PřF:E4014 Project of Comp Biol - BB - Course Information
E4014 Project of the Computational Biology - Biomedical Bioinformatics
Faculty of ScienceAutumn 2024
- Extent and Intensity
- 0/3/0. 3 credit(s) (plus extra credits for completion). Type of Completion: z (credit).
In-person direct teaching - Teacher(s)
- Mgr. Eva Budinská, Ph.D. (lecturer)
doc. Ing. Matej Lexa, Ph.D. (lecturer)
Ing. Vojtěch Bartoň (seminar tutor)
Mgr. Pavla Holochová, Ph.D. (lecturer) - Guaranteed by
- Mgr. Eva Budinská, Ph.D.
RECETOX – Faculty of Science
Contact Person: Mgr. Eva Budinská, Ph.D.
Supplier department: RECETOX – Faculty of Science - Timetable
- Mon 10:00–12:50 D29/347-RCX2
- Prerequisites
- None, it is a basic course.
- Course Enrolment Limitations
- The course is only offered to the students of the study fields the course is directly associated with.
- fields of study / plans the course is directly associated with
- Biomedical bioinformatics (programme PřF, N-MBB)
- Course objectives
- Students in this course work in two to four-person groups and solve problems in experimental data processing, analysis and modelling. In addition to solving the problem itself, the students practically learn the principles of teamwork.
- Learning outcomes
- After completing the course, student will be able to:
- review the scientific area related to the assigned task;
- use selected tools and methods to solve the assigned task;
- present the level of completion of the assigned task;
- cooperate in teams. - Syllabus
- Presentation of project assignments by teachers.
- Division of students into two-person or three-person investigator teams.
- Continuous teamwork and consultations with the project sponsors.
- Presentation of the project state in three phases by the investigator teams.
- Literature
- BUDINSKÁ, Eva, Zbyněk BORTLÍČEK and Ladislav DUŠEK. Současné trendy v analýze genomických dat (Current trends in genomic data analysis). Lékař a technika. 2011, vol. 2011. ISSN 0301-5491. info
- BUDINSKA, Eva and Zbyněk BORTLÍČEK. E-learning in genomic and proteomic data analysis. 2009. URL info
- Teaching methods
- teamwork, presentations, consultations, discussions between the teams
- Assessment methods
- Two interim presentations and a final presentation of the resolved data analysis problem
- Language of instruction
- Czech
- Further Comments
- Study Materials
The course is taught annually.
- Enrolment Statistics (recent)
- Permalink: https://is.muni.cz/course/sci/autumn2024/E4014