The predictive performances of MC4PC were evaluated using its learning machine functionality. Its superior characteristics are demonstrated in this following up study using the newly published Ames mutagenicity benchmark set.
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Article Synopsis
- In human health risk assessment, genotoxicity hazards of chemicals typically start with a set of in vitro tests, but these tests don't capture all potential genotoxic endpoints, leading to sometimes contradictory results.
- Mathematical modeling can improve the interpretation of these tests by accounting for each test's strengths and weaknesses, providing objective predictions with associated uncertainties.
- A study found that combining a mammalian in vitro clastogenicity test and a gene mutation test offers strong evidence for genotoxic hazard assessment, but the bacterial reverse mutation (Ames) test alone can still provide useful evidence when no other data is available.
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