IV107 Bioinformatics I

Faculty of Informatics
Autumn 2019
Extent and Intensity
2/1/0. 2 credit(s) (plus extra credits for completion). Type of Completion: zk (examination).
Teacher(s)
doc. Ing. Matej Lexa, Ph.D. (lecturer)
Guaranteed by
doc. Ing. Matej Lexa, Ph.D.
Department of Machine Learning and Data Processing – Faculty of Informatics
Supplier department: Department of Machine Learning and Data Processing – Faculty of Informatics
Timetable
Mon 16:00–18:50 B410
Prerequisites
This is an entry course into the area of bioinformatics for students of non-biological disciplines, there are no prerequisites.
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
This course will lead the students into the fascinating world of molecules, genes and proteins. Currently, bioinformatics is going through a period of unusual growth. Abilities to think and act as a bioinformatician (to work with large biological datasets using modern computer science methods) are needed in many areas of science and applied disciplines, especially biology, medicine and chemistry.
Learning outcomes
After taking the course, the students will understand basic principles of molecular biology; they will be familiar with important biological problems that can be best handled by computers; they will understand and be able to choose basic computational methods for handling molecular data.
Syllabus
  • The history and subject of bioinformatics
  • Basics of molecular biology
  • Organization of living matter
  • DNA structure and function
  • Protein structure and function
  • Evolution of genes and proteins
  • Bioinformatic data
  • Data sources
  • Common data types
  • Public sequence data and their accessibility
  • DNA sequence analysis
  • Computer exercises: Data sources, similarity search, visualization of molecules
  • Protein sequence analysis
  • Structural and functional data
  • Similarity searches and scoring
  • Other types of data and their analysis
  • Expression data
  • Protein digests and mass spectra
  • Literature data analysis
Literature
  • ZVELEBIL, Marketa J. and Jeremy O. BAUM. Understanding bioinformatics. New York, N.Y.: Garland Science, 2008, xxiii, 772. ISBN 9780815340249. info
  • Fundamental concepts of bioinformatics. Edited by Dane E. Krane - Micheal L. Raymer. [1st ed.]. San Francisco: Benjamin Cummings, 2003, xiii, 314. ISBN 0-8053-4633-3. info
Teaching methods
lectures, computer exercises
Assessment methods
midterm test, final exam (both written)
Language of instruction
Czech
Follow-Up Courses
Further Comments
Study Materials
The course is taught annually.
Teacher's information
http://www.fi.muni.cz/~lexa/iv107.html
The course is also listed under the following terms Spring 2005, Spring 2006, Spring 2007, Spring 2008, Spring 2009, Spring 2010, Spring 2011, Spring 2012, Autumn 2012, Autumn 2013, Autumn 2014, Autumn 2015, Autumn 2016, Autumn 2017, Autumn 2018, Autumn 2020, Autumn 2021, Autumn 2022, Autumn 2023, Autumn 2024.
  • Enrolment Statistics (Autumn 2019, recent)
  • Permalink: https://is.muni.cz/course/fi/autumn2019/IV107