Vít Škrhák
PhD student
Vít is a researcher with a background in software engineering. His current research focus revolves around the development of innovative tools for exploring conformation changes in protein structures with special emphasis on detecting cryptic binding sites that are observable only after those conformation changes.
Courses
Latest publications
- Protein Language Models and Structure-Based Machine Learning for Prediction of Allosteric Binding Sites in Protein Kinases: An Explainable AI Framework Grounded in Energy Landscape-Encoded Frustration (2026)
- Predicting and Decoding Allosteric Binding Sites Using Protein Language Models and Structure-Based Machine Learning: An Energy Landscape-Guided Explainable AI Framework (2026)
- Beyond Exact Matches: Near-Hit Scoring for Protein Binding Site Prediction with Protein Language Models (2025)
- Hidden in protein sequences: Predicting cryptic binding sites (2025)
- CryptoBench: cryptic protein--ligand binding sites dataset and benchmark (2025)
- Cryptic binding site prediction with protein language models (2023)
- Evaluating a Bayesian-like relevance feedback model with text-to-image search initialization (2023)
- Rank-sensitive proportional aggregations in dynamic recommendation scenarios (2022)
- W2VV++ BERT model at VBS 2021 (2021)