Course detail

Multidimensional Analysis of Biomedical Data

FEKT-MPA-VMMAcad. year: 2020/2021

Not applicable.

Language of instruction

English

Number of ECTS credits

5

Mode of study

Not applicable.

Guarantor

Ing. Marina Filipenská, Ph.D.

Department

Department of Biomedical Engineering (UBMI)

Learning outcomes of the course unit

Not applicable.

Prerequisites

Not applicable.

Co-requisites

Not applicable.

Planned learning activities and teaching methods

Not applicable.

Assesment methods and criteria linked to learning outcomes

Not applicable.

Course curriculum

1. Introduction to analysis of multidimentional biological data. Multidimentional analysis object, pros and cons. Classification of the methods.
2. Linear algebra foundations.
3. Multidimentional distributions and statistical tests.
4. Methods for data preprocessing. Transformation and standardization approaches. Problem of missing data.
5. Relationship between variables in multidimentional space. Similarity and distance measures. Correlation and covariance.
6. Cluster analysis of biological data. Hierarchical and non-hierarchical clustering. Determining the optimal number of clusters. Clusters validation.
7. Ordinal analysis. Review of the methods used in biomedical applications.
8. Principal component analysis (PCA). Singular value decomposition.
9. Factor analysis. Fundamentals of factor analysis. Rotation of the factors.
10. Independent component analysis (ICA). ICA based feature extraction from biomedical data. Relationship between PCA, ICA and factor analysis.
11. Non-linear methods for data dimensionality reduction.
12. Multidimensional data analysis in biomedicine applications – overview.

Work placements

Not applicable.

Aims

Not applicable.

Specification of controlled education, way of implementation and compensation for absences

Not applicable.

Recommended optional programme components

Not applicable.

Prerequisites and corequisites

Not applicable.

Basic literature

A.C. Rencher: Methods of Multivariate Analysis, Wiley-Interscience, 2002 (CS)
J.H. McDonald: Handbook of Biological Statistics, Sparky House Publishing, 2008 (CS)

Recommended reading

S. Theodoridis, K. Koutroumbas: An Introduction to Pattern Recognition: A Matlab Approach, Elsevier, 2010 (CS)

Classification of course in study plans

  • Programme MPA-BIO Master's 1 year of study, winter semester, compulsory

Type of course unit

 

Lecture

26 hod., optionally

Teacher / Lecturer

Ing. Marina Filipenská, Ph.D.

Exercise in computer lab

26 hod., compulsory

Teacher / Lecturer

Ing. Marina Filipenská, Ph.D.