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CZECH TECHNICAL UNIVERSITY IN PRAGUE
STUDY PLANS
2024/2025

Information Analysis in Biomedicine

The course is not on the list Without time-table
Code Completion Credits Range Language
F7DINEIA ZK 20P+8C Czech
Garant předmětu:
Lecturer:
Tutor:
Supervisor:
Department of Information and Communication Technology in Medicine
Synopsis:

Summary of practical applications of fractal and multifractal analysis, applied to biological time-series. Introduction to deterministic chaos, discrete and continuous models with chaotic behavior. Takens theorem, practical computation of selected invariant parameters from experimental data (correlation dimension, Lyapunov exponents etc.). Tests for determinism and nonlinearity. Fractal analysis of biological time series. Time series parameters extraction.High-dimensional chaos. Multifractal formalism, estimators of Hurst exponents, self-similarity of time series. Information entropy, applications. Average mutual information. Continuous and discrete communication channel. Relationship of information and thermodynamic entropy. Principle of maximal entropy. Relationship between information and thermodynamic entropy. Biosystem organization, models and system identification. Introduction to statistical decision making, testing of statistical hypothesis. Examples of typical applications of nonlinear and information analysis in biology and medicine.

Requirements:

As a standard, full-time 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 self-study 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 time-series.

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. High-dimensional chaos. Multifractal formalism, estimators of Hurst exponents, self-similarity 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. Examples of statistical decision making, basics of testing statistical hypotheses.

2. Examples of modern applications of nonlinear and information analysis in biology and medicine.

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 978-0-387-79233-0

[6] M. Cover, Joy A. Thomas. Elements of information theory, 2nd Edition. New York: Wiley-Interscience, 2006. ISBN 0-471-24195-4

[7] Leon Brillouin, Science and Information Theory, Mineola, N.Y.: Dover, 3rd edition 2004. ISBN 0-486-43918-6

Note:
Further information:
No time-table has been prepared for this course
The course is a part of the following study plans:
Data valid to 2024-03-29
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