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61 to 70 of 21,098 Results
Studying Dynamical Systems for Intelligible Modeling and Unconventional Computing(Universität Stuttgart)
May 20, 2026PN 6
We investigate computation through the lens of dynamical systems, unifying physical processes and machine learning. By treating both hardware and algorithms as evolving dynamical systems, we leverage natural physical dynamics - such as relaxation to stable states and phase transitions - as a foundation for robust, efficient computation. Our work sh...
Supplementary Material for "Refinement of CHARMM36m force field parameters for protein phosphorylation by force-matching"
May 11, 2026 - PN 3-11
Korn, Viktoria Helena; Pluhackova, Kristyna, 2026, "Supplementary Material for "Refinement of CHARMM36m force field parameters for protein phosphorylation by force-matching"", https://doi.org/10.18419/DARUS-5682, DaRUS, V2
GROMACS simulation files, input and final structures for CHARMM36m MD simulations including our refined parameters for phosphorylated serine in 3 different protonation states. The directory charmm36-jul22mod.ff contains our refined parameters.
charmm36-jul2022mod.ff.zip
May 11, 2026 - Supplementary Material for "Refinement of CHARMM36m force field parameters for protein phosphorylation by force-matching"
ZIP Archive - 1.1 MB - MD5: e5e758a42a7a04a3af52bd2a3746f599
Ready-to-use CHARMM36m force field with our parameters for phosphorylated aminoacids
charmm_toppar_mod.zip
May 11, 2026 - Supplementary Material for "Refinement of CHARMM36m force field parameters for protein phosphorylation by force-matching"
ZIP Archive - 1.4 MB - MD5: 10d788673880f41321b528dd43b8b042
Patched CHARMM36m force field files for CHARMM with our parameters
nmr_MD_sims.zip
May 11, 2026 - Supplementary Material for "Refinement of CHARMM36m force field parameters for protein phosphorylation by force-matching"
ZIP Archive - 19.4 GB - MD5: bd30ce5c884d7dda4d9bb1b00d847840
DATA
MD sims for calculating relaxation times and Excel sheet with all datapoints, including experimental values.
osmotic_experimental.zip
May 11, 2026 - Supplementary Material for "Refinement of CHARMM36m force field parameters for protein phosphorylation by force-matching"
ZIP Archive - 53.9 KB - MD5: b871e4cc529a90ef9fc5fa93bf225b63
Measured osmotic concentration values for MPA and MAM
osmotic_mp2_ions_MD_sims.zip
May 11, 2026 - Supplementary Material for "Refinement of CHARMM36m force field parameters for protein phosphorylation by force-matching"
ZIP Archive - 12.0 GB - MD5: e87671fc468f8473d2071eb6cbfab36a
DATA
osmotic pressure simulations of MP2 with sodium and guanidinium. Also simulations of MP2 with original charmm params scaled to -1 and MP2-1MAM with charge shifted from P to C
protein_simulations.zip
May 11, 2026 - Supplementary Material for "Refinement of CHARMM36m force field parameters for protein phosphorylation by force-matching"
ZIP Archive - 45.5 MB - MD5: 56a4af1e874bb6a8c90083dc1b152582
Anti-Sigma Factor Antagonist SpoIIAA simulations wild type and phosphorylated
Replication Data for: Fine-Tuning Large Language Models for JSON Schema Generation and Modification
May 8, 2026 - Usability and Sustainability of Simulation Software
Sajith, Durga Lakshmi, 2026, "Replication Data for: Fine-Tuning Large Language Models for JSON Schema Generation and Modification", https://doi.org/10.18419/DARUS-5914, DaRUS, V1
This dataset contains a training dataset consisting of natural language description-JSON Schema pairs, which can be used to fine-tune LLMs and an evaluation dataset, which can be used to assess the JSON Schema generation capability of LLMs. The evaluation dataset consists of five categories with prompts and their corresponding ground truth schemas....
ambiguous.zip
May 8, 2026 - Replication Data for: Fine-Tuning Large Language Models for JSON Schema Generation and Modification
ZIP Archive - 6.6 KB - MD5: 99a99e66bc33da7d39153bf58c5fb02c
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