IV121 Computer science applications in biology

Faculty of Informatics
Spring 2021
Extent and Intensity
2/1. 3 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)
doc. Mgr. Bc. Vít Nováček, PhD (lecturer)
doc. RNDr. David Šafránek, 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
Thu 14:00–16:50 Virtuální místnost
Prerequisites
The course has no specific initial requirements. The goal is to inform students and young researchers of life sciences about several opportunities to apply computer scientific techniques in their field.
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
The main aim of the course is to bridge the gaps between computer science and life sciences by presenting the selected theoretical problems solved in computer science After absolving the course students should be able to:
understand selected parts of computer science that make a tool for life sciences;
get a comprehensive overview of computational tools and techniques relevant for life sciences;
get basic knowledge of selected software tools (ability to execute programs and to use their elementary features).
Learning outcomes
After absolving the course students should be able to:
define the contribution of computer science for biology and biomedicine;
associate relevant tools and techniques with selected set of biological problems;
use selected tools at basic level and apply them to simple models.
Syllabus
  • 1. Introduction to bioinformatics and systems biology
  • 2. Qualitative models and their analysis
  • 3. Quantitative models and their analysis
  • 4. Network-based representation of information
  • 5. Data mining from literature
  • 6. Data integration
  • 7. Applications of artificial intelligence and machine learning techniques
  • 8. 3D geometry, CSG
Literature
  • KLIPP, Edda. Systems biology in practice : concepts, implementation and application. Weinheim: Wiley-Vch, 2005, xix, 465. ISBN 3527310789. info
Teaching methods
Several thematic blocks, each consisting of a lecture and a hands-on session related to one or relevant two software tools.
Assessment methods
A written exam showing the knowledge obtained.
Language of instruction
Czech
Further comments (probably available only in Czech)
Study Materials
The course is taught once in two years.
The course is also listed under the following terms Spring 2012, Spring 2013, Spring 2014, Spring 2016, Spring 2018.
  • Enrolment Statistics (recent)
  • Permalink: https://is.muni.cz/course/fi/spring2021/IV121