Ersilia Model Hub Identifier: eos8jx6
5.3K
Bioactivity prediction of growth inhibition in Candida albicans, trained as binary (active/inactive) classifiers from publicly available data in ChEMBL and PubChem. Independent models are trained on multiple bioactivity datasets, corresponding to single-point (Inhibition) and dose-response (MIC) assays, among others. A ranking score is provided for each model alongside a combined consensus score.
This model was incorporated on 2026-05-19.Last packaged on 2026-07-22.
eos8jx6antimicrobial-activity-calbicansAnnotationActivity predictionCandidiasisCandida albicansAntimicrobial activity, ChEMBLCompound118FixedBelow are the Output Columns of the model:
| Name | Type | Direction | Description |
|---|---|---|---|
| consensus_score | float | high | Tanh-transformed quality-weighted consensus probability across the 17 sub-models. Recommended threshold: 0.897. |
| chembl_single_point_0 | float | high | Probability from sub-model trained on ChEMBL single-point signal-based pool of 174 assays (1717 compounds). Recommended threshold: 0.773. |
| chembl_single_point_1 | float | high | Probability from sub-model trained on ChEMBL single-point signal-based pool of 69 assays (949 compounds). Recommended threshold: 0.713. |
| chembl_single_point_2 | float | high | Probability from sub-model trained on ChEMBL single-point signal-based pool of 101 assays (842 compounds). Recommended threshold: 0.614. |
| chembl_single_point_3 | float | high | Probability from sub-model trained on ChEMBL single-point signal-based pool of 86 assays (695 compounds). Recommended threshold: 0.679. |
| chembl_single_point_4 | float | high | Probability from sub-model trained on ChEMBL single-point signal-based pool of 82 assays (627 compounds). Recommended threshold: 0.666. |
| chembl_dose_response_0 | float | high | Probability from sub-model trained on ChEMBL dose-response signal-based pool of 612 assays (7988 compounds). Recommended threshold: 0.782. |
| chembl_dose_response_1 | float | high | Probability from sub-model trained on ChEMBL dose-response signal-based pool of 628 assays (7670 compounds). Recommended threshold: 0.737. |
| chembl_dose_response_2 | float | high | Probability from sub-model trained on ChEMBL dose-response signal-based pool of 345 assays (4640 compounds). Recommended threshold: 0.678. |
| chembl_dose_response_3 | float | high | Probability from sub-model trained on ChEMBL dose-response signal-based pool of 79 assays (2490 compounds; incl. 88 added negatives). Recommended threshold: 0.468. |
10 of 18 columns are shown
LocalInternalAMD64, ARM6461572087952.88Computational Performance (seconds):
81.5482.49-1Other2026This package is licensed under a GPL-3.0 license. The model contained within this package is licensed under a GPL-3.0-or-later license.
Notice: Ersilia grants access to models as is, directly from the original authors, please refer to the original code repository and/or publication if you use the model in your research.
To use this model locally, you need to have the Ersilia CLI installed. The model can be fetched using the following command:
# fetch model from the Ersilia Model Hub
ersilia fetch eos8jx6
Then, you can serve, run and close the model as follows:
# serve the model
ersilia serve eos8jx6
# generate an example file
ersilia example -n 3 -f my_input.csv
# run the model
ersilia run -i my_input.csv -o my_output.csv
# close the model
ersilia close
The Ersilia Open Source Initiative is a tech non-profit organization fueling sustainable research in the Global South. Please cite the Ersilia Model Hub if you've found this model to be useful. Always let us know if you experience any issues while trying to run it. If you want to contribute to our mission, consider donating to Ersilia!
Content type
Image
Digest
sha256:908d7348c…
Size
3.9 GB
Last updated
2 months ago
docker pull ersiliaos/eos8jx6Pulls:
35
Last week