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Matematical Modelling in Biology and Medicine

General data

Course ID: WM-MA-Z-S1-E5-Mmwbim
Erasmus code / ISCED: (unknown) / (unknown)
Course title: Matematical Modelling in Biology and Medicine
Name in Polish: Modelowanie matematyczne w biologii i medycynie
Organizational unit: Faculty of Mathematics and Natural Sciences. School of Exact Sciences.
Course groups:
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.
Language: Polish
(in Polish) Dyscyplina naukowa, do której odnoszą się efekty uczenia się:

mathematics

Subject level:

elementary

Learning outcome code/codes:

LECTURE

MA1_W01, MA1_W03

EXERCISES

MA1_K01, MA1_K02

Preliminary Requirements:

(in Polish) Analiza I i II, Algebra Liniowa, RRZ, Rachunek P-stwa

Full description:

The aim of the course is to introduce the basics of classical mathematical modeling in biology, epidemiology and medicine. In particular, the student will learn biological and medical applications of integrals and derivatives; equations and systems of ordinary differential equations modeling the development of populations, epidemics, and diseases; discrete models in genetics based on Markov chains. The student will also acquire basic skills in understanding models, their construction, their application in practice and their mathematical analysis.

Efekty kształcenia i opis ECTS:

The student knows and understands: (MA1_W01, MA1_W03)

W1.1 - using the derivative as the rate of change or gradient of a given quantity,

W1.2 - construction, applications and limitations of polynomial regression;

W2 - differential equation (dimension 1 or higher) which is a biological and epidemiological model, the concept of steady states, their stability and their importance in models; including models: exponential and logistic, L-V, SIR, their variants; other models;

W3 - basic discrete models which are numerical schemes for solving RRZ and discrete models based on Markov chains.

The student is able to (MA_W03, MA1_U01)

U1 - solve problems requiring the use of derivatives, integrals, research on the course of function variability in biological and epidemiological applications,

U2 - perform basic analysis of the RRZ-based model, its steady states, stability, interpret mathematical conclusions in a real context;

U3 - carry out basic analysis of a model based on a Markov-type process, its absorbing states, expected value;

The student is ready: (MA1_K01, MA1_K02)

K1 - prepare a paper presenting a new issue,

K2 - participate in a scientific discussion.

Assessment methods and assessment criteria:

For all effects, the following assessment criteria are adopted for all forms of verification:

grade 5: fully achieved (no obvious shortcomings)

grade 4.5: achieved almost fully and criteria for awarding a higher grade are not met

grade 4: largely achieved and the criteria for a higher grade are not met

grade 3.5: largely achieved - with a clear majority of positives - and the criteria for granting a higher grade are not met

grade 3: achieved for most of the cases covered by the verification and criteria for a higher grade are not met

grade 2: not achieved for most of the cases covered by the verification

Classes in period "Winter semester 2022/23" (past)

Time span: 2022-10-01 - 2023-01-31
Selected timetable range:
Navigate to timetable
Type of class:
Classes, 20 hours more information
Lectures, 20 hours more information
Coordinators: Maria Gokieli
Group instructors: Maria Gokieli
Students list: (inaccessible to you)
Examination: Course - examination
Classes - graded credit
Lectures - examination
(in Polish) E-Learning:

(in Polish) E-Learning (pełny kurs) z podziałem na grupy

(in Polish) Opis nakładu pracy studenta w ECTS:

(in Polish) WYKŁAD

uczestnictwo w zajęciach - 20 h

konsultacje - 6 h

egzamin - 4 h

samodzielna lektura - 10 h

przygotowanie do egzaminu - 10 h


razem 50 h czyli 2 ECTS


ĆWICZENIA

uczestnictwo w zajęciach - 20 h

przygotowanie referatów - 15 h

prace domowe - 15 h


razem 50 h czyli 2 ECTS

Classes in period "Winter semester 2023/24" (past)

Time span: 2023-10-01 - 2024-01-31
Selected timetable range:
Navigate to timetable
Type of class:
Classes, 20 hours more information
Lectures, 20 hours more information
Coordinators: Maria Gokieli, Paweł Pęczkowski
Group instructors: Paweł Pęczkowski
Students list: (inaccessible to you)
Examination: examination
(in Polish) E-Learning:

(in Polish) E-Learning

(in Polish) Opis nakładu pracy studenta w ECTS:

LECTURE

participation in classes - 20 h

consultations - 6 h

exam - 4 hours

independent reading - 10 h

preparation for the exam - 10 hours

total 50 hours, i.e. 2 ECTS


EXERCISES

participation in classes - 20 h

preparation of papers - 15 hours

housework - 15 h

total 50 hours, i.e. 2 ECTS

Type of subject:

obligatory

(in Polish) Grupa przedmiotów ogólnouczenianych:

(in Polish) nie dotyczy

Full description:

The aim of the course is to introduce the basics of classical mathematical modeling in biology, epidemiology and medicine. In particular, the student will learn biological and medical applications of integrals and derivatives; equations and systems of ordinary differential equations modeling the development of populations, epidemics, and diseases; discrete models in genetics based on Markov chains. The student will also acquire basic skills in understanding models, their construction, their application in practice and their mathematical analysis.

Bibliography:

Required literature

J. Stewart, Calculus, PWN 2020

U. Foryś, Mathematical modeling in biology and medicine, https://mst.mimuw.edu.pl/wyklady/mbm/wyklad.pdf

Additional literature

U. Foryś, Mathematics in biology, WNT 2005

J.D. Murray, Introduction to biomathematics, PWN 2006

A. Garfinkel, J. Shevtsov, Y. Guo, Modeling Life - The Mathematics of Biological Systems, Springer 2017

Wymagania wstępne:

3rd year. nst.

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