Electrostatic interactions in aminoglycoside-RNA complexes M Kulik, AM Goral, M Jasiński, PM Dominiak, J Trylska Biophysical Journal 108 (3), 655-665, 2015 | 43 | 2015 |
Rossmann-toolbox: a deep learning-based protocol for the prediction and design of cofactor specificity in Rossmann fold proteins K Kamiński, J Ludwiczak, M Jasiński, A Bukala, R Madaj, K Szczepaniak, ... Briefings in bioinformatics 23 (1), bbab371, 2022 | 30 | 2022 |
MINT: software to identify motifs and short-range interactions in trajectories of nucleic acids A Górska, M Jasiński, J Trylska Nucleic acids research 43 (17), e114-e114, 2015 | 28 | 2015 |
Thermal stability of peptide nucleic acid complexes M Jasiński, J Miszkiewicz, M Feig, J Trylska The Journal of Physical Chemistry B 123 (39), 8168-8177, 2019 | 23 | 2019 |
Improved Force Fields for Peptide Nucleic Acids with Optimized Backbone Torsion Parameters M Jasiński, M Feig, J Trylska Journal of chemical theory and computation 14 (7), 3603–3620, 2018 | 20 | 2018 |
Thermodynamics of the fourU RNA thermal switch derived from molecular dynamics simulations and spectroscopic techniques F Leonarski, M Jasiński, J Trylska Biochimie 156, 22-32, 2019 | 6 | 2019 |
Interactions of 2'-O-methyl oligoribonucleotides with the RNA models of the 30S subunit A-site. M Jasiński, M Kulik, M Wojciechowska, R Stolarski, J Trylska PLoS One 13 (1), e0191138, 2018 | 4 | 2018 |
Revealing biophysical properties of KfrA-type proteins as a novel class of cytoskeletal, coiled-coil plasmid-encoded proteins M Adamczyk, E Lewicka, R Szatkowska, H Nieznanska, J Ludwiczak, ... BMC microbiology 21, 1-16, 2021 | 2 | 2021 |
ARDitox: platform for the prediction of TCRs potential off-target binding VM Pienkowski, T Boschert, P Skoczylas, A Sanecka-Duin, M Jasiński, ... bioRxiv, 2023.04. 11.536336, 2023 | 1 | 2023 |
Identification of tumor-specific MHC ligands through improved biochemical isolation and incorporation of machine learning S Mecklenbräuker, P Skoczylas, P Biernat, B Zaghla, B Król-Józaga, ... bioRxiv, 2023.06. 08.544182, 2023 | | 2023 |
Modeling pHLA: TCR interactions for effective TCR therapies: Leveraging AI and molecular dynamics A Myronov, S Stachura, A Sanecka-Duin, O Gniewek, Ł Grochowalski, ... Cancer Research 82 (12_Supplement), 2810-2810, 2022 | | 2022 |
827 Streamlining design of safe and effective TCR therapies with AI M Mizera, A Sanecka-Duin, M Jasiński, P Król, G Mazzocco, ... Journal for ImmunoTherapy of Cancer 9 (Suppl 2), 2021 | | 2021 |
Oddziaływanie syntetycznych oligomerów z rybosomowym RNA M Jasiński | | 2017 |
2P123 Bacterial ribosomal RNA as a target for sequence-specific inhibition (05A. Nucleic acid: Structure & Property, Poster) J Tyylska, SG Thoduka, Z Dabrowska, A Gorska, M Jasinski, T Witula Seibutsu Butsuri 53 (supplement1-2), S179, 2013 | | 2013 |
MINT software manual AGMJJ Trylska http://mint.cent.uw.edu.pl/, 2013 | | 2013 |
Targeting bacterial ribosomal RNA [p][p][p][p] J Trylska, J Romanowska, T Witula, S Thoduka, Z Dabrowska, M Jasinski, ... ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY 243, 2012 | | 2012 |
Symulacje dynamiki molekularnej oligomerów PNA M Jasiński, M Długosz, J Trylska peer-reviewed conference proceedings – I National Conference of Biophysics …, 2010 | | 2010 |
AI-based tools for target identification foster the generation of novel TCR hits against solid tumor antigens A Sanecka-Duin, P Biernat, W Czarnocka, K Dudaniec, O Gniewek, ... | | |
MINT: software to identify motifs and short-range interactions in trajectories of nucleic acids Supplementary Data A Górska, M Jasinski, J Trylska | | |