Asset Detail:

Autoencoder for MD Simulation Data (P2B1)

Asset Detail:

Autoencoder for MD Simulation Data (P2B1)
Overview
ASSET LINK: https://modac.cancer.gov/assetDetails?dme_data_id=NCI-DME-MS01-7681692
PROGRAM NAME: NCI-DOE Collaboration
STUDY NAME: NCI-DOE-Collaboration ADMIRRAL project: Improving Outcomes for RAS-related Cancers
ASSET NAME: Autoencoder for MD Simulation Data (P2B1)
ASSET PATH: /NCI_DOE_Archive/JDACS4C/JDACS4C_Pilot_2/autoencoder_md_simulation_data_p2b1
Asset Attributes
  ATTRIBUTE VALUE
ASSET NAME Autoencoder for MD Simulation Data (P2B1)
ASSET DESCRIPTION This collection contains the model topology files and the trained model weights for the Autoencoder for MD Simulation Data (P2B1). P2B1 is an autoencoder for molecular dynamics (MD) simulation data that compresses the output of MD runs into a minimal set of features that can be used as tractable input into downstream algorithms. This collection includes the full autoencoder (p2b1.model.json), just the encoder part of the autoencoder (p2b1.encoder.json), and the corresponding trained model weights after two epochs (model_weights.hdf5 and encoder_weights.hdf5, respectively) as sample weights corresponding to the simulation input data. The autoencoder is a convolutional neural network. The authors of this model trained it on the MD output of a 3k disordered, 3-component-system (DPPC-DOPC-CHOL). They ran this model for two epochs by default, producing a converged reconstruction loss of ~0.0314. For more information, refer to the Simulation Input Data link and the GitHub Repository link.
ASSET IDENTIFIER autoencoder_md_simulation_data_p2b1
ASSET TYPE Model
DOI NA
MODEL DOMAIN Autoencoder
MODEL FRAMEWORK Keras
MODEL PLATFORM None
POC NAME Andrew Weisman
POC EMAIL andrew.weisman@nih.gov
IS MODEL DEPLOYED No
COLLECTION SIZE 101.5 MB
GITHUB REPOSITORY https://github.com/CBIIT/NCI-DOE-Collab-Pilot2-Autoencoder_MD_Simulation_Data
SIMULATION INPUT DATA https://modac.cancer.gov/searchTab?dme_data_id=NCI-DME-MS01-7654212

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