Mathematical Biology – Field of study catalogue MU
“Analytical thinking, work and discoveries”
Computational Biology is a scientific field focusing on the application of mathematical and analytical approaches in biological and medical research. The study of computational biology is a chance for all those interested in biology as well as mathematics and computer skills.
The studies lead to the knowledge and understanding of biology, applied mathematics and computer science with a primary focus on mathematical analysis of biological and biomedical problems. Graduates become familiar with all fundamental biological disciplines, as well as mathematical methods (statistics, mathematical modelling, data analysis) and information technology utilisable in applied research. The practical part of the studies focuses on the application of mathematical methods and information technologies in solving specific problems. Students will be qualified in three main areas according to the specialization of their Bachelor's thesis and according to their choice of elective courses:
1) processing and analysis of biological, genomic and proteomic data
2) processing, analysis and modelling of clinical, physiological and epidemiological data
3) processing, analysis and modelling of environmental data
After successfully completing his/her studies the graduate is able to:
- understand fundamental theoretical and methodological principles of biology and mathematics
- solve a given problem regarding biological, medical or environmental data analysis and define specific sub-tasks within the solution
- search for the state of the art of the given problem in the Czech as well as foreign literature
- select appropriate mathematical methods for solving the given problem
- select and apply software tools for the chosen mathematical methods available under the specified conditions
- draw conclusions from the results of a mathematical solution to the given problem
Graduates of the Computational Biology study programme can find employment in the processing and analysis of biological, medical and environmental data in both academic and commercial sectors (research, medical departments, pharmacology, health care, environmental protection, agriculture and forestry). They can also work in the management of clinical studies or in other fields concerning data management and administration.
The standard duration of the studies is six semesters. To be admitted to the final state examination, students must obtain a total of 180 ECTS credits and defend their Bachelor's thesis.
Exceptions to this rule are students of Bachelor's study programme, double-subject, who are awarded max. 158 ECTS credits for required and selective courses and max. 171 ECTS credits for required, selective and recommended courses and elective courses from the broader scientific field.
During the course of their studies, students should follow the Course Catalogue for their year of matriculation. They can access the Course Catalogues through the faculty website.
The final state examination consists of the oral defence of the Bachelor's thesis and written exams in Biology and Mathematics.
Final examination topics in Biology are: 1) General Biology: basic principles of the structure and functioning of living systems, structural components of cells, organs and organ systems, cell cycle, transport and metabolic processes within cells and organs, basic principles of genetics, plant organs, major organ systems of animals 2) Ecology: terminology, environmental factors, organisms and their environment, populations, communities and ecosystems, basic biomes of the Earth, applied ecology
Final examination topics in Mathematics are: Linear Algebra and Geometry, Mathematical Analysis, Probability and Statistics, Signals and Systems.
After the successful completion of the Bachelor's study programme, students can apply for admission to the follow-up Master's study programme in Computational Biology that focuses on closer specialization and deepening of the knowledge in a certain biological, mathematical or computer science field according to the student's specialization.