Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Rong2020 - Grover-qm8: Prediction of the electronic spectra and excited state energy of small molecules.

ABSTRACT: This model has been trained using the GROVER embedding with the QM8 dataset from Molecule Net, where the electronic properties have been calculated by multiple quantum mechanic methods. Model Type: Molecular properties prediction ML model. Model Relevance: Predicts electronic spectra and excited state energy of small molecules. Model Encoded by: Amna Ali (Ersilia) Metadata Submitted in BioModels by: Zainab Ashimiyu-Abdusalam Implementation of this model code by Ersilia is available here: https://github.com/ersilia-os/eos3xip

SUBMITTER: Zainab Ashimiyu-Abdusalam

PROVIDER: MODEL2406040002 | BioModels | 2024-06-04

REPOSITORIES: BioModels

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
	MODEL2406040002?filename=BioModelsMetadata%20-%20eos3xip.csv	Csv

Items per page:

1 - 1 of 1

Similar Datasets

Rong2020 - Grover-QM7: Atomization energy prediction of small molecules.

Project description:This model has been trained using the GROVER embedding with the QM7 dataset from MoleculeNet, a subset of GDB13 containing all molecules up to 23 atoms (7 heavy atoms + C, S, O, N). This dataset contains the computed atomization energy of 7165 molecules. Model Type: Molecular properties prediction ML model. Model Relevance: Predicts the atomization energy of a molecule. Model Encoded by: Amna Ali (Ersilia) Metadata Submitted in BioModels by: Zainab Ashimiyu-Abdusalam Implementation of this model code by Ersilia is available here: https://github.com/ersilia-os/eos6o0z

2024-06-04 | MODEL2406040003 | BioModels

Rong2020 - Grover-Lipo: Octanol/water distribution coefficient

Project description:This model has been trained using the GROVER embedding with the Lipophilicity Molecule Net dataset. Model Type: Molecular properties prediction ML model. Model Relevance: Predicts octanol/water distribution coefficient. Model Encoded by: Amna Ali (Ersilia) Metadata Submitted in BioModels by: Zainab Ashimiyu-Abdusalam Implementation of this model code by Ersilia is available here: https://github.com/ersilia-os/eos85a3

2024-06-04 | MODEL2406040004 | BioModels

Rong2020 - Grover-Esol: Prediction of water solubility (log solubility in mols per litre) for common organic small molecules

Project description:This model has been trained using the GROVER embedding and the Molecule Net ESOL dataset. . Model Type: Molecular properties prediction ML model. Model Relevance: Predicts Log Solubility. Model Encoded by: Amna Ali (Ersilia) Metadata Submitted in BioModels by: Zainab Ashimiyu-Abdusalam Implementation of this model code by Ersilia is available here: https://github.com/ersilia-os/eos8451

2024-06-04 | MODEL2406040005 | BioModels

Rong2020 - Grover-Freesolv: Experimental and calculated hydration free energy of small molecules in water

Project description:This model has been trained using the GROVER embedding and the the FreeSolv dataset from MoleculeNet. The Model is based on experimental and calculated hydration free energy of small molecules in water and Hydration free energies are relevant to understand the binding interaction between a molecule (in solution) into its binding site. Model Type: Molecular properties prediction ML model. Model Relevance: Predicts Calculated Hydration Free energy. Model Encoded by: Amna Ali (Ersilia) Metadata Submitted in BioModels by: Zainab Ashimiyu-Abdusalam Implementation of this model code by Ersilia is available here: https://github.com/ersilia-os/eos157v

2024-06-05 | MODEL2406050001 | BioModels

Rong2020 - Grover-embedding: A self-supervised Graph Neural Network for molecular representation

Project description:This is the base grover model. GROVER is a self-supervised Graph Neural Network for molecular representation pretrained with 10 million unlabelled molecules from ChEMBL and ZINC15, and has been fine-tuned to predict several activities from the MoleculeNet benchmark. Model Type: Representative machine learning model. Model Relevance: Performs embedding representation of a molecule Model Encoded by: Amna Ali (Ersilia) Metadata Submitted in BioModels by: Zainab Ashimiyu-Abdusalam Implementation of this model code by Ersilia is available here: https://github.com/ersilia-os/eos7w6n

2024-06-05 | MODEL2406050006 | BioModels

Rong2020 - Grover-Toxcast: Probability of toxicity against 617 biological targets

Project description:This model has been trained using the GROVER embedding and performs prediction across the ToxCast toxicity panel, containing hundreds of toxicity outcomes, as part of the MoleculeNet benchmark. Model Type: Predicitive machine learning model. Model Relevance: Predicts Probability of toxicity against 617 biological targets. Model Encoded by: Amna Ali (Ersilia) Metadata Submitted in BioModels by: Zainab Ashimiyu-Abdusalam Implementation of this model code by Ersilia is available here: https://github.com/ersilia-os/eos481p

2024-06-05 | MODEL2406050002 | BioModels

Rong2020 - Grover-bbbp: Prediction of the Blood-brain barrier penetration.

Project description:This model predicts the Blood-Brain Barrier (BBB) penetration potential of small molecules using as training data the curated MoleculeNet benchmark containing 2000 experimental data points. It has been trained using the GROVER transformer. Model Type: Predicitive machine learning model. Model Relevance: Predicts Probability that a molecule crosses the blood brain barrier. Model Encoded by: Amna Ali (Ersilia) Metadata Submitted in BioModels by: Zainab Ashimiyu-Abdusalam Implementation of this model code by Ersilia is available here: https://github.com/ersilia-os/eos1amr

2024-06-05 | MODEL2406050008 | BioModels

Rong2020 - Grover-tox21: Predicts activity of compounds accross the Tox21 panel.

Project description:This model has been trained using the GROVER transformer and Predicts activity of compounds in the Tox21 toxicity panel, comprising of 12 toxicity pathways, as part of the MoleculeNet benchmark datasets. Model Type: Predicitive machine learning model. Model Relevance: Toxicity measurements against 12 biological targets. Model Encoded by: Amna Ali (Ersilia) Metadata Submitted in BioModels by: Zainab Ashimiyu-Abdusalam Implementation of this model code by Ersilia is available here: https://github.com/ersilia-os/eos5smc

2024-06-05 | MODEL2406050005 | BioModels

Rong2020 - Grover-Bace: Prediction of Beta-secretase 1 (BACE-1) inhibition.

Project description:Prediction of Beta-secretase 1 (BACE-1) inhibition. BACE-1 is expressed mainly in neurons and has been involved in the development of Alzheimer's disease. This model has been trained on the BACE dataset from MoleculeNet using the GROVER transformer. Model Type: Predicitive machine learning model. Model Relevance: Probability that the molecule is a BACE-1 inhibitor. Model Encoded by: Amna Ali (Ersilia) Metadata Submitted in BioModels by: Zainab Ashimiyu-Abdusalam Implementation of this model code by Ersilia is available here: https://github.com/ersilia-os/eos2mhp

2024-06-05 | MODEL2406050003 | BioModels

Rong2020 - Grover-sider: Prediction of the putative adverse drug reactions (ADR) of a molecule

Project description:The model predicts the putative adverse drug reactions (ADR) of a molecule, using the SIDER database (MoleculeNet) that contains pairs of marketed drugs and their described ADRs.This model has been trained using the GROVER transformer Model Type: Predicitive machine learning model. Model Relevance: Predicts adverse drug reactions (ADR) of a molecule Model Encoded by: Amna Ali (Ersilia) Metadata Submitted in BioModels by: Zainab Ashimiyu-Abdusalam Implementation of this model code by Ersilia is available here: https://github.com/ersilia-os/eos77w8

2024-06-05 | MODEL2406050007 | BioModels