| Machine learning in enzyme engineering S Mazurenko, Z Prokop, J Damborsky ACS Catalysis 10 (2), 1210-1223, 2019 | 383 | 2019 |
| FireProtDB: database of manually curated protein stability data J Stourac, J Dubrava, M Musil, J Horackova, J Damborsky, S Mazurenko, ... Nucleic acids research 49 (D1), D319-D324, 2021 | 115 | 2021 |
| Computer‐assisted engineering of hyperstable fibroblast growth factor 2 P Dvorak, D Bednar, P Vanacek, L Balek, L Eiselleova, V Stepankova, ... Biotechnology and bioengineering 115 (4), 850-862, 2018 | 77 | 2018 |
| Machine learning-guided protein engineering P Kouba, P Kohout, F Haddadi, A Bushuiev, R Samusevich, J Sedlar, ... ACS catalysis 13 (21), 13863-13895, 2023 | 74 | 2023 |
| Substrate inhibition by the blockage of product release and its control by tunnel engineering P Kokkonen, A Beier, S Mazurenko, J Damborsky, D Bednar, Z Prokop RSC chemical biology 2 (2), 645-655, 2021 | 67 | 2021 |
| Exploration of protein unfolding by modelling calorimetry data from reheating S Mazurenko, A Kunka, K Beerens, CM Johnson, J Damborsky, Z Prokop Scientific reports 7 (1), 16321, 2017 | 61 | 2017 |
| CalFitter: a web server for analysis of protein thermal denaturation data S Mazurenko, J Stourac, A Kunka, S Nedeljković, D Bednar, Z Prokop, ... Nucleic acids research 46 (W1), W344-W349, 2018 | 42 | 2018 |
| Predicting protein stability and solubility changes upon mutations: data perspective S Mazurenko ChemCatChem 12 (22), 5590-5598, 2020 | 34 | 2020 |
| Tools for computational design and high-throughput screening of therapeutic enzymes M Vasina, J Velecký, J Planas-Iglesias, SM Marques, J Skarupova, ... Advanced Drug Delivery Reviews 183, 114143, 2022 | 31 | 2022 |
| Evolutionary analysis as a powerful complement to energy calculations for protein stabilization K Beerens, S Mazurenko, A Kunka, SM Marques, N Hansen, M Musil, ... ACS Catalysis 8 (10), 9420-9428, 2018 | 29 | 2018 |
| Acceleration and global convergence of a first-order primal-dual method for nonconvex problems C Clason, S Mazurenko, T Valkonen SIAM Journal on Optimization 29 (1), 933-963, 2019 | 26 | 2019 |
| A differential equation for the gauge function of the star-shaped attainability set of a differential inclusion SS Mazurenko Doklady Mathematics 86, 476-479, 2012 | 25 | 2012 |
| Exploring new galaxies: Perspectives on the discovery of novel PET-degrading enzymes J Mican, J Da'san MM, W Liu, G Weber, S Mazurenko, UT Bornscheuer, ... Applied Catalysis B: Environmental 342, 123404, 2024 | 23 | 2024 |
| Advanced database mining of efficient haloalkane dehalogenases by sequence and structure bioinformatics and microfluidics M Vasina, P Vanacek, J Hon, D Kovar, H Faldynova, A Kunka, T Buryska, ... Chem Catalysis 2 (10), 2704-2725, 2022 | 23 | 2022 |
| SoluProtMutDB: A manually curated database of protein solubility changes upon mutations J Velecký, M Hamsikova, J Stourac, M Musil, J Damborsky, D Bednar, ... Computational and Structural Biotechnology Journal 20, 6339-6347, 2022 | 15 | 2022 |
| Primal–dual proximal splitting and generalized conjugation in non-smooth non-convex optimization C Clason, S Mazurenko, T Valkonen Applied Mathematics & Optimization 84 (2), 1239-1284, 2021 | 14 | 2021 |
| In-depth analysis of biocatalysts by microfluidics: An emerging source of data for machine learning M Vasina, D Kovar, J Damborsky, Y Ding, T Yang, A deMello, ... Biotechnology Advances 66, 108171, 2023 | 13 | 2023 |
| Development of fluorescent assay for monitoring of dehalogenase activity S Nevolova, E Manaskova, S Mazurenko, J Damborsky, Z Prokop Biotechnology Journal 14 (3), 1800144, 2019 | 13 | 2019 |
| Machine learning in enzyme engineering. ACS Catal 10: 1210–1223 S Mazurenko, Z Prokop, J Damborsky | 12 | 2020 |
| Learning to design protein-protein interactions with enhanced generalization A Bushuiev, R Bushuiev, P Kouba, A Filkin, M Gabrielova, M Gabriel, ... arXiv preprint arXiv:2310.18515, 2023 | 11 | 2023 |
