Poster Presentations
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- “Mondrian Conformal Prediction – Confidence Predictions with Excellent Handling of Imbalanced Data”; Fredrik Svensson, University of Cambridge and IOTA Pharmaceuticals
- “Predicting Ligand-Protein binding affinities in Leucyl-tRNA Synthetases”; Grace Edmund, Oxford Drug Design
- “Active search for computer-aided drug design”; Steven Oatley, University of Nottingham
- “Augmenting De novo Drug Design using Reaction Classification”; Gianmarco Ghiandoni, University of Sheffield
- “Machine Learning: Predicting Chemical Ames Mutagenicity”; Charmaine Chu, University of Liverpool
- “On the mechanisms of DNA G-quadruplexes targeting by gold(I) N-heterocyclic compounds: new insights by combined meta-dynamics and biophysical methods”; Darren Wragg, University of Cardiff
- “Using advanced computational methods to model the binding of flexible proteins: a case study from the coagulation cascade”; Martin Rosellen, UCL
- “WhichP450 – A Multi-class Categorical Model to Predict the Major Metabolising CYP450 Isoform for a Compound”; Peter Hunt, Optibrium Ltd.
- “Water Networks and Topological Data Analysis: A Data Science Approach to Understanding Intermolecular Structures”; Lee Steinberg, University of Southampton
- “Comparison of multitask prediction methods for chemical data”; Antonio de la Vega de Leon, University of Sheffield
- “Investigating the importance of solid state descriptors for statistical models of temperature dependent aqueous solubility”; Richard Marchese Robinson, University of Leeds
- “Meta-QSAR: a large-scale application of meta-learning to drug design and discovery”; Ivan Olier, Liverpool John Moores University
- “DL_ANALYSER Notation for Atomic Interactions (DANAI): A Natural Annotation System for Molecular Interactions, Using Carboxylic Acids as Test Cases”; Chin Yong, STFC Daresbury Laboratory and University of Manchester
- “G-protein coupled receptor-KNIME Automated Modelling Platform (GPCR_KAMP)”; Ajay Pal, Dublin Institute of Technology
- “From exploration to exploitation: how do QSAR models depict trends during lead optimisation?”; Chris Luscombe and David Marcus, Glaxo SmithKline
- “Adaptation of a Matched Molecular Pair Identification Algorithm for Solid State Informatics Analysis of the Cambridge Structural Database”; Jakub Janowiak, University of Leeds
- “The mechanism of aquaporin inhibition by gold compounds elucidated by biophysical and computational methods”; Andreia de Almeida, University of Cardiff
- “Regression conformal prediction of ADME data using error models for normalisation”; Christina Founti, University of Sheffield
- “Application of quantum mechanics and/or structural fingerprinting for the prediction of glutathione conjugation site-specificity?”; Martin Payne, LHASA Ltd.
- “Conformational variation from a spectral geometry perspective”; Matthew Seddon, University of Sheffield
- “Large-scale comparison between robust methods for QSAR”; Phillippa McCabe, Liverpool John Moores University
- “Modelling ChEMBL protein targets using conformal prediction”; Nicolas Bosc, EBI