JOY: protein sequence-structure representation and analysis. - Kenji Mizuguchi; Charlotte M. Deane; Tom L. Blundell; Mark S. Johnson; John P. Overington (Bioinform., 1998)

Browsing the SLoop database of structurally classified loops connecting elements of protein secondary structure. - David F. Burke; Charlotte M. Deane; Tom L. Blundell (Bioinform., 2000)

SCORE: predicting the core of protein models. - Charlotte M. Deane; Quentin Kaas; Tom L. Blundell (Bioinform., 2001)

How old is your fold? - Henry F. Winstanley; Sanne Abeln; Charlotte M. Deane (ISMB (Supplement of Bioinformatics), 2005)

Modelling sequential protein folding under kinetic control. - Fabien P. E. Huard; Charlotte M. Deane; Graham R. Wood (ISMB (Supplement of Bioinformatics), 2006)

Protein protein interactions, evolutionary rate, abundance and age. - Ramazan Saeed; Charlotte M. Deane (BMC Bioinform., 2006)

Cotranslational protein folding - fact or fiction? - Charlotte M. Deane; Mingqiang Dong; Fabien P. E. Huard; Braddon K. Lance; Graham R. Wood (ISMB/ECCB (Supplement of Bioinformatics), 2007)

A statistical approach using network structure in the prediction of protein characteristics. - Pao-Yang Chen; Charlotte M. Deane; Gesine Reinert (Bioinform., 2007)

Linking evolution of protein structures through fragments. - Sanne Abeln; Charlotte M. Deane (BMC Syst. Biol., 2007)

Using the protein interaction network to predict protein folds without homology. - Ramazan Saeed; Charlotte M. Deane (BMC Syst. Biol., 2007)

Using Phylogeny to Improve Genome-Wide Distant Homology Recognition. - Sanne Abeln; Carlo Teubner; Charlotte M. Deane (PLoS Comput. Biol., 2007)

An assessment of the uses of homologous interactions. - Ramazan Saeed; Charlotte M. Deane (Bioinform., 2008)

Predicting and Validating Protein Interactions Using Network Structure. - Pao-Yang Chen; Charlotte M. Deane; Gesine Reinert (PLoS Comput. Biol., 2008)

Functionally guided alignment of protein interaction networks for module detection. - Waqar Ali; Charlotte M. Deane (Bioinform., 2009)

iMembrane: homology-based membrane-insertion of proteins. - Sebastian Kelm; Jiye Shi; Charlotte M. Deane (Bioinform., 2009)

MEDELLER: homology-based coordinate generation for membrane proteins. - Sebastian Kelm; Jiye Shi; Charlotte M. Deane (Bioinform., 2010)

Exploring the potential of template-based modelling. - Braddon K. Lance; Charlotte M. Deane; Graham R. Wood (Bioinform., 2010)

How threshold behaviour affects the use of subgraphs for network comparison. - Tiago Rito; Zi Wang; Charlotte M. Deane; Gesine Reinert (Bioinform., 2010)

Directionality in protein fold prediction. - Jonathan J. Ellis; Fabien P. E. Huard; Charlotte M. Deane; Sheenal Srivastava; Graham R. Wood (BMC Bioinform., 2010)

Deciphering chemotaxis pathways using cross species comparisons. - Rebecca Hamer; Pao-Yang Chen; Judith P. Armitage; Gesine Reinert; Charlotte M. Deane (BMC Syst. Biol., 2010)

The function of communities in protein interaction networks at multiple scales. - Anna C. F. Lewis; Nick S. Jones; Mason A. Porter; Charlotte M. Deane (BMC Syst. Biol., 2010)

Revisiting Date and Party Hubs: Novel Approaches to Role Assignment in Protein Interaction Networks. - Sumeet Agarwal; Charlotte M. Deane; Mason A. Porter; Nick S. Jones (PLoS Comput. Biol., 2010)

Environment specific substitution tables improve membrane protein alignment. - Jamie R. Hill; Sebastian Kelm; Jiye Shi; Charlotte M. Deane (Bioinform., 2011)

