Course details

Bioinformatics

IV108 Acad. year 2020/2021 Winter semester

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


Guarantor

Lexa Matej, Ing., Ph.D. (FI MUNI)

Language of instruction

Czech

Completion

Examination (oral)

Time span

13 hrs lectures, 13 hrs exercises

Assessment points

100 exam

Lecturer

Lexa Matej, Ing., Ph.D. (FI MUNI)

Subject specific learning outcomes and competences

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

Learning objectives

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

Study literature

  • BROWN, Stuart M. Next-generation DNA sequencing informatics. Second edition. Cold Spring Harbor, New York: Cold Spring Harbor Laboratory Press, [2015]. ISBN 978-1621821236.

Fundamental literature

  • Jones N.C., Pevzner P.: An introduction to algorithms in bioinformatics. MIT Press, 2004, ISBN 978-0262101066
  • 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.

Syllabus of lectures

  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)

Controlled instruction

Continouous solving exercices, final exam, min 50 points.

Course inclusion in study plans

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