Structure-based detection of protein interaction sites with machine learning

• Thesis title in Czech: Využití strojového učerní k detekci interakčních míst proteinové struktury
• Thesis title in English: Structure-based detection of protein interaction sites with machine learning
• Key words: bioinformatika|molekulární interakce|strukutrní bioinformatika|strojové učení
• English key words: bioinformatics|molecular interaction|structural bioinformatics|machine learning
• Academic year of topic announcement: 2022/2023
• Thesis type: dissertation
• Thesis language: angličtina
• Department: Department of Software Engineering (32-KSI)
• Supervisor: doc. RNDr. David Hoksza, Ph.D.
• Author: hidden - assigned and confirmed by the Study Dept.
• Date of registration: 19.09.2022
• Date of assignment: 19.09.2022
• Confirmed by Study dept. on: 27.09.2022

Guidelines

Proteins, the primary building blocks of living systems, function by interacting with other molecules such as DNAs, RNAs, small molecules, or other proteins. Although at the most elementary level, the interactions are driven by the same physical forces, on a higher level, where the environment is captured by more abstract concepts such as amino acid type, shape, or even evolutionary conservation, the different interaction types are associated with different properties. The thesis aims to study these higher-level concepts and explore representations and machine learning approaches to capture these concepts and use them to detect interaction sites on yet unseen protein structures.

References

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[4] Koller, D., & Friedman, N. (2009). Probabilistic graphical models: principles and techniques. MIT press.
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