Bosc2021 - MAIP: a web service for predicting blood‐stage malaria inhibitors
Ontology highlight
ABSTRACT: Prediction of the antimalarial potential of small molecules. This model is an ensemble of smaller QSAR models trained on proprietary data from various sources, up to a total of >7M compounds. The training sets belong to Evotec, Johns Hopkins, MRCT, MMV - St. Jude, AZ, GSK, and St. Jude Vendor Library. The code and training data are not released, using this model posts predictions to the MAIP online server. The Ersilia Model Hub also offers MAIP-surrogate as a downloadable package for IP-sensitive queries.
Model Type: Predictive machine learning model.
Model Relevance: Predicts antimalarial activity.
Model Encoded by: Amna Ali (Ersilia)
Metadata Submitted in BioModels by: Zainab Ashimiyu-Abdusalam
Implementation of this model code by Ersilia is available here:
https://github.com/ersilia-os/eos4zfy
SUBMITTER:
Zainab Ashimiyu-Abdusalam
PROVIDER: MODEL2405210002 | BioModels | 2024-06-17
REPOSITORIES: BioModels
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