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ersiliaos/eos4an7

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By Ersilia Open Source Initiative

Updated about 2 months ago

Ersilia Model Hub Identifier: eos4an7

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ersiliaos/eos4an7 repository overview

Antimicrobial activity prediction against Plasmodium falciparum from public ChEMBL and PubChem data

Bioactivity prediction of growth inhibition in Plasmodium falciparum, 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.

Information

Identifiers
  • Ersilia Identifier: eos4an7
  • Slug: antimicrobial-activity-pfalciparum
Domain
  • Task: Annotation
  • Subtask: Activity prediction
  • Biomedical Area: Malaria
  • Target Organism: Plasmodium falciparum
  • Tags: Protozoa, Antiparasitic activity, Antimicrobial activity, ChEMBL
Input
  • Input: Compound
  • Input Dimension: 1
Output
  • Output Dimension: 52
  • Output Consistency: Fixed
  • Interpretation: Probability of antimicrobial activity against Plasmodium falciparum from 51 ChEMBL- and PubChem-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 51 sub-models. Recommended threshold: 0.639.
chembl_single_point_0floathighProbability from sub-model trained on ChEMBL single-point signal-based pool of 19 assays (147560 compounds). Recommended threshold: 0.852.
chembl_single_point_1floathighProbability from sub-model trained on ChEMBL single-point signal-based pool of 13 assays (55965 compounds). Recommended threshold: 0.844.
chembl_single_point_2floathighProbability from sub-model trained on ChEMBL single-point signal-based pool of 20 assays (33900 compounds). Recommended threshold: 0.848.
chembl_single_point_3floathighProbability from sub-model trained on ChEMBL single-point signal-based pool of 21 assays (20662 compounds). Recommended threshold: 0.978.
chembl_single_point_4floathighProbability from sub-model trained on ChEMBL single-point signal-based pool of 16 assays (15912 compounds; incl. 2438 added negatives). Recommended threshold: 0.479.
chembl_single_point_5floathighProbability from sub-model trained on ChEMBL single-point signal-based pool of 20 assays (603 compounds). Recommended threshold: 0.648.
chembl_single_point_6floathighProbability from sub-model trained on ChEMBL single-point signal-based pool of 16 assays (250 compounds; incl. 6 added negatives). Recommended threshold: 0.433.
chembl_dose_response_00floathighProbability from sub-model trained on ChEMBL dose-response signal-based pool of 173 assays (29588 compounds; incl. 14148 added negatives). Recommended threshold: 0.526.
chembl_dose_response_01floathighProbability from sub-model trained on ChEMBL dose-response signal-based pool of 869 assays (13456 compounds; incl. 3418 added negatives). Recommended threshold: 0.513.

10 of 52 columns are shown

Source and Deployment
Resource Consumption
  • Model Size (Mb): 2478
  • Environment Size (Mb): 7208
  • Image Size (Mb): 10242.18

Computational Performance (seconds):

  • 10 inputs: 99.15
  • 100 inputs: 112.47
  • 10000 inputs: -1
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 eos4an7

Then, you can serve, run and close the model as follows:

# serve the model
ersilia serve eos4an7
# 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:ae3d3b258

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4.6 GB

Last updated

about 2 months ago

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