Merget2013 - Mycobacterium tuberculosis permeability prediction tool
Ontology highlight
ABSTRACT: MycPermCheck predicts potential to permeate the Mycobacterium tuberculosis cell membrane based on physicochemical properties. Due to the lack of reliable experimental datapoints, the authors defined the training set using molecules that are active against M.tb.
Model Type: Predictive machine learning model.
Model Relevance: Probability of permeability across the M.tb cell wall.
Model Encoded by: Miquel Duran-Frigola (Ersilia)
Metadata Submitted in BioModels by: Zainab Ashimiyu-Abdusalam
Implementation of this model code by Ersilia is available here:
https://github.com/ersilia-os/eos8d8a
SUBMITTER:
Zainab Ashimiyu-Abdusalam
PROVIDER: MODEL2405210004 | BioModels | 2024-05-21
REPOSITORIES: BioModels
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