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Autor principal: Lazzeri, Gianmarco
Formato: Recurso digital
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Publicado: Zenodo 2025
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Acceso en línea:https://doi.org/10.5281/zenodo.14830224
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_version_ 1866902228857520128
author Lazzeri, Gianmarco
author_facet Lazzeri, Gianmarco
contents <p>This repository contains the trajectory files of the RFPS-AIMMD run "fps2" on chignolin. It includes the two-way shooting paths and the free simulations around state A and state B. </p> <p>Due to size constraints, the data has been split into separate repositories. </p> <p>The trajectory files are not required for running the main analysis, as all necessary information for machine learning and path reweighting is contained in the "PatEnsemble" object files stored in the main repository. However, these trajectories are essential for projecting the path ensemble estimate onto an arbitrary set of collective variables.</p> <p>To reconstruct the full dataset, please merge the data folder from the main repository with the one you find here.</p> <h2>Data structure and content</h2> <p>data<br>|- chignolin<br>   |- fps2 (the RFPS-AIMMD run)<br>      |- equilibriumA (the trajectory data for the free simulations around A)<br>         |- traj000001.part0000.xtc<br>         |- traj000001.part0001.xtc<br>         |- ...<br>         |- traj000002.part0000.xtc<br>         |- ...<br>      |- equilibriumB (the trajectory data for the free simulations around B)<br>         |- ...<br>      |- shots0 (the path sampling chain, with the paths in order)<br>         |- path000001.xtc<br>         |- path000002.xtc<br>         |- ...</p> <p> </p>
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institution Zenodo
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publishDate 2025
publisher Zenodo
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spellingShingle Simulation data for "Optimal Rejection-Free Path Sampling". Trajectory files of the chignolin RFPS-AIMMD run "fps2"
Lazzeri, Gianmarco
path sampling
Statistical mechanics
Molecular Dynamics Simulation
Artificial intelligence
Active learning
Protein folding
rare events
Biochemistry
<p>This repository contains the trajectory files of the RFPS-AIMMD run "fps2" on chignolin. It includes the two-way shooting paths and the free simulations around state A and state B. </p> <p>Due to size constraints, the data has been split into separate repositories. </p> <p>The trajectory files are not required for running the main analysis, as all necessary information for machine learning and path reweighting is contained in the "PatEnsemble" object files stored in the main repository. However, these trajectories are essential for projecting the path ensemble estimate onto an arbitrary set of collective variables.</p> <p>To reconstruct the full dataset, please merge the data folder from the main repository with the one you find here.</p> <h2>Data structure and content</h2> <p>data<br>|- chignolin<br>   |- fps2 (the RFPS-AIMMD run)<br>      |- equilibriumA (the trajectory data for the free simulations around A)<br>         |- traj000001.part0000.xtc<br>         |- traj000001.part0001.xtc<br>         |- ...<br>         |- traj000002.part0000.xtc<br>         |- ...<br>      |- equilibriumB (the trajectory data for the free simulations around B)<br>         |- ...<br>      |- shots0 (the path sampling chain, with the paths in order)<br>         |- path000001.xtc<br>         |- path000002.xtc<br>         |- ...</p> <p> </p>
title Simulation data for "Optimal Rejection-Free Path Sampling". Trajectory files of the chignolin RFPS-AIMMD run "fps2"
topic path sampling
Statistical mechanics
Molecular Dynamics Simulation
Artificial intelligence
Active learning
Protein folding
rare events
Biochemistry
url https://doi.org/10.5281/zenodo.14830224