IV129 Sybila Laboratory

Faculty of Informatics
Spring 2022
Extent and Intensity
0/0/2. 2 credit(s). Type of Completion: z (credit).
Teacher(s)
doc. RNDr. David Šafránek, Ph.D. (lecturer)
prof. RNDr. Luboš Brim, CSc. (lecturer)
Guaranteed by
doc. RNDr. David Šafránek, Ph.D.
Department of Machine Learning and Data Processing – Faculty of Informatics
Supplier department: Department of Machine Learning and Data Processing – Faculty of Informatics
Prerequisites
SOUHLAS
Applicants should 1) be able to work independently 2) have interest in long-term projects (several semesters) 3) have working knowledge of English 4) be able to work in a team. The enrollment must be approved by one of the laboratory researchers (L. Brim, D. Šafránek).
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
On successful completion of the course students - will have practical experience with active research - should be able to read and understand scientific papers - should be able to employ gathered information to formulate and prove their own hypotheses within the relevant context - should be able to present the research results in English.
Learning outcomes
After the course the student will be able:
- to analyse and discuss pros and cons of computational methods in systems biology;
- to contrast conceptual errors in analysed publications by employing suitable arguments;
- to judge ideas and opinions in front of students and professionals.
Syllabus
  • Sybila Laboratory is a team project focused on the development of methods and tools for the design and analysis of biological systems and their experimental application. Students meet regularly with senior researchers to discuss research problems related to their research topics. Students are expected to regularly present state-of-the-art results in the relevant fields at the laboratory seminar.
Teaching methods
team research projects
Assessment methods
Students are evaluated according their performance on assigned projects.
Language of instruction
Czech
Further Comments
Study Materials
The course is taught each semester.
The course is taught: every week.
Teacher's information
http://sybila.fi.muni.cz
The course is also listed under the following terms Autumn 2017, Spring 2018, Autumn 2018, Spring 2019, Autumn 2019, Spring 2020, Autumn 2020, Spring 2021, Autumn 2021, Autumn 2022, Spring 2023, Autumn 2023, Spring 2024, Autumn 2024, Spring 2025.
  • Enrolment Statistics (Spring 2022, recent)
  • Permalink: https://is.muni.cz/course/fi/spring2022/IV129