PřF:C1472 Applied mathematics for bioche - Course Information
C1472 Applied mathematics for biochemists - seminar
Faculty of ScienceSpring 2021
- Extent and Intensity
- 0/1/0. 1 credit(s) (plus extra credits for completion). Type of Completion: z (credit).
- Teacher(s)
- prof. RNDr. Jaroslav Koča, DrSc. (lecturer)
RNDr. Tomáš Raček, Ph.D. (lecturer)
doc. RNDr. Radka Svobodová, Ph.D. (lecturer)
Mgr. Zdeněk Kříž, Ph.D. (lecturer) - Guaranteed by
- prof. RNDr. Jaroslav Koča, DrSc.
National Centre for Biomolecular Research – Faculty of Science
Supplier department: National Centre for Biomolecular Research – Faculty of Science - Timetable
- Mon 1. 3. to Fri 14. 5. Thu 17:00–17:50 online_BCH1
- Prerequisites (in Czech)
- NOW( C1471 Applied mathematics for biochemists )
- 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
- Applied biochemistry (programme PřF, B-BIC)
- Biochemistry (programme PřF, B-BIC)
- Bioinformatics (programme PřF, B-BIC)
- Course objectives
- The aim of this course is to introduce the methods and approaches for solving the most common computational problems in chemistry, biochemistry and, more generally, in life sciences.
- Learning outcomes
- At the end of the course student will be able to describe and apply basic numerical methods on life science problems as well as evaluate their limits on particular examples.
- Syllabus
- 1. Problems of floating point representation of real numbers.
- 2. Solution to linear systems (GEM drawbacks, LU decomposition, least squares method).
- 3. Vector algebra. Transformation of coordinates. Molecular modelling applications.
- 4. Dimensionality reduction and visualization of multidimensional data. Cluster analysis.
- 5. Random numbers a their generation. Monte Carlo methods.
- 6. Functions of two variables. Local extremes.
- 7. Numerical differentiation and integration.
- 8. Integration of functions of two variables, applications.
- 9. Introduction to optimization. Molecular geometry optimization.
- 10. Parameterization of computational methods in chemistry. Local vs. global optimization methods.
- 11. Differential equations and their application in chemistry.
- 12. Differential equations in molecular mechanics (analytical and numerical approaches).
- Literature
- Teaching methods
- Practical exercises.
- Assessment methods
- Continuous assessment.
- Language of instruction
- Czech
- Further Comments
- Study Materials
The course is taught annually. - Listed among pre-requisites of other courses
- Enrolment Statistics (Spring 2021, recent)
- Permalink: https://is.muni.cz/course/sci/spring2021/C1472