, their advantages and disadvanteges, including knowledge of recent alternatives
  • be able to work with 3-D models of molecules
  • be able to evaluate or design methods for solving current problems in bioinformatics
  • understand the principles of existing DNA sequencing methods and processing sequencing data

Prerequisites

Not applicable.

Co-requisites

Not applicable.

Planned learning activities and teaching methods

Not applicable.

Assesment methods and criteria linked to learning outcomes

Not applicable.

Course curriculum

Not applicable.

Work placements

Not applicable.

Aims

Introduction to selected algorithms and methods of analysis used in bioinformatics.

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

Continouous solving exercices, final exam, min 50 points.

Recommended optional programme components

Not applicable.

Prerequisites and corequisites

Not applicable.

Basic literature

Not applicable.

Recommended reading

Jones N.C., Pevzner P.: An introduction to algorithms in bioinformatics. MIT Press, 2004, ISBN 978-0262101066
BROWN, Stuart M. Next-generation DNA sequencing informatics. Second edition. Cold Spring Harbor, New York: Cold Spring Harbor Laboratory Press, [2015]. ISBN 978-1621821236.
Xinkun Wang, Next-Generation Sequencing Data Analysis, ISBN: 978-1482217889, CRC Press, 2016.
Zvelebil M., Baum J.: Understanding bioinformatics. Garland Science, London, 2007 ISBN 978-0815340249.

Classification of course in study plans

  • Programme VTI-DR-4 Doctoral

    branch DVI4 , any year of study, winter semester, elective

  • Programme VTI-DR-4 Doctoral

    branch DVI4 , any year of study, winter semester, elective

  • Programme VTI-DR-4 Doctoral

    branch DVI4 , any year of study, winter semester, elective

  • Programme VTI-DR-4 Doctoral

    branch DVI4 , any year of study, winter semester, elective

  • Programme DIT Doctoral, any year of study, winter semester, compulsory-optional
  • Programme DIT-EN Doctoral, any year of study, winter semester, compulsory-optional
  • Programme DIT-EN Doctoral, any year of study, winter semester, compulsory-optional
  • Programme DIT Doctoral, any year of study, winter semester, compulsory-optional

Type of course unit

 

Lecture

13 hours, optionally

Teacher / Lecturer

Ing. Matej Lexa, Ph.D.

Syllabus

  1. Biological language (sequence segmentation, information-statistical analysis of biological sequences)
  2. Pattern matching (algorithms based on filtration and suffix arrays)
  3. Heuristic algorithms for similarity searching in biological sequences (BLAST, BLAT, Pattern Hunter)
  4. Regular expressions in bioinformatics
  5. Algorithms for analysis and prediction of structural data (secondary structure, contacts inb proteins, domain identification)
  6. Algorithms for analysis and prediction of structural data (3D structure, structural comparisons)
  7. Working with molecular structures in Pymol
  8. New methods of DNA sequencing
  9. Genome assembly and other operations on short nucleic acid sequences
  10. Prediction of melting temperature in DNA and other nucleic acids (program mfold)
  11. RNA secondary structure
  12. DNA computing
  13. Comparative genomics of human (analysis of scientific papers)

Guided consultation in combined form of studies

26 hours, optionally

Teacher / Lecturer

Ing. Matej Lexa, Ph.D.

Fundamentals seminar

13 hours, compulsory

Teacher / Lecturer

Ing. Matej Lexa, Ph.D.