IV108 Bionformatics II

Faculty of Informatics
Autumn 2009
Extent and Intensity
1/1/0. 2 credit(s) (plus extra credits for completion). Recommended Type of Completion: zk (examination). Other types of completion: k (colloquium).
Teacher(s)
doc. Ing. Matej Lexa, Ph.D. (lecturer)
Guaranteed by
prof. Ing. Václav Přenosil, CSc.
Department of Machine Learning and Data Processing – Faculty of Informatics
Timetable
Tue 8:00–8:50 B411, Tue 9:00–9:50 B117
Prerequisites
IV107 Bioinformatics I or consent of the teacher (not needed for biology students).
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
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
Syllabus
  • Algorithms for sequence analysis
  • Algorithms for prediction and analysis of structural data
  • Biological language
  • Next-generation DNA sequencing methods
  • Understanding protein cleavage and mass spectra
  • Expression profile and promoter analysis
Literature
  • ZVELEBIL, Marketa J. and Jeremy O. BAUM. Understanding bioinformatics. New York, N.Y.: Garland Science, 2008, xxiii, 772. ISBN 9780815340249. info
  • JONES, Neil C. and Pavel PEVZNER. An introduction to bioinformatics algorithms. Cambridge, Mass.: MIT Press, 2004, xviii, 435. ISBN 0262101068. info
Teaching methods
lectures and exercises
Assessment methods
Bonus exercices, final exam.
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/teaching.html
The course is also listed under the following terms Autumn 2004, Autumn 2005, Autumn 2006, Autumn 2007, Autumn 2008, Autumn 2010, Autumn 2011, Autumn 2012, Autumn 2013, Autumn 2014, Autumn 2015, Autumn 2016, Autumn 2017, Autumn 2018, Autumn 2019, Autumn 2020, Autumn 2021, Autumn 2022, Autumn 2023, Autumn 2024.
  • Enrolment Statistics (Autumn 2009, recent)
  • Permalink: https://is.muni.cz/course/fi/autumn2009/IV108