Course detail

Advanced Bioinformatics

FIT-PBIAcad. year: 2017/2018

During the lectures, the students will get acquainted with areas integrating different bioinformatic data-types. They will study possibilities of data integration to solve specific problems or create specific computational tools. Textbook material will be supplemented by recently published scientific papers. Students will work on individual computational modules in the exercises/projects leading to the creation of an integrated whole-class tool suitable for general bioinformatic analysis (functional annotation, structural prediction, molecule visualization).

Language of instruction

Czech

Number of ECTS credits

4

Mode of study

Not applicable.

Guarantor

Ing. Matej Lexa, Ph.D.

Department

Department of Computer Systems (UPSY)

Learning outcomes of the course unit

Knowledge of less-common algorithm and analysis methods, better ability to design and implement algorithms for bioinformatics.

Deeper understanding the role of computers in the analysis and presentation of biological data.

Prerequisites

There are no prerequisites

Co-requisites

Not applicable.

Planned learning activities and teaching methods

Not applicable.

Assesment methods and criteria linked to learning outcomes

Study evaluation is based on marks obtained for specified items. Minimimum number of marks to pass is 50.

None.

Course curriculum

    Syllabus of lectures:
    1. Introduction
    2. Primary and derived bioinformatic data
    3. Genomes and genome analysis methods
    4. Uniprot and sequence analysis methods
    5. Statistical, information-theory and linguistic aspect of data
    6. Coding algorithms for biological sequence analysis
    7. PDB and structural data analysis
    8. Gene Ontology and functional data analysis
    9. Integration of data from multiple sources for genomics and proteomics
    10. Tools and libraries for software development (Biopython)
    11. Visualization tools (PyMol)
    12. Bioinformatics and nanotechnology: DNA computing, sequencing by hybridization
    13. Recent trends

    Syllabus of computer exercises:
    1. Biological sequence analysis
    2. Genome Browser, Biomart
    3. Biopython a PyMol
    4. R/Bioconductor
    5. Integration of bioinformatic data

    Syllabus - others, projects and individual work of students:
    Design and implementation of an integrated computational tool for bioinformatics and its presentation on a mini-conference.

Work placements

Not applicable.

Aims

To build on the introductory bioinformatics course. Introduce the students to selected, fast-evolving, or otherwise noteworthy areas of bioinformatics. To allow space for creative activities resulting in the creation of a computational tool based on studied principles.

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

Project, computer labs assignments.

Recommended optional programme components

Not applicable.

Prerequisites and corequisites

Not applicable.

Basic literature

Not applicable.

Recommended reading

Jones N.C., Pevzner P.: An introduction to algorithms in bioinformatics. MIT Press, 2004, ISBN 978-0262101066

Classification of course in study plans

  • Programme IT-MSC-2 Master's

    branch MBI , 2 year of study, winter semester, compulsory

Type of course unit

 

Lecture

20 hod., optionally

Teacher / Lecturer

Ing. Matej Lexa, Ph.D.

Syllabus

  1. Introduction
  2. Primary and derived bioinformatic data
  3. Genomes and genome analysis methods
  4. Uniprot and sequence analysis methods
  5. Statistical, information-theory and linguistic aspect of data
  6. Coding algorithms for biological sequence analysis
  7. PDB and structural data analysis
  8. Gene Ontology and functional data analysis
  9. Integration of data from multiple sources for genomics and proteomics
  10. Tools and libraries for software development (Biopython)
  11. Visualization tools (PyMol)
  12. Bioinformatics and nanotechnology: DNA computing, sequencing by hybridization
  13. Recent trends

Exercise in computer lab

13 hod., optionally

Teacher / Lecturer

Ing. Matej Lexa, Ph.D.

Syllabus

  1. Biological sequence analysis
  2. Genome Browser, Biomart
  3. Biopython a PyMol
  4. R/Bioconductor
  5. Integration of bioinformatic data

Project

6 hod., optionally

Teacher / Lecturer

Ing. Matej Lexa, Ph.D.