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Data Dos and Don’ts In Building Statistical Models For Ames Mutagenicitypdf fileSarah Nexus
Using privacy-preserving federated learning to enable pre-competitive cross-industry knowledge sharing and improve QSAR modelspdf fileEffiris
QSAR 2021 - leveraging data from multiple sources to build QSARs through curation and federated learning in Effiris.pdf fileEffiris
Systematic analysis of protein targets associated with adverse events of drugs from clinical trials and postmarketing reports
Developing Federated QSAR Models for Secondary Pharmacologypdf file
Building Secondary Pharmacology Models: A Novel Approach to Proprietary Data Transfer.pdf fileEffiris
Building Secondary Pharmacology Models: A Novel Approach to Proprietary Data Transfer - RecordingEffiris
From Private Data to Shared Knowledgepdf fileEffiris
To Model or Not to Model? Posterpdf file
To Model or Not to Model? Presentationpdf file
Applicability Domain: Towards a More Formal Framework to Express the Applicability of a Model and the Confidence in Individual PredictionsDerek Nexus
A Case Study in Predicting hERG Activity using Multiple (Q)SARs and Data Sourcespdf fileEffiris
Avoiding hERG-liability in drug design via synergetic combinations of different (Q)SAR methodologies and data sources: a case study in an industrial settingSarah NexusDerek Nexus
Improvement of quantitative structure–activity relationship (QSAR) tools for predicting Ames mutagenicity: outcomes of the Ames/QSAR International Challenge ProjectDerek NexusSarah Nexus
Applicability Domain: Towards a more formal definitionpdf file
Applicability domain and confidence in predictions: Towards a more formal frameworkpdf file
Distinguishing between expert and statistical systems for application under ICH M7Derek NexusSarah Nexus
Applicability Domain: Towards a More Formal Definition
Evaluation Of A Statistics-based Ames Mutagenicity QSAR Model And Interpretation Of The Results ObtainedSarah Nexus
Self organising hypothesis networks: a new approach for representing and structuring SAR knowledgeSarah Nexus
Emerging Pattern Mining to Aid Toxicological Knowledge Discovery
Feature combination networks for the interpretation of statistical machine learning models: application to Ames mutagenicity

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