Master study
Study plan
1. grade
winter semester
Code | Course name | P/C/L | Examination | Credits |
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Compulsory courses | ||||
M320043 | Molecular Modelling
AnnotationThe subject covers theoretical backgrounds and practical examples of application of computational methods on molecular systems, namely molecular mechanics and quantum mechanics. It includes small molecules, as well as biomolecules and supra-molecular systems. Syllabus
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2/0/0 | Zk | 3 |
M143003 | Genomics: Algorithms and Analysis
AnnotationWithin this course contemporary high-throughput sequencing techniques are introduced. The main focus of the course are individual applications such as, e.g., ChIP-Seq, RNA-Seq, resequencing, metagenomics or de-novo sequencing. A procedures of the complete analyses for individual applications will be described, and will be demonstrated during practical exercises. Explained knowledge include sequence quality reading ("base calling") and its control, data formats and standards, advanced software tools and evaluation of their suitability, mapping of sequence data, short and long sequence assembly, identification of SNPs, and functional annotation. Syllabus
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2/2/0 | z, Zk | 5 |
M319001 | Molecular Biology
AnnotationThe subject is devoted to the study of cellular processes at the molecular level and is conceived so that the students receive the basic knowledge for understanding the complex functioning of eukaryotic cells in multicellular organisms. Syllabus
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2/0/0 | Zk | 3 |
M320017 | Genetic Engineering
AnnotationThe subject is focused on understanding of principles of manipulation with nucleic acids and their analysis. It cover information about various methods of introducing genes into diverse cell types, determination of gene expression and analysis. The goal is to deliver information about techniques genetic engineering for orientation to facilitate decision for optimal method for particular application. The lectures cover basic methods of isolation, analysis and modification of nucleic acids and special applications as gene modification for detection or affinity purification of gene product, study of interaction of proteins and nucleic acids, or gene therapies. Syllabus
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2/0/0 | Zk | 3 |
M143002 | Statistical Data Analysis
AnnotationThis course is the follow-up to the Applied Statistics lectures. Freely available statistical software R is presented, and students use it to practise common statistical tasks such as, e.g., exploratory data analysis, hypothesis testing, analysis of variance or regression. Syllabus
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2/2/0 | z, Zk | 5 |
M143010 | Practical Classes in Bioinformatics I
AnnotationThe goal of the course is to get practical knowledge of available bioinformatics toolkits and to be able to write some useful bioinformatics Python programs yourself. Syllabus
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0/2/0 | kz | 2 |
M500001 FIT | Efficient Text Pattern Matching
AnnotationStudents get knowledge of efficient algorithms for text pattern matching. They learn to use so called succinct data structures that are efficient in both access time and memory complexity. They will be able to use the knowledge in design of applications that utilize pattern matching. Syllabus
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2/1/0 | z, Zk | 4 |
Compulsorily optional courses | ||||
M445021 | Statistical Pattern Recognition
AnnotationThe lectures are oriented to application of mathematical statistics in pattern recognition. Basic terms, their relationships to statistics, programming techniques, and descriptor design are poined out together with research, real data processing, and applications. Syllabus
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2/2/0 | z, Zk | 5 |
M445023 | Introduction to Python
AnnotationThe course Introduction to Python provides a basic overview of the possibilities of Python and its possible applications. Students will learn about data structures, program flow control, and basic Python features, including creating documentation, working with the versioning system, testing code, and using the numpy and matplotlib packages. Syllabus
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1/3/0 | kz | 5 |
summer semester
Code | Course name | P/C/L | Examination | Credits |
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Compulsory courses | ||||
M143007 | Computational Drug Design
AnnotationThe aim of the course is to introduce basic principles and methods of molecular informatics and cheminformatics which deal with computational analysis of relationships between small organic molecules and biomolecules. Students will also be acquainted with concepts of a related field of a computational drug design. Topics include e. g. molecular similarity, design of chemical libraries, quantitative structure-activity relationship (QSAR), virtual screening or prediction of pharmacokinetic and toxicologic properties of compounds. Syllabus
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2/2/0 | z, Zk | 5 |
M143017 | Semestral project
AnnotationIn this course, the student, under the guidance of a designated supervisor, will prepare a written review on a chosen topic. This topic is related to the scientific activities of the Department of Informatics and Chemistry and the student will, thus, become acquainted in advance with the scientific results that will be the starting point for the solution of his/her diploma thesis. The review will be used as the theoretical part of the thesis. The student will present the review orally to a wider scientific audience at the end of the semester. Syllabus
