by Marina Chenery | Oct 19, 2021 | General, Publications and presentations
In this article, the team demonstrates the application of Alchemite™, a deep learning imputation method which underpins our Cerella™ technology, to physicochemical and sensory data. They compare the deep learning model with traditional QSAR models, demonstrating...
by Marina Chenery | May 20, 2021 | General, Publications and presentations
This Open Access paper outlines practical applications of deep imputation on large-scale drug discovery data. It compares deep learning to traditional QSAR methods. Find out more about deep imputation by visiting our Cerella webpage. Summary Accurately predicting...
by Marina Chenery | Jun 2, 2020 | General, Metabolism, Publications and presentations
This paper describes methods for modelling two enzyme families, flavin-containing monoxygenases (FMOs) and uridine 5′-diphospho-glucuronosyltransferases (UGTs), to predict reactivity to drug metabolism. It builds on the metabolism modelling methods within the...
by Marina Chenery | Apr 20, 2018 | General, Publications and presentations
Translating Methods from Pharma to Fragrances and Flavours Tamsin Mansley gave this presentation at the ACS National Spring Meeting 2018 in New Orleans. Abstract The pharma sector has generated a wealth of experience in cheminformatics methods that are used in the...
by Marina Chenery | Mar 7, 2018 | General, Publications and presentations
Pistoia Alliance AI/Deep Learning Projects and Community At our Drug Discovery Consultants’ Day in March 2018, Nick Lynch gave an overview of the Pistoia Alliances’ projects and community on AI and Deep Learning, including discussions around best practices...
by Marina Chenery | Apr 15, 2016 | General, Publications and presentations
User-friendly Database Querying for Decision-Making in Drug Discovery This poster was presented by Chris Leeding, Ed Champness, Chris Mills*, Andrew Lemon*, Ashley Fenwick$ and Matt Segall at BioIT World Expo and Meeting in April 2016. * – The Edge Software...