Producing High-Accuracy Lattice Models from Protein Atomic Coordinates Including Side Chains. - Martin Mann; Rhodri Saunders; Cameron Smith; Rolf Backofen; Charlotte M. Deane (Adv. Bioinformatics, 2012)

The Importance of Age and High Degree, in Protein-Protein Interaction Networks. - Tiago Rito; Charlotte M. Deane; Gesine Reinert (J. Comput. Biol., 2012)

Freely Available Conformer Generation Methods: How Good Are They? - Jean-Paul Ebejer; Garrett M. Morris; Charlotte M. Deane (J. Chem. Inf. Model., 2012)

What Evidence Is There for the Homology of Protein-Protein Interactions? - Anna C. F. Lewis; Nick S. Jones; Mason A. Porter; Charlotte M. Deane (PLoS Comput. Biol., 2012)

MP-T: improving membrane protein alignment for structure prediction. - Jamie R. Hill; Charlotte M. Deane (Bioinform., 2013)

Memoir: template-based structure prediction for membrane proteins. - Jean-Paul Ebejer; Jamie R. Hill; Sebastian Kelm; Jiye Shi; Charlotte M. Deane (Nucleic Acids Res., 2013)

Exploring Fold Space Preferences of New-born and Ancient Protein Superfamilies. - Hannah Edwards; Sanne Abeln; Charlotte M. Deane (PLoS Comput. Biol., 2013)

Alignment-free protein interaction network comparison. - Waqar Ali; Tiago Rito; Gesine Reinert; Fengzhu Sun; Charlotte M. Deane (Bioinform., 2014)

Improving B-cell epitope prediction and its application to global antibody-antigen docking. - Konrad Krawczyk; Xiaofeng Liu; Terry Baker; Jiye Shi; Charlotte M. Deane (Bioinform., 2014)

Gro2mat: A package to efficiently read gromacs output in MATLAB. - Hung Dien; Charlotte M. Deane; Bernhard Knapp (J. Comput. Chem., 2014)

OOMMPPAA: A Tool To Aid Directed Synthesis by the Combined Analysis of Activity and Structural Data. - Anthony R. Bradley; Ian D. Wall; Darren V. S. Green; Charlotte M. Deane; Brian D. Marsden (J. Chem. Inf. Model., 2014)

Crowdsourcing Yields a New Standard for Kinks in Protein Helices. - Henry R. Wilman; Jean-Paul Ebejer; Jiye Shi; Charlotte M. Deane; Bernhard Knapp (J. Chem. Inf. Model., 2014)

SAbDab: the structural antibody database. - James Dunbar; Konrad Krawczyk; Jinwoo Leem; Terry Baker; Angelika Fuchs; Guy Georges; Jiye Shi; Charlotte M. Deane (Nucleic Acids Res., 2014)

Examining Variable Domain Orientations in Antigen Receptors Gives Insight into TCR-Like Antibody Design. - James Dunbar; Bernhard Knapp; Angelika Fuchs; Jiye Shi; Charlotte M. Deane (PLoS Comput. Biol., 2014)

Large Scale Characterization of the LC13 TCR and HLA-B8 Structural Landscape in Reaction to 172 Altered Peptide Ligands: A Molecular Dynamics Simulation Study. - Bernhard Knapp; James Dunbar; Charlotte M. Deane (PLoS Comput. Biol., 2014)

Ten Simple Rules for Effective Computational Research. - James M. Osborne; Miguel O. Bernabeu; Maria Bruna; Ben Calderhead; Jonathan Cooper; Neil Dalchau; Sara-Jane Dunn; Alexander G. Fletcher; Robin Freeman; Derek Groen; Bernhard Knapp; Greg J. McInerny; et al. (PLoS Comput. Biol., 2014)

Current status and future challenges in T-cell receptor/peptide/MHC molecular dynamics simulations. - Bernhard Knapp; Samuel Demharter; Reyhaneh Esmaielbeiki; Charlotte M. Deane (Briefings Bioinform., 2015)

