Ersilia Model Hub Identifier: eos4an7
6.6K
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 2026-10-06.
eos4an7antimicrobial-activity-pfalciparumAnnotationActivity predictionMalariaPlasmodium falciparumProtozoa, Antiparasitic activity, Antimicrobial activity, ChEMBLCompound152FixedBelow are the Output Columns of the model:
| Name | Type | Direction | Description |
|---|---|---|---|
| consensus_score | float | high | Quality-weighted consensus across the 51 sub-models on the same rank scale as the sub-models. Calibrated against a reference library of 50K drug-like molecules so that a score of 0.65 is better than 99% of them. Recommended threshold: 0.65. |
| chembl_single_point_0 | float | high | Probability from sub-model trained on ChEMBL single-point signal-based pool of 19 assays (147560 compounds). Recommended threshold: 0.65. |
| chembl_single_point_1 | float | high | Probability from sub-model trained on ChEMBL single-point signal-based pool of 13 assays (55965 compounds). Recommended threshold: 0.65. |
| chembl_single_point_2 | float | high | Probability from sub-model trained on ChEMBL single-point signal-based pool of 20 assays (33900 compounds). Recommended threshold: 0.65. |
| chembl_single_point_3 | float | high | Probability from sub-model trained on ChEMBL single-point signal-based pool of 21 assays (20662 compounds). Recommended threshold: 0.65. |
| chembl_single_point_4 | float | high | Probability from sub-model trained on ChEMBL single-point signal-based pool of 16 assays (15912 compounds; incl. 2438 added negatives). Recommended threshold: 0.65. |
| chembl_single_point_5 | float | high | Probability from sub-model trained on ChEMBL single-point signal-based pool of 20 assays (603 compounds). Recommended threshold: 0.65. |
| chembl_single_point_6 | float | high | Probability from sub-model trained on ChEMBL single-point signal-based pool of 16 assays (250 compounds; incl. 6 added negatives). Recommended threshold: 0.65. |
| chembl_dose_response_00 | float | high | Probability from sub-model trained on ChEMBL dose-response signal-based pool of 173 assays (29588 compounds; incl. 14148 added negatives). Recommended threshold: 0.65. |
| chembl_dose_response_01 | float | high | Probability from sub-model trained on ChEMBL dose-response signal-based pool of 869 assays (13456 compounds; incl. 3418 added negatives). Recommended threshold: 0.65. |
10 of 52 columns are shown
LocalInternalAMD64, ARM642772798211093.44Computational Performance (seconds):
104.81108.21-1Other2026This 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 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
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Content type
Image
Digest
sha256:0004257ac…
Size
5 GB
Last updated
5 days ago
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