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0/5/0 | kz | 3 |
M143004 | Gene Expression Data Analysis
AnnotationThis course will present basic types of functional genetics data such as RT-qPCR data, DNA chips profiling data, and high-throughput sequencing data. Students will acquire information on how to preprocess, clean, and standardize data, and will be acquainted with specific statistical and exploratory data analysis methods used for multidimensional genomic data processing. Students will learn how to interpret data using gene ontologies, how to archive, and how to visualize data. During exercises students will practise gained knowledge on the real life data, and will master commonly used online resources and analytical tools. Syllabus
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2/1/0 | z, Zk | 4 |
M143013 | Structural Bioinformatics
AnnotationThe course introduces structural bioinformatics – a multifields discipline which utilizes biomolecular structural data obtained by a range of experimental methods – X-Ray, NMR and electron microscopy. High numbers of structures in structural databases (ca. 130 000 structures in total) allow the application of computational and statistical methods to extract principles which control the folding process. These principles are used in structure prediction methods or as a basis for structural modelling in combination with physico-chemical rules. Students will get knowledge of basic principles used in structural bioinformatics, statistical methods, and available tools for structural analysis and prediction. Syllabus
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2/0/0 | Zk | 3 |
M143011 | Practical Classes in Bioinformatics II
AnnotationThis is the follow-up course for "Practical Classes in Bioinformatics I" and continues in exercising practical bioinformatics programming. Syllabus
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0/2/0 | kz | 2 |
M413004 | Multivariate data analysis
AnnotationBasic principles of selected statistical methods for analysing multidimensional data will be outlined with focus on reconciliation of the assumptions of the methods and interpretation of their results. Students will learn how to perform corresponding calculations in statistical software R. Syllabus
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2/2/0 | z, Zk | 5 |
M500002 FIT | Data Mining Algorithms
AnnotationIn this course, we discuss most popular data mining algoritms and optimization techniques such as decision trees, support vector machines, multilayered perceptrons etc. We also explain theoreticaly basic elements of statistical learning that are essential for all data engineers. Syllabus
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2/1/0 | z, Zk | 4 |
Compulsorily optional courses | ||||
M143008 | Probability and Random Processes
AnnotationThe course is focused on computer modelling of biological macromolecules (nucleic acids and proteins) and their interactions. With increasing computer power and development of new algorithms, computer modelling now forms an integral part of research in molecular biology, genetics and biochemistry. The first part of the course comprises an introduction to probability theory and stochastic processes, more solid than usually taught in introductory courses. This knowledge is of broader use well outside the domain of biomolecular modelling. We then use the acquired theoretical background to formulate an important simulation method, Brownian dynamics. We finish by discussing its applications to specific biological problems such as protein-ligand interactions or macromolecular dynamics in the cell. The exercises include theoretical topics as well as simple computations which the students are supposed to programm themselves. Syllabus
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2/1/0 | z, Zk | 4 |
M320010 | Enzymology
AnnotationThe general part of the course presents enzyme nomenclature, their covalent structure and structures of cofactors, enzyme kinetics, enzyme assays, regulation of enzymes in the cell, medicinal enzymology, enzyme engineering and mechanisms of enzymatic reactions. The second part will present applied enzymology, namely industrial production of enzymes, application of enzymes in food and non-food industry, enzyme-associated changes in food and raw materials and the role of enzymes in analytical chemistry, clinical diagnostics molecular biology research and organic synthesis. Syllabus
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2/1/0 | z, Zk | 4 |
2. grade
winter semester
Code | Course name | P/C/L | Examination | Credits |
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Compulsory courses | ||||
M320022 | Structural Bioinformatics seminar
AnnotationThe subject gives practical training in computational methods for prediction of structures of proteins, their application in modeling their complexes with small-molecule ligands and for simulation of their dynamics. The subject follows introduction to bioinformatics and structural biology and develops practical skills based on these subjects. These skills will help students in further praxis in biochemical and pharmaceutical research and development. Syllabus
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0/2/0 | kz | 2 |
M342018 | Scientific Communication
