Data Analysis and Correlations in Biology

Data Analysis and Correlations in Biology

Code: 63068
ECTS: 7.0
Lecturers in charge: doc. dr. sc. Matko Glunčić - Lectures
Lecturers: Matko Glunčić - Exercises
Take exam: Studomat
Load:

1. komponenta

Lecture typeTotal
Lectures 30
Exercises 15
* Load is given in academic hour (1 academic hour = 45 minutes)
Description:
COURSE GOALS: The course goal is to introduce students to basic terms and methodological approaches of nonlinear dynamics, fractal geometry and information theory as well as with a use of existing databases. Students should also gain a preliminary insight into relevant actual theoretical literature

LEARNING OUTCOMES AT THE LEVEL OF THE PROGRAMME:
1. KNOWLEDGE AND UNDERSTANDING
1.3. demonstrate a thorough knowledge of the most important physics theories (logical and mathematical structure, experimental support, described physical phenomena)
1.4. describe the state of the art in - at least- one of the presently active physics specialities;
2. APPLYING KNOWLEDGE AND UNDERSTANDING
2.3. apply standard methods of mathematical physics, in particular mathematical analysis and linear algebra and corresponding numerical methods;
3. MAKING JUDGMENTS:
3.3. develop a personal sense of responsibility, given the free choice of elective/optional courses;
4. COMUNICATION SKILLS
4.4. present one's own research or literature search results to professional as well as to lay audiences
4.5. develop the written and oral English language communication skills that are essential for pursuing a career in physics;
5. LEARNING SKILLS:
5.1. search for and use physical and other technical literature, as well as any other sources of information relevant to research work and technical project development (good knowledge of technical English is required);
5.4. participate in projects which require advanced skills in modelling, analysis, numerical calculations and use of technologies;

LEARNING OUTCOMES SPECIFIC FOR THE COURSE
Upon completing the course, students will be able to:
* use theoretical physics and information theory tools in biology data analysis;
* use statistical analysis in identifying patterns;
* describe and to explain fractal object, calculate its dimension and to list most known fractal objects in biology and in other natural sciences;
* describe and to explain noise and to be able to analyse noise with biology data;
* describe and to explain deterministic chaos and to list most known chaos systems in biology and in other natural sciences;

COURSE DESCRIPTION
1. Novel methods in data analysis in theoretical physics and information theory (3 weeks)
2. Data analysis on the specific examples in biology (2 weeks);
3. Nonlinear time sequences (2 weeks);
4. Fractal geometry methods in biology and other natural sciences (2 weeks),
5. Data analysis with space-time dynamics (2 weeks),
6. Noise analysis in biology (2 weeks),
7. Deterministic chaos identification in biological and other natural objects (2 weeks)

REQUIREMENTS FOR STUDENTS
Students are required to attend classes, to participate in exercises and to solve problems and quizzes during the semester.

GRADING AND ASSESSING THE WORK OF STUDENTS
It includes all elements of monitoring student achievements during the semester plus one final oral exam.
Literature:
  1. H.O. Peitgen, H. Juergens, D. Saupe, Chaos and fractals (Springer, New York, 1993)
  2. A. Bunde, S. Havlin (eds.) Fractals in Science (Springer, Berlin, 1995)
  3. J.H. Brown, G.B. West, Scaling in biology (Oxford University Press, Oxford, 2000)
Prerequisit for:
Enrollment :
Passed : Classical Mechanics 2
9. semester
Izborni predmeti - Mandatory studij - Physics
Consultations schedule:

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