Predict the MIC of compounds against pathogenic bacteria
Predictions are from an AI model trained on the wild-type accumulator subset of the SPARK dataset, available to browse here.
Predictions are given in micromolar (µM) and µg/mL. You can optionally have uncertainty scores calculated. These can take a few minutes, so please be patient.
This model was generated using our Duvida framework, as a result of hyperparameter searches and selecting the model that performs best on unseen test data (from a scaffold split). Duvida also allows the calculation of uncertainty metrics based on training data.
Available species for prediction are:
- Acinetobacter baumannii
- Brucella abortus
- Escherichia coli
- Francisella tularensis
- Klebsiella pneumoniae
- Pseudomonas aeruginosa
- Staphylococcus aureus
- Streptococcus pneumoniae
- Yersinia enterocolitica
- Yersinia pestis
Click on the links above for training details, model configurations, and evaluation metrics.
Examples
Input string format
Predictions (scroll left and right)
Examples
E. coli training data from Stokes J. et al., Cell (2020)
A. baumannii training data from Liu G., Nature Chemical Biology (2023)
S. aureus training data from Wong F., Nature (2024)
Drop File Here - or - Click to Upload
Input column name
Input string format
Species 1 for prediction
Species 2 for prediction
Input data
Observed column (y-axis) for left plot
Color for left plot
x-axis for right plot
y-axis for right plot
Color for right plot
Textbox
Textbox