Mathematical foundations of population genetics
Course: Applied Mathematics
Structural unit: Faculty of Computer Science and Cybernetics
            Title
        
        
            Mathematical foundations of population genetics 
        
    
            Code
        
        
            ДВС.3.03
        
    
            Module type 
        
        
            Вибіркова дисципліна для ОП
        
    
            Educational cycle
        
        
            First
        
    
            Year of study when the component is delivered
        
        
            2022/2023
        
    
            Semester/trimester when the component is delivered
        
        
            7 Semester
        
    
            Number of ECTS credits allocated
        
        
            3
        
    
            Learning outcomes
        
        
            LO 3. Formalize problem sets up in the language of a particular subject area; define their mathematical
formulation and choose a rational problem-solving approach; solve the obtained problems with analytical and numerical methods, evaluate the accuracy and reliability of the results obtained.
PLO 22.3. Understand the main areas of mathematical logic, theory of algorithms and computational theory, programming theory, probability theory and mathematical statistics;
PLO 23.3. Be able to use professional knowledge, skills and abilities in the field of fundamental sections of mathematics and computer science for research of real processes of different nature;
        
    
            Form of study
        
        
            Full-time form
        
    
            Prerequisites and co-requisites
        
        
            To successfully learn the discipline "Mathematical foundations of population genetics" the student should satisfy the following requirements.
They know fundamental bases of mathematical methods of construction, verification, analysis of qualitative characteristics of deterministic and stochastic mathematical models; classical methods of mathematical analysis, probability theory, random processes.
They can conduct research on the qualitative characteristics of the constructed mathematical models; apply classical methods for the study of applied problems in deterministic and stochastic models.
They should be able to apply classical methods of mathematical analysis and probability theory; search and analyze information in open sources.
        
    
            Course content
        
        
            The purpose of the discipline is to get acquainted with the main applications of probabilistic ideas in systems studied in genetics, as well as to master the technical apparatus inherent in this field of knowledge. "Mathematical foundations of population genetics" is the basis for studying the discipline "Environmental and economic processes and their modeling".
        
    
            Recommended or required reading and other learning resources/tools
        
        
            4. Durrett, Richard. Probability models for DNA sequence evolution. Springer, 2008. 
5. Berestycki, Nathanaël. "Recent progress in coalescent theory." Ensaios Matematicos 16 (2009): 1-193. 
6. B.V. Dovgay. Matematichní osnovi genetiki populyatsíy: Yelektronniy navchal'niy posíbnik.-2014. - 55 s. 
http://do.unicyb.kiev.ua/index.php/uk/2011-01-03-16-37-54?task=download&cid[0]=43
        
    
            Planned learning activities and teaching methods
        
        
            Lectures, practice work, independent work, test works.
        
    
            Assessment methods and criteria
        
        
            Intermediate assessment:
Maximum number of points that can be obtained by a student: 100 points:
1. Test work no. 1: 25/15 points.
2. Test work no. 2: 25/15 points.
3. Work in the audience:: 50/30 points.
Final assessment (in the form of a test):
Not provided
        
    
            Language of instruction
        
        
            Ukrainian
        
    Lecturers
This discipline is taught by the following teachers
                    Bohdan
                    V.
                    Dovhai
                
                
                    Operations Research  
Faculty of Computer Science and Cybernetics
            Faculty of Computer Science and Cybernetics
Departments
The following departments are involved in teaching the above discipline
                        Operations Research 
                    
                    
                        Faculty of Computer Science and Cybernetics