Van-Heerden2023 - Chemical Features Identification for Stage-Specific Antimalarial Compounds

ABSTRACT: Prediction of the antimalarial potential of small molecules using data from various chemical libraries that were screened against the asexual and sexual (gametocyte) stages of the parasite. Several compounds’ molecular fingerprints were used to train machine learning models to recognize stage-specific active and inactive compounds. Model Type: Predictive machine learning model. Model Relevance: Probability of inhibition of the malaria parasite growth. Model Encoded by: Gemma Turon (Ersilia) Metadata Submitted in BioModels by: Zainab Ashimiyu-Abdusalam Implementation of this model code by Ersilia is available here: https://github.com/ersilia-os/eos80ch

SUBMITTER: Zainab Ashimiyu-Abdusalam  

PROVIDER: MODEL2403270002 | BioModels | 2024-03-28

REPOSITORIES: BioModels