Ersilia Model Hub Identifier: eos9bpi
5.2K
Bioactivity prediction of growth inhibition in Enterobacter spp., trained as binary (active/inactive) classifiers from publicly available data in ChEMBL. Independent models are trained on multiple bioactivity datasets, corresponding to single-point (ACTIVITY) 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.
eos9bpiantimicrobial-activity-enterobacterAnnotationActivity predictionAntimicrobial resistanceEnterobacter sppGram-negative bacteria, Antimicrobial activity, ChEMBLCompound16FixedBelow are the Output Columns of the model:
| Name | Type | Direction | Description |
|---|---|---|---|
| consensus_score | float | high | Tanh-transformed quality-weighted consensus probability across the 5 sub-models. Recommended threshold: 0.637. |
| chembl_single_point_0 | float | high | Probability from sub-model trained on ChEMBL single-point low-data catch-all pool of 39 assays (191 compounds). Recommended threshold: 0.705. |
| chembl_dose_response_0 | float | high | Probability from sub-model trained on ChEMBL dose-response signal-based pool of 77 assays (1284 compounds). Recommended threshold: 0.498. |
| chembl_dose_response_1 | float | high | Probability from sub-model trained on ChEMBL dose-response signal-based pool of 111 assays (1281 compounds). Recommended threshold: 0.699. |
| chembl_dose_response_2 | float | high | Probability from sub-model trained on ChEMBL dose-response signal-based pool of 67 assays (634 compounds; incl. 132 added negatives). Recommended threshold: 0.563. |
| chembl_dose_response_3 | float | high | Probability from sub-model trained on ChEMBL dose-response signal-based pool of 65 assays (492 compounds; incl. 91 added negatives). Recommended threshold: 0.51. |
LocalInternalAMD64, ARM644772087257.47Computational Performance (seconds):
52.9738.7970.09Other2026This 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 eos9bpi
Then, you can serve, run and close the model as follows:
# serve the model
ersilia serve eos9bpi
# 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
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Content type
Image
Digest
sha256:4f93e3464…
Size
3.7 GB
Last updated
about 2 months ago
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Last week