FI:IV108 Bionformatics II - Course Information
IV108 Bionformatics II
Faculty of InformaticsAutumn 2017
- 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
- doc. RNDr. Aleš Horák, 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
- Tue 10:00–11:50 B116
- 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
- there are 48 fields of study the course is directly associated with, display
- 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 and processing sequencing data - Syllabus
- Algorithms for sequence analysis
- Algorithms for prediction and analysis of structural data
- Biological language
- Next-generation DNA sequencing methods and data processing
- Understanding protein cleavage and mass spectra
- Expression profile and promoter analysis
- Literature
- Teaching methods
- lectures and exercises
- Assessment methods
- Bonus exercices, final exam.
- Language of instruction
- Czech
- Follow-Up Courses
- Further Comments
- The course is taught annually.
- Teacher's information
- http://www.fi.muni.cz/~lexa/teaching.html
- Enrolment Statistics (Autumn 2017, recent)
- Permalink: https://is.muni.cz/course/fi/autumn2017/IV108