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Machine learning coarse-grained potentials of protein thermodynamics

Project: ScaleCell

Updated at: 31-07-2024

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Project acronym ScaleCell

Statistically optimal force aggregation for coarse-graining molecular dynamics

Project: ScaleCell

Updated at: 31-07-2024

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Project acronym ScaleCell

Structure prediction of protein-ligand complexes from sequence information with Umol

Project: ScaleCell

Updated at: 31-07-2024

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Project acronym ScaleCell

Stochastic Approximation to MBAR and TRAM: Batchwise Free Energy Estimation

Project: ScaleCell

Updated at: 31-07-2024

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Project acronym ScaleCell

Coupling of Conformational Switches in Calcium Sensor Unraveled with Local Markov Models and Transfer Entropy

Project: ScaleCell

Updated at: 27-04-2024

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Project acronym ScaleCell

Neuraldecipher – reverse-engineering extended-connectivity fingerprints (ECFPs) to their molecular structures

Project: ScaleCell

Updated at: 27-04-2024

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Project acronym ScaleCell

Neural mode jump Monte Carlo

Project: ScaleCell

Updated at: 27-04-2024

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Project acronym ScaleCell

Large-scale simulation of biomembranes incorporating realistic kinetics into coarse-grained models

Project: ScaleCell

Updated at: 27-04-2024

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Project acronym ScaleCell

Ensemble learning of coarse-grained molecular dynamics force fields with a kernel approach

Project: ScaleCell

Updated at: 27-04-2024

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Project acronym ScaleCell

Stochastic Normalizing Flows

Project: ScaleCell

Updated at: 27-04-2024

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Project acronym ScaleCell

The mechanism of RNA base fraying: Molecular dynamics simulations analyzed with core-set Markov state models

Project: ScaleCell

Updated at: 27-04-2024

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Project acronym ScaleCell

OpenPathSampling: A Python Framework for Path Sampling Simulations. 1. Basics

Project: ScaleCell

Updated at: 27-04-2024

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Project acronym ScaleCell

Molecular mechanism of inhibiting the SARS-CoV-2 cell entry facilitator TMPRSS2 with camostat and nafamostat

Project: ScaleCell

Updated at: 27-04-2024

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Project acronym ScaleCell

Markov Models of Molecular Kinetics

Project: ScaleCell

Updated at: 27-04-2024

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Project acronym ScaleCell

Equivariant Flows: Exact Likelihood Generative Learning for Symmetric Densities

Project: ScaleCell

Updated at: 27-04-2024

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Project acronym ScaleCell

Periodic Reporting for period 3 - ScaleCell (Scalable Kinetic Models: From Molecular Dynamics to Cellular Signaling)

Project: ScaleCell

Updated at: 27-04-2024

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Project acronym ScaleCell

Efficient multi-objective molecular optimization in a continuous latent space

Project: ScaleCell

Updated at: 27-04-2024

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Project acronym ScaleCell

Deep Generative Markov State Models

Project: ScaleCell

Updated at: 27-04-2024

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Project acronym ScaleCell

Polymer-like Model to Study the Dynamics of Dynamin Filaments on Deformable Membrane Tubes

Project: ScaleCell

Updated at: 27-04-2024

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Project acronym ScaleCell

Kernel methods for detecting coherent structures in dynamical data

Project: ScaleCell

Updated at: 27-04-2024

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Project acronym ScaleCell

Identification of kinetic order parameters for non-equilibrium dynamics

Project: ScaleCell

Updated at: 27-04-2024

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Project acronym ScaleCell

Variational selection of features for molecular kinetics

Project: ScaleCell

Updated at: 27-04-2024

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Project acronym ScaleCell

Diffusion-influenced reaction rates in the presence of pair interactions

Project: ScaleCell

Updated at: 27-04-2024

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Project acronym ScaleCell

Collective hydrogen-bond rearrangement dynamics in liquid water

Project: ScaleCell

Updated at: 27-04-2024

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Project acronym ScaleCell

Nanoscale coupling of endocytic pit growth and stability

Project: ScaleCell

Updated at: 27-04-2024

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Project acronym ScaleCell

Targeted Adversarial Learning Optimized Sampling

Project: ScaleCell

Updated at: 27-04-2024

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Project acronym ScaleCell

What Markov State Models Can and Cannot Do: Correlation versus Path-Based Observables in Protein-Folding Models

Project: ScaleCell

Updated at: 27-04-2024

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Project acronym ScaleCell

Structure and assembly of the mitochondrial membrane remodelling GTPase Mgm1

Project: ScaleCell

Updated at: 27-04-2024

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Project acronym ScaleCell

Learning continuous and data-driven molecular descriptors by translating equivalent chemical representations

Project: ScaleCell

Updated at: 27-04-2024

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Project acronym ScaleCell

Boltzmann generators: Sampling equilibrium states of many-body systems with deep learning

Project: ScaleCell

Updated at: 27-04-2024

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Project acronym ScaleCell

Resources

Selected filters:

Machine learning coarse-grained potentials of protein thermodynamics

Statistically optimal force aggregation for coarse-graining molecular dynamics

Structure prediction of protein-ligand complexes from sequence information with Umol

Stochastic Approximation to MBAR and TRAM: Batchwise Free Energy Estimation

Coupling of Conformational Switches in Calcium Sensor Unraveled with Local Markov Models and Transfer Entropy

Neuraldecipher – reverse-engineering extended-connectivity fingerprints (ECFPs) to their molecular structures

Neural mode jump Monte Carlo

Large-scale simulation of biomembranes incorporating realistic kinetics into coarse-grained models

Ensemble learning of coarse-grained molecular dynamics force fields with a kernel approach

Stochastic Normalizing Flows

The mechanism of RNA base fraying: Molecular dynamics simulations analyzed with core-set Markov state models

OpenPathSampling: A Python Framework for Path Sampling Simulations. 1. Basics

Molecular mechanism of inhibiting the SARS-CoV-2 cell entry facilitator TMPRSS2 with camostat and nafamostat

Markov Models of Molecular Kinetics

Equivariant Flows: Exact Likelihood Generative Learning for Symmetric Densities

Periodic Reporting for period 3 - ScaleCell (Scalable Kinetic Models: From Molecular Dynamics to Cellular Signaling)

Efficient multi-objective molecular optimization in a continuous latent space

Deep Generative Markov State Models

Polymer-like Model to Study the Dynamics of Dynamin Filaments on Deformable Membrane Tubes

Kernel methods for detecting coherent structures in dynamical data

Identification of kinetic order parameters for non-equilibrium dynamics

Variational selection of features for molecular kinetics

Diffusion-influenced reaction rates in the presence of pair interactions

Collective hydrogen-bond rearrangement dynamics in liquid water

Nanoscale coupling of endocytic pit growth and stability

Targeted Adversarial Learning Optimized Sampling

What Markov State Models Can and Cannot Do: Correlation versus Path-Based Observables in Protein-Folding Models

Structure and assembly of the mitochondrial membrane remodelling GTPase Mgm1

Learning continuous and data-driven molecular descriptors by translating equivalent chemical representations

Boltzmann generators: Sampling equilibrium states of many-body systems with deep learning