WONKA: objective novel complex analysis for ensembles of protein-ligand structures. - Anthony R. Bradley; Ian D. Wall; Frank von Delft; Darren V. S. Green; Charlotte M. Deane; Brian D. Marsden (J. Comput. Aided Mol. Des., 2015)

Structural Bridges through Fold Space. - Hannah Edwards; Charlotte M. Deane (PLoS Comput. Biol., 2015)

Ten Simple Rules for a Successful Cross-Disciplinary Collaboration. - Bernhard Knapp; Rémi Bardenet; Miguel O. Bernabeu; Rafel Bordas; Maria Bruna; Ben Calderhead; Jonathan Cooper; Alexander G. Fletcher; Derek Groen; Bram Kuijper; Joanna Lewis; Greg J. McInerny; et al. (PLoS Comput. Biol., 2015)

Progress and challenges in predicting protein interfaces. - Reyhaneh Esmaielbeiki; Konrad Krawczyk; Bernhard Knapp; Jean-Christophe Nebel; Charlotte M. Deane (Briefings Bioinform., 2016)

ANARCI: antigen receptor numbering and receptor classification. - James Dunbar; Charlotte M. Deane (Bioinform., 2016)

Exploring peptide/MHC detachment processes using hierarchical natural move Monte Carlo. - Bernhard Knapp; Samuel Demharter; Charlotte M. Deane; Peter Minary (Bioinform., 2016)

T-Cell Receptor Binding Affects the Dynamics of the Peptide/MHC-I Complex. - Bernhard Knapp; Charlotte M. Deane (J. Chem. Inf. Model., 2016)

Tertiary Element Interaction in HIV-1 TAR. - Konrad Krawczyk; Adelene Y. L. Sim; Bernhard Knapp; Charlotte M. Deane; Peter Minary (J. Chem. Inf. Model., 2016)

SAbPred: a structure-based antibody prediction server. - James Dunbar; Konrad Krawczyk; Jinwoo Leem; Claire Marks; Jaroslaw Nowak; Cristian Regep; Guy Georges; Sebastian Kelm; Bojana Popovic; Charlotte M. Deane (Nucleic Acids Res., 2016)

Sphinx: merging knowledge-based and ab initio approaches to improve protein loop prediction. - Claire Marks; Jaroslaw Nowak; Stefan Klostermann; Guy Georges; James Dunbar; Jiye Shi; Sebastian Kelm; Charlotte M. Deane (Bioinform., 2017)

Comparing co-evolution methods and their application to template-free protein structure prediction. - Saulo Henrique Pires de Oliveira; Jiye Shi; Charlotte M. Deane (Bioinform., 2017)

Ten simple rules for surviving an interdisciplinary PhD. - Samuel Demharter; Nicholas Pearce; Kylie Beattie; Isabel Frost; Jinwoo Leem; Alistair Martin; Robert Oppenheimer; Cristian Regep; Tammo Rukat; Alexander Skates; Nicola Trendel; David J. Gavaghan; et al. (PLoS Comput. Biol., 2017)

pyHVis3D: visualising molecular simulation deduced H-bond networks in 3D: application to T-cell receptor interactions. - Bernhard Knapp; Marta Alcalá; Hao Zhang; Clare E. West; P. Anton van der Merwe; Charlotte M. Deane (Bioinform., 2018)

In silico structural modeling of multiple epigenetic marks on DNA. - Konrad Krawczyk; Samuel Demharter; Bernhard Knapp; Charlotte M. Deane; Peter Minary (Bioinform., 2018)

CommWalker: correctly evaluating modules in molecular networks in light of annotation bias. - Malte Lücken; M. J. T. Page; A. J. Crosby; S. Mason; Gesine Reinert; Charlotte M. Deane (Bioinform., 2018)

Predicting loop conformational ensembles. - Claire Marks; Jiye Shi; Charlotte M. Deane (Bioinform., 2018)

Combining co-evolution and secondary structure prediction to improve fragment library generation. - Saulo Henrique Pires de Oliveira; Charlotte M. Deane (Bioinform., 2018)

Sequential search leads to faster, more efficient fragment-based de novo protein structure prediction. - Saulo