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Project:
ADMIRRAL
Description:
Performs “dynamic” sampling where the input distribution can change over time and the sampling adapts itself to the new distribution.
DESCRIPTION:
Performs “dynamic” sampling where the input distribution can change over time and the sampling adapts itself to the new distribution.
IMPACT: Enables machine learning-based adaptive multiscale simulations for cancer biology.
INPUT DATA TYPE: NumPy Arrays
INPUT DATA FORMAT: Unspecified
LEVEL OF DOCUMENTATION: Minimal
AVAILABLE ON GITHUB
Project:
ADMIRRAL
Description:
Supports very large and multiscale simulations of molecular dynamic interactions between proteins (or their domains) with each other or with cell membranes.
DESCRIPTION:
Supports very large and multiscale simulations of molecular dynamic interactions between proteins (or their domains) with each other or with cell membranes.
IMPACT: Produces data like KRas4B Campaign 1 Trajectory data for use in models.
PRIMARY PUBLICATION: Machine Learning–driven Multiscale Modeling Reveals Lipid-dependent Dynamics of RAS Signaling Proteins
INPUT DATA FORMAT: Unspecified
LEVEL OF DOCUMENTATION: Minimal
AVAILABLE ON GITHUB
Project:
ADMIRRAL
Description:
Computes and analyzes membrane surfaces found in a wide variety of large-scale molecular simulations. MemSurfer works independent of the type of simulation, directly on the 3D point coordinates.
DESCRIPTION:
Computes and analyzes membrane surfaces found in a wide variety of large-scale molecular simulations. MemSurfer works independent of the type of simulation, directly on the 3D point coordinates.
IMPACT:
Enables assessment of lipid membrane curvature and density.
Allows counting of normal lipids and area per lipid.
Provides a simple-to-use Python API to perform other types of analysis.
PRIMARY PUBLICATION: MemSurfer: A Tool for Robust Computation and Characterization of Curved Membranes
INPUT DATA TYPE: Membrane Data
INPUT DATA FORMAT: Unspecified
LEVEL OF DOCUMENTATION: Minimal
AVAILABLE ON GITHUB