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TitlePublishedTypeProducts
A k-Nearest Neighbours Approach Using Metabolism-related Fingerprints to Improve In Silico Metabolite RankingMeteor NexusSarah Nexus
A quantitative in silico model for predicting skin sensitization using a nearest neighbours approach within expert-derived structure–activity alert spacesDerek Nexus
Assessing confidence in predictions made by knowledge-based systemsDerek Nexus
Beyond adverse outcome pathways: making toxicity predictions from event networks, SAR models, data and knowledgeKaptis
Capturing and curating in vitro data from diverse sources to support MIE investigation for hepatotoxicitypdf file
Data Dos and Don’ts In Building Statistical Models For Ames Mutagenicitypdf fileSarah Nexus
Development of a network of carcinogenicity adverse outcome pathways and its employment as an evidence framework for safety assessmentKaptis
Emerging Pattern Mining to Aid Toxicological Knowledge Discovery
Establishing best practise in the application of expert review of mutagenicity under ICH M7Derek NexusSarah Nexus
Evaluation Of A Statistics-based Ames Mutagenicity QSAR Model And Interpretation Of The Results ObtainedSarah Nexus
Feature combination networks for the interpretation of statistical machine learning models: application to Ames mutagenicity
Investigation of an in vitro hepatotoxicity dataset to search for co-occurrence of signals amongst assays.pdf file
Modeling the Mutagenic Potential of Primary Aminespdf file
New structural alerts for Ames mutagenicity discovered using emerging pattern mining techniquesDerek Nexus
Prediction of the effect of formulation on the toxicity of chemicals
Self organising hypothesis networks: a new approach for representing and structuring SAR knowledgeSarah Nexus
Using random forest and decision tree models for a new vehicle prediction approach in computational toxicology

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