460-6029/02 – Biomarkers and Computational proteomics (VP)
| Gurantor department | Department of Computer Science | Credits | 10 |
| Subject guarantor | prof. MUDr. Vít Procházka, Ph.D. | Subject version guarantor | prof. MUDr. Vít Procházka, Ph.D. |
| Study level | postgraduate | Requirement | Choice-compulsory type B |
| Year | | Semester | winter + summer |
| | Study language | English |
| Year of introduction | 2019/2020 | Year of cancellation | |
| Intended for the faculties | FEI | Intended for study types | Doctoral |
Subject aims expressed by acquired skills and competences
The aim of the course is to deepen students' knowledge in the field of proteomics, with special emphasis to biomarkers, analysis and interpretation of data generated in proteomic experiments. In addition, this knowledge and skills will be further enhanced in a direction that is in line with the specific focus of its Ph.D. studies and dissertation work.
Teaching methods
Seminars
Individual consultations
Project work
Other activities
Summary
The course focuses on biomarkers, their validation and verification and their use in biomedicine. Students will be acquainted with methods and tools used in computational biology and proteomics (alignment of sequences and structures, protein structure prediction, protein folding, protein-protein interaction, protein design and modeling). Qualitative and quantitative methods of protein detection, their importance and use in biomedicine will be discussed and the impact of changes on selected diseases and complications discussed. The aim is to help students quickly cope with proteomics, their clinical use and interpretation of proteomic data, and be able to use computational tools to solve problems in their own research. Examples and practical examples of analyzes of relevant data sets and practical use of proteomics and proteome analyzes in biomedicine will be discussed.
Compulsory literature:
• Barh D, Carpi A, Verma M, Gunduz M. Cancer Biomarkers: Minimal and Noninvasive Early Diagnosis and Prognosis. 1st Edition (2017) CRC Press
• Series Editors: Cohen IR, Lajtha A, Lambris JD, Pailetti R, Rezaei N. Advances in Experimental Medicine and Biology. Springer Nature International Publishing AG. ISSN: 0065-2598
• Twyman, R. M. Principles of Proteomics, 2nd Edition (2013), Garland Science, New York
• Lovaric, J. Introducing Proteomics (2011), Wiley-Blackwell, Hoboken, New Jersey
Recommended literature:
• Goh W.W., Wong, L. Computational proteomics: designing a comprehensive analytical strategy. Drug Discov Today. 2014.
Additional study materials
Way of continuous check of knowledge in the course of semester
Continuous monitoring of study activities and assigned tasks during regular consultations. If some publication activity will be a part of the student's tasks, the relevant article would be presented in the course.
Oral exam.
E-learning
Other requirements
The student prepares and presents the work on a given topic.
Prerequisities
Subject has no prerequisities.
Co-requisities
Subject has no co-requisities.
Subject syllabus:
• biomarkers and their use in medicine
• validation and verification of biomarkers
• the use of proteomics and proteome analyzes in clinical applications
• identification and characterization of proteins (detection methods, de novo sequencing, significance testing, post-translational modifications, protein folding and degradation, protein complexes)
• qualitative and quantitative protein analysis, protein detection methods
• protein structure prediction, protein structure modeling
• clinically important proteins in health and disease
• selected chapters from clinical haemato-oncology and immunology, non-invasive biomarkers
• proteomic databases
• analysis and interpretation of data generated in proteomic experiments
Conditions for subject completion
Occurrence in study plans
Occurrence in special blocks
Assessment of instruction
Předmět neobsahuje žádné hodnocení.