Ersilia Model Hub Identifier: eos5qya
4.9K
Bioactivity prediction of growth inhibition in Neisseria gonorrhoeae, trained as binary (active/inactive) classifiers from publicly available data in ChEMBL. Independent models are trained on multiple bioactivity datasets, corresponding to 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.
eos5qyaantimicrobial-activity-ngonorrhoeaeAnnotationActivity predictionGonorrheaNeisseria gonorrhoeaeGram-negative bacteria, Antimicrobial activity, ChEMBLCompound11FixedBelow are the Output Columns of the model:
| Name | Type | Direction | Description |
|---|---|---|---|
| chembl_dose_response_0 | float | high | Probability from sub-model trained on ChEMBL dose-response low-data catch-all pool of 47 assays (438 compounds). Recommended threshold: 0.554. |
LocalInternalAMD64, ARM642372087048.47Computational Performance (seconds):
39.1731.36711.65Other2026This 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 eos5qya
Then, you can serve, run and close the model as follows:
# serve the model
ersilia serve eos5qya
# 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
sha256:9333201db…
Size
3.5 GB
Last updated
about 2 months ago
docker pull ersiliaos/eos5qyaPulls:
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Last week