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Stochastic processes in biology and social sciences

General data

Course ID:	1000-135PSB
Erasmus code / ISCED:	(unknown) / (unknown)
Course title:	Stochastic processes in biology and social sciences
Name in Polish:	Procesy stochastyczne w biologii i naukach społecznych
Organizational unit:	Faculty of Mathematics, Informatics, and Mechanics
Course groups:	(in Polish) Przedmioty obieralne na studiach drugiego stopnia na kierunku bioinformatyka Elective courses for 2nd stage studies in Mathematics Specific programme courses of 2nd stage Bioinformatics
ECTS credit allocation (and other scores):	6.00 Basic information on ECTS credits allocation principles: the annual hourly workload of the student’s work required to achieve the expected learning outcomes for a given stage is 1500-1800h, corresponding to 60 ECTS; the student’s weekly hourly workload is 45 h; 1 ECTS point corresponds to 25-30 hours of student work needed to achieve the assumed learning outcomes; weekly student workload necessary to achieve the assumed learning outcomes allows to obtain 1.5 ECTS; work required to pass the course, which has been assigned 3 ECTS, constitutes 10% of the semester student load. view allocation of credits
Language:	English
Type of course:	elective courses
Short description:	Lectures on theoretical foundations of stochastic analysis (Markov chains, Poisson process, birth and death processes, Master and Fokker-Planck equations will be integrated with concrete biological models on the micro level (gene expression and regulation, ion channels) and on the macro level (evolutionary game theory).
Full description:	Lectures on theoretical foundations of stochastic analysis (Markov chains, Poisson process, birth and death processes, Master and Fokker-Planck equations will be integrated with concrete biological models on the micro level (gene expression and regulation, ion channels) and on the macro level (evolutionary game theory).
Bibliography:	1. G. R. Grimmett i D. R. Stirzaker, Probability and Random Processes, Oxford University Press, 1982 2. Ch. Mazza i M. Benaim, Stochastic Dynamics for Systems Biology, Chapman and Hall/CRC Mathematical and Computational Biology, 2014.
Learning outcomes:	Knowledge and Competence 1. Student knows basic definitions, theorems, and properties of Markov chains, branching processes, Poisson process, and birth and death processes. 2. Student knows how to compute moments using generating functions. 3. Student knows basic mathematical models of gene expression and evolutionary game theory. 4. Student knows how to construct mathematical models based on biological and social texts. Social Competence Student is able to talk with biologists and economists about mathematics and with mathematicians about biology and social science.
Assessment methods and assessment criteria:	Tests: 30% Project: 30% Written Exam: 40%

Classes in period "Summer semester 2023/24" (in progress)

Time span:	2024-02-19 - 2024-06-16	Selected timetable range: weekly course term Navigate to timetable MO TU WYK CW W TH FR
Type of class:	Classes, 30 hours more information Lecture, 30 hours more information
Coordinators:	Jan Karbowski
Group instructors:	Jan Karbowski
Students list:	(inaccessible to you)
Examination:	Examination

Classes in period "Summer semester 2024/25" (future)

Time span:	2025-02-17 - 2025-06-08	Selected timetable range: weekly course term Navigate to timetable
Type of class:	Classes, 30 hours more information Lecture, 30 hours more information
Coordinators:	Jan Karbowski
Group instructors:	Jan Karbowski
Students list:	(inaccessible to you)
Examination:	Examination

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