AnnotationThe course is aimed at acquisition of knowledge of presentation methods of own results and public performance at an Ms degree level. It covers also practicing of presented topics. Syllabus
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2/1/0 | z, Zk | 4 |
M143009 | Phylogenetics and Applied Genomics
AnnotationThe course focuses on comparative genomics both in the vertical direction, between species, with an emphasis on biological evolution, and in the horizontal direction, interspecies, with emphasis on diversity of populations. It describes the main evolutionary principles and their application to genomic and proteomic data with a focus on second and third generation high-throughput sequencing methods. It describes methods and algorithms of construction of phylogenetic trees from genic, genomic and protein sequences. It shows the differences between genome and species trees. It also describes known mutation processes, genome evolution, the molecular clock concept, selection and genetic drift on the molecular level, nucleotide composition, polymorphisms. One lecture is devoted to evaluating the quality and reliability of genetic trees. Furthermore, the course describes genetic variability within populations, ways of measuring this variability, and various models of population genetics. Special attention is paid to the main evolutionary forces that shape this population variability (genetic drift, isolation, migration, selection). Clinical applications include the detection of mutations in both germline and somatic lineage and their link to human diseases. Syllabus
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2/0/0 | Zk | 3 |
M143005 | Bioinformatics Applications
AnnotationThe aim of the course is to describe applications of bioinformatics in various scientific fields, and to defined their synergy. Discussed will be bioinformatics projects in imunology, pharmacy, and in other life science disciplines. Students will get acquainted with legal, ethical and commercial issues in bioinformatics, and will be informed about authorship and intellectual property rights. Important international bioinformatics integration proojects will also be introduced. Syllabus
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2/0/0 | Zk | 3 |
M143006 | Case Studies in Bioinformatics
AnnotationThis course summarizes acquired bioinformatics knowledge, and puts bioinformatics skills into a context. Lecturers will demonstrate individual methods and approaches using well documented and well performed experiments. Possible solutions will be compared, and their efficiency will be discussed. Syllabus
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2/0/0 | z | 3 |
M143012 | Pred-diploma Project
AnnotationThe content of the subject is an idependent work on a selected research project at the Department of Informatics and Chemistry. The topic of the project is chosen by the student from the current offer of the institute. The student usually continues on this subject during the work on his diploma thesis. The aim of the subject is to involve students into the research of the department, to familiarize them with the fundamentals of scientific work and with the methods of data processing and analysis and to teach them how to present results of their work. Syllabus
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0/5/0 | kz | 3 |
M500003 FIT | Computational Intelligence Methods
AnnotationStudents will understand methods and techniques of computational intelligence that are mostly nature-inspired, parallel by nature, and applicable to many problems. They will learn how these methods work and how to apply them to problems related to data mining, control, intelligen games, optimizations, etc. Syllabus
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2/1/0 | z, Zk | 4 |
M500004 FIT | Data Preprocessing
AnnotationStudents learn to prepare raw data for further processing and analysis. They learn what algorithms can be used to extract parameters from various data sources, such as images, texts, time series, etc., and learn the skills to apply these theoretical concepts to solve a specific problem in individual projects - e.g., parameter extraction from image data or from Internet. Syllabus
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2/1/0 | z, Zk | 4 |
Compulsorily optional courses | ||||
M320001 | Biophysical Chemistry
AnnotationThe lectures are focused on description of physical-chemical aspects of biological systems and use of physical-chemical terms to describe and solve the problems in biological systems. Students will have an overview of the most important concepts and methodology of modern biophysical chemistry as well as structural methods for description of biomacromolecules. Syllabus
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2/1/0 | Zk | 4 |
M320034 | Forensic genetics
AnnotationThis course introduces students to the forensic DNA analysis as the dominant method of determining the origin of biological material. It describes biological principles on which the field is based, application circuits (criminology, kinship analysis, identification analysis, bioarcheology, recreational genetics), principles of analysis from the collection of biological material to final evaluation. It brings an overview of non-ID analysis and includes the basics of forensic statistics in the field of genetic analysis. Syllabus
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2/2/0 | z, Zk | 5 |
summer semester
Code | Course name | P/C/L | Examination | Credits |
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Compulsory courses | ||||
M963001 | Diploma Thesis | 0/30/0 | z | 30 |