PřF:E4014 Project of Comp Biol - BB - Course Information

E4014 Project of the Computational Biology - Biomedical Bioinformatics

Extent and Intensity

0/3/0. 3 credit(s) (plus extra credits for completion). Type of Completion: z (credit).

Teacher(s)

Mgr. Eva Budinská, Ph.D. (lecturer)
doc. Ing. Matej Lexa, Ph.D. (lecturer)
doc. Mgr. Natália Martínková, Ph.D. (lecturer)
Ing. Vojtěch Bartoň (seminar tutor)
Mgr. Jan Böhm (seminar tutor)

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 (Autumn 2023, recent)
  
• Permalink: https://is.muni.cz/course/sci/autumn2023/E4014