Course detail
Bioinformatics
FIT-BIFAcad. year: 2020/2021
This course introduces students to basic principles of molecular biology, present algorithms pro biological data analysis, describes their time complexity and shows direction how to design the new methods very effectively. Particularly, the following algorithms will be discussed: methods for sequence alignment, evolutionary models, construction of phylogenetic trees, algorithms for gene identification using machine learning and approaches for prediction of 2D and 3D protein structure. Lectures will be supplement with practical examples using available biological databases.
Supervisor
Department
Learning outcomes of the course unit
Students will be able to take advantages of large biological database and design new efficient algorithms for their analysis.
Understanding the relations between computers (computing) and selected molecular processes.
Prerequisites
Not applicable.
Co-requisites
Not applicable.
Recommended optional programme components
Not applicable.
Recommended or required reading
Jacques Cohen: Bioinformatics - An introduction for Computer Scientists, ACM Computing Surveys, 2004, Vol. 36, No. 2, p. 122-158.
Jean-Michel Claverie, Cedric Notredame: Bioinformatics for Dummies, ISBN: 0-7645-1696-5, Wiley Publishing, Inc., 2003.
Yi-Ping Phoebe Chen: Bioinformatics Technologies, ISBN: 3540208739, Springer, 2005.
Alberts, Bray, Johnson, Lewis, Raff, Roberts, Walter: Základy buněčné biologie, ISBN: 80-902906-0-4, Espero Publishing, 1998.
Supratim Choudhuri: Bioinformatics for Beginners: Genes, Genomes, Molecular Evolution, Databases and Analytical Tools, ISBN: 978-0124104716, Academic Press, 2014
Dan K. Krane, Michael L. Raymer: Fundamental Concepts of Bioinformatics, ISBN: 0-8053-4633-3, Benjamin Cummings 2003.
Neil C. Jones, Pavel A. Pevzner: An Introduction to Bioinformatics Algorithms, ISBN: 0262101068, MIT Press, 2004.
Andreas D. Baxevanis, B. F. Francis Ouellette: Bioinformatics: A Practical Guide to the Analysis of Genes and Proteins, ISBN: 0-471-47878-4, Wiley-Interscience, 2005.
Planned learning activities and teaching methods
Not applicable.
Assesment methods and criteria linked to learning outcomes
Mid-term exam, project, computer lab assignments.
Exam prerequisites:
None.
Language of instruction
Czech
Work placements
Not applicable.
Aims
To understand the principles of molecular biology. To perceive the basic used algorithms and to well informed about relevant biological databases. To be able to design new effective methods for biological data analysis.
Specification of controlled education, way of implementation and compensation for absences
Presence in any form of instruction is not compulsory. An absence (and hence loss of points) can be compensated in the following ways:
- presence in another laboratory group dealing with the same task.
- showing a summary of results to the tutor at the next lab.
- sending a short report (summarizing the results of the missed lab and answering the questions from the assignment) to the tutor, in 14 days after the missed lab.
Classification of course in study plans
- Programme IT-MGR-2 Master's
branch MPV , any year of study, summer semester, 5 credits, elective
branch MGM , any year of study, summer semester, 5 credits, elective
branch MSK , any year of study, summer semester, 5 credits, elective
branch MIS , any year of study, summer semester, 5 credits, elective
branch MBS , any year of study, summer semester, 5 credits, elective
branch MIN , any year of study, summer semester, 5 credits, elective
branch MMM , any year of study, summer semester, 5 credits, elective - Programme MITAI Master's
specialization NADE , any year of study, summer semester, 5 credits, elective
specialization NGRI , any year of study, summer semester, 5 credits, elective
specialization NNET , any year of study, summer semester, 5 credits, elective
specialization NVIZ , any year of study, summer semester, 5 credits, elective
specialization NCPS , any year of study, summer semester, 5 credits, elective
specialization NSEC , any year of study, summer semester, 5 credits, elective
specialization NEMB , any year of study, summer semester, 5 credits, elective
specialization NHPC , any year of study, summer semester, 5 credits, elective
specialization NISD , any year of study, summer semester, 5 credits, elective
specialization NIDE , any year of study, summer semester, 5 credits, elective
specialization NISY , any year of study, summer semester, 5 credits, elective
specialization NMAL , any year of study, summer semester, 5 credits, elective
specialization NMAT , any year of study, summer semester, 5 credits, elective
specialization NSEN , any year of study, summer semester, 5 credits, elective
specialization NVER , any year of study, summer semester, 5 credits, elective
specialization NSPE , any year of study, summer semester, 5 credits, elective - Programme IT-MGR-2 Master's
branch MBI , 1. year of study, summer semester, 5 credits, compulsory
- Programme MITAI Master's
specialization NBIO , 1. year of study, summer semester, 5 credits, compulsory
Type of course unit
Lecture
26 hours, optionally
Teacher / Lecturer
Syllabus
- Introduction to bioinformatics
- Basis of molecular biology
- Tools of molecular biology
- Biological databases
- Sequence alignment, dynamic programing, BLAST, FASTA
- Evolutionary models
- Construction of phylogenetic trees
- DNA assembling
- Genomics and gene searching
- Proteins and their prediction
- Computation of RNA secondary structure
- Proteomics, regulatory networks
- Polymorphism of genes
Exercise in computer lab
12 hours, compulsory
Teacher / Lecturer
Syllabus
- Biological databases
- Analysis of genome sequences
- Sequence alignment
- Phylogenetic trees
- Gene prediction
- Protein structure analysis
Project
14 hours, compulsory
Teacher / Lecturer
Syllabus
A project will be assigned to each student. Implementation, presentation and documentation of the project will be evaluated.