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ersiliaos/eos9bpi

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By Ersilia Open Source Initiative

Updated about 2 months ago

Ersilia Model Hub Identifier: eos9bpi

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ersiliaos/eos9bpi repository overview

Antimicrobial activity prediction against Enterobacter spp. from public ChEMBL data

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.

Information

Identifiers
  • Ersilia Identifier: eos9bpi
  • Slug: antimicrobial-activity-enterobacter
Domain
  • Task: Annotation
  • Subtask: Activity prediction
  • Biomedical Area: Antimicrobial resistance
  • Target Organism: Enterobacter spp
  • Tags: Gram-negative bacteria, Antimicrobial activity, ChEMBL
Input
  • Input: Compound
  • Input Dimension: 1
Output
  • Output Dimension: 6
  • Output Consistency: Fixed
  • Interpretation: Probability of antimicrobial activity against Enterobacter spp. from 5 ChEMBL-trained sub-models, plus a quality-weighted consensus score.

Below are the Output Columns of the model:

NameTypeDirectionDescription
consensus_scorefloathighTanh-transformed quality-weighted consensus probability across the 5 sub-models. Recommended threshold: 0.637.
chembl_single_point_0floathighProbability 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_0floathighProbability from sub-model trained on ChEMBL dose-response signal-based pool of 77 assays (1284 compounds). Recommended threshold: 0.498.
chembl_dose_response_1floathighProbability from sub-model trained on ChEMBL dose-response signal-based pool of 111 assays (1281 compounds). Recommended threshold: 0.699.
chembl_dose_response_2floathighProbability 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_3floathighProbability from sub-model trained on ChEMBL dose-response signal-based pool of 65 assays (492 compounds; incl. 91 added negatives). Recommended threshold: 0.51.
Source and Deployment
Resource Consumption
  • Model Size (Mb): 47
  • Environment Size (Mb): 7208
  • Image Size (Mb): 7257.47

Computational Performance (seconds):

  • 10 inputs: 52.97
  • 100 inputs: 38.7
  • 10000 inputs: 970.09
References
License

This 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.

Use

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

About Ersilia

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!

Tag summary

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Image

Digest

sha256:4f93e3464

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3.7 GB

Last updated

about 2 months ago

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