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Molecular Dynamics Inc machine learning-based methods
Machine Learning Based Methods, supplied by Molecular Dynamics Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/machine+learning-based+methods/machine+learning+approaches/pm37016530-49-5-0
Average 90 stars, based on 1 article reviews
machine learning-based methods - by Bioz Stars, 2026-09
90/100 stars

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Related Articles

Sampling:

Article Title: Reaction Coordinates for Conformational Transitions Using Linear Discriminant Analysis on Positions
Article Snippet: .. Recently, extensive effort has been invested in using a variety of machine learning approaches, from very simple to very sophisticated, to determine optimal coordinates for sampling from molecular dynamics (MD) simulation data (refs ( − ) provide a representative but not exhaustive sample). ..

Functional Assay:

Article Title: Synergy of Small Antiviral Molecules on a Black-Phosphorus Nanocarrier: Machine Learning and Quantum Chemical Simulation Insights
Article Snippet: .. We have systematically unveiled the interaction characteristics of inhibitor drugs on the surface of a phosphorene sheet by using accelerated molecular dynamics simulations, machine learning, and density functional theory calculations. ..

Sequencing:

Article Title: Dynamics of the charge transfer to solvent process in aqueous iodide.
Article Snippet: .. Through the combined use of ab initio molecular dynamics and machine learning methods, we investigate the structure, dynamics and free energy as the excited electron evolves through the chargetransfer-to-solvent process, which we characterize as a sequence of states denoted charge-transfer-to-solvent, contact-pair, solvent-separated, and hydrated electron states, depending on the distance between the iodine and the excited electron. ..

Article Title: Dynamics of the charge transfer to solvent process in aqueous iodide
Article Snippet: .. Through the combined use of ab initio molecular dynamics and machine learning methods, we investigate the structure, dynamics and free energy as the excited electron evolves through the charge-transfer-to-solvent process, which we characterize as a sequence of states denoted charge-transfer-to-solvent, contact-pair, solvent-separated, and hydrated electron states, depending on the distance between the iodine and the excited electron. ..

Solvent:

Article Title: Dynamics of the charge transfer to solvent process in aqueous iodide.
Article Snippet: .. Through the combined use of ab initio molecular dynamics and machine learning methods, we investigate the structure, dynamics and free energy as the excited electron evolves through the chargetransfer-to-solvent process, which we characterize as a sequence of states denoted charge-transfer-to-solvent, contact-pair, solvent-separated, and hydrated electron states, depending on the distance between the iodine and the excited electron. ..

Article Title: Dynamics of the charge transfer to solvent process in aqueous iodide
Article Snippet: .. Through the combined use of ab initio molecular dynamics and machine learning methods, we investigate the structure, dynamics and free energy as the excited electron evolves through the charge-transfer-to-solvent process, which we characterize as a sequence of states denoted charge-transfer-to-solvent, contact-pair, solvent-separated, and hydrated electron states, depending on the distance between the iodine and the excited electron. ..

Drug discovery:

Article Title: Therapeutic Peptides, Proteins and their Nanostructures for Drug Delivery and Precision Medicine.
Article Snippet: .. [166] Molecular dynamics simulations and other computational modeling and machine learning approaches, while still costly, have been already reported specifically in the field of nanomaterials design for drug discovery and precision medicine. ..

Clinical Proteomics:

Article Title: Therapeutic Peptides, Proteins and their Nanostructures for Drug Delivery and Precision Medicine.
Article Snippet: .. [166] Molecular dynamics simulations and other computational modeling and machine learning approaches, while still costly, have been already reported specifically in the field of nanomaterials design for drug discovery and precision medicine. ..

other:

Article Title: Transition1x - a dataset for building generalizable reactive machine learning potentials.
Article Snippet: Machine Learning (ML) models have, in contrast to their usefulness in molecular dynamics studies, had limited success as surrogate potentials for reaction barrier search.

Article Title: Novel Computational Methods for Cancer Drug Design.
Article Snippet: Department of Biotechnology, GITAM School of Technology, GITAM, Visakhapatnam, 530045, Andhra Pradesh, India; Institutes for Systems Genetics, Frontiers Science Center for Disease-related Molecular Network, , West China Hospital, Sichuan University, Chengdu, China; King Fahd Medical Research Center, King Abdulaziz University, Jeddah, Saudi Arabia; Department of Pharmacy, Faculty of Allied Health Sciences, Daffodil International University, Birulia, Bangladesh; Enzymoics, 7 Peterlee place, Hebersham, NSW 2770, Australia; Novel Global Community Educational Foundation, Hebersham, NSW 2770, Australia; Cancer Biology Laboratory, Department of Biochemistry, GITAM School of Science, GITAM, Visakhapatnam, 530045, Andhra Pradesh, India



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