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.
Guarantor
Department
Learning outcomes of the course unit
Understanding the relations between computers (computing) and selected molecular processes.
Prerequisites
Co-requisites
Recommended optional programme components
Literature
Planned learning activities and teaching methods
Assesment methods and criteria linked to learning outcomes
Exam prerequisites:
None.
Language of instruction
Work placements
Aims
Specification of controlled education, way of implementation and compensation for absences
- 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
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
Teacher / Lecturer
Syllabus
- Biological databases
- Analysis of genome sequences
- Sequence alignment
- Phylogenetic trees
- Gene prediction
- Protein structure analysis
Project
Teacher / Lecturer
Syllabus