Nonlinear and Information Analysis in Biomedicine
Code  Completion  Credits  Range  Language 

F7ADINEIA  ZK  20P+8C  English 
 Garant předmětu:
 Pavel Smrčka
 Lecturer:
 Gleb Donin, Pavel Smrčka
 Tutor:
 Gleb Donin, Pavel Smrčka
 Supervisor:
 Department of Information and Communication Technology in Medicine
 Synopsis:

The aim of the course is to acquaint students with practical applications of fractal and multifractal analysis, applied to biological timeseries.
The course syllabus covers mainly the following topics: introduction to deterministic chaos, practical computation of selected invariant parameters from experimental data, tests for determinism and nonlinearity, fractal and multifractal analysis of biological time series, information entropy, average mutual information, examples of typical applications of nonlinear and information analysis in biology and medicine.
 Requirements:

As a standard, fulltime teaching takes place and the course ends with an oral exam, which is preceded by written preparation. If the number of students is less than 5, teaching can take place at a distance in the form of guided selfstudy with regular consultations. Furthermore, the student prepares a written study on a given topic in the field. The condition for admission to the exam is the completion of two laboratory exercises (evidenced by a protocol signed by the student, the head of the exercise and the guarantor of the course). The protocols will be archived in the doctoral study material.
 Syllabus of lectures:

1. Summary of practical applications of the fractal and multifractal analysis, applied to biological timeseries.
2. Introduction to deterministic chaos, dicrete and continuos systems with chaotic behavior.
3. Takens theorem, practical computation of selected invariant parameters from experimental data (correlation dimension, Lyapunov exponents etc.).
4. Tests for determinism and nonlinearity.
5. Fractal analysis of biological time series.
6. Highdimensional chaos. Multifractal formalism, estimators of Hurst exponents, selfsimilarity of time series.
7. Relationship between information, entropy, systems, signals.
8. Information entropy, applications. An average mutual information.
9. Continuous and discrete communication channel.
10. Relationship of information and thermodynamic entropy.
 Syllabus of tutorials:

1. Summary of practical applications of the fractal and multifractal analysis, applied to biological timeseries.
2. Introduction to deterministic chaos, dicrete and continuos systems with chaotic behavior.
3. Takens theorem, practical computation of selected invariant parameters from experimental data (correlation dimension, Lyapunov exponents etc.).
4. Tests for determinism and nonlinearity.
5. Fractal analysis of biological time series.
6. Highdimensional chaos. Multifractal formalism, estimators of Hurst exponents, selfsimilarity of time series.
7. Relationship between information, entropy, systems, signals.
8. Information entropy, applications. An average mutual information.
9. Continuous and discrete communication channel.
10. Relationship of information and thermodynamic entropy.
 Study Objective:
 Study materials:

Required:
[1] Christos H. Skiadas: Handbook of Applications of Chaos Theory, Chapman and Hall, 2016
[2] David J. Lubliner: Biomedical informatics: an introduction to information systems and software in medicine and health, Boca Raton : CRC Press, Taylor & Francis Group, 2016
Recommended:
[3] Andreas Holzinger, Igor Jurisica: Interactive Knowledge Discovery and Data Mining in Biomedical Informatics, Springer Verlag 2014
[4] David J. Lubliner: Biomedical informatics: an introduction to information systems and software in medicine and health, Boca Raton : CRC Press, Taylor & Francis Group, 2016
[5] Raymond W. Yeung. Information Theory and Network Coding Springer 2008, 2002. ISBN 9780387792330
[6] M. Cover, Joy A. Thomas. Elements of information theory, 2nd Edition. New York: WileyInterscience, 2006. ISBN 0471241954
[7] Leon Brillouin, Science and Information Theory, Mineola, N.Y.: Dover, 3rd edition 2004. ISBN 0486439186
 Note:
 Timetable for winter semester 2022/2023:
 Timetable is not available yet
 Timetable for summer semester 2022/2023:
 Timetable is not available yet
 The course is a part of the following study plans: