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ChemProp |

ChemProp: Property Training

6
Drug Design
    More
Step 1: Upload your data

Upload a training dataset file

Drag your file(s) or upload
  • Your file can be in the following formats:csv
    • File must contain 'SMILES' and 'Molecular Property' columns respectively. Rows in first column represents molecules in SMILES format and rows in second column represent property: 0 (False) or 1 (True).
or
Don’t have a file?
Use our demo data to run
Use Demo Data
View example data

Upload a File for Prediction

Drag your file(s) or upload
  • Your file can be in the following formats:csv
    • File should contain only 'SMILES' column. Rows represents molecules in SMILES format that will be used in prediction phase.
or
Don’t have a file?
Use our demo data to run
Use Demo Data
View example data
Step 2: Set Parameters
0.100
0.200
0.900
rdkit_2d_normalized
Classification
1
10
100
1
1
100

Classification model training for molecular property prediction by analyzing learned molecular representations

Example use case: drug toxicity prediction during lead generation

Technology: Message passing neural networks

Citation:
Yang et al., Analyzing Learned Molecular Representations for Property Prediction, Journal of Chemical Information and Modeling 2019 59 (8), 3370-3388, DOI: 10.1021/acs.jcim.9b00237
Released:
Sep-29-2022
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Parameters