C3211 Applied bioinformatics

Faculty of Science
Spring 2025
Extent and Intensity
0/2. 3 credit(s). Type of Completion: k (colloquium).
In-person direct teaching
Teacher(s)
prof. RNDr. Michaela Wimmerová, Ph.D. (lecturer)
Mgr. Josef Houser, Ph.D. (seminar tutor)
Mgr. Lenka Malinovská, Ph.D. (seminar tutor)
Guaranteed by
prof. RNDr. Michaela Wimmerová, Ph.D.
National Centre for Biomolecular Research – Faculty of Science
Supplier department: National Centre for Biomolecular Research – Faculty of Science
Prerequisites
Basic knowledge of biomacromolecules
Course Enrolment Limitations
The course is offered to students of any study field.
The capacity limit for the course is 15 student(s).
Current registration and enrolment status: enrolled: 0/15, only registered: 0/15, only registered with preference (fields directly associated with the programme): 0/15
Course objectives
At the end of the course students should be able to utilize bioinformatic tools for solving biological problems and for optimization of experimental laboratory research.
Learning outcomes
At the end of the course students should: 1) Obtain basic knowledge of bioinformatics. Students should be able to: 1) Process bioinformational data. 2) Predict basic properties of biomacromolecules. 3) Utilize bioinformational tools for solving of biological problems.
Syllabus
  • Peptides and proteins: theoretical introduction (proteinogenic amino acids, non-standard proteinogenic amino acids), D-amino acids, D-peptides, d-proteins, antimicrobial peptides, peptide design, hydrophobic moment, "helical wheel", How to work with proteins?, melting temperature (Tm), prediction of melting temperature, prediction of thermostability, stabilizing mutations and databases, protein aggregation (in vitro, in vivo), prediction of aggregation (from sequence, from structure), prediction of prions, aggregation and neurodegenerative diseases. Preparation of recombinant proteins: theoretical introduction (protein origin, host organism), toxic proteins, significance of disulfide bridges, inclusion bodies, prediction of protein solubility, codon usage, codon analysis and optimization, synthetic gene, intron problem, glycosylation, prediction of glycosylation and other post-translational modifications.
  • Secondary structure and function of proteins: theoretical background (secondary structure and protein folding, CD spectroscopy, prediction of protein function, secondary protein databases), secondary structure prediction, CD spectrum prediction, prediction of function by sequence alignment, identification and analysis of active site, mutations in active sites, identification of structural and functional motifs in sequences.
  • Protein tertiary structure and oligomerization: theoretical background (3D structure, structural databases, structure determination, RTG, NMR, theory of structure prediction, importance of oligomerization, determination of oligomerization), 3D structure visualization, types of depiction, homology proteins alignment, active site analysis, prediction tools, model validation, prediction of oligomerization, repetition analysis.
Literature
Teaching methods
Lectures, practical exercises in silico, educational excursions.
Assessment methods
Homework, oral exam.
Language of instruction
Czech
Further Comments
The course is taught: every week.
The course is also listed under the following terms Spring 2013, Spring 2014, Spring 2015, Spring 2016, Spring 2017, spring 2018, Spring 2019, Spring 2020, Spring 2021, Spring 2022, Spring 2023, Spring 2024.
  • Enrolment Statistics (Spring 2025, recent)
  • Permalink: https://is.muni.cz/course/sci/spring2025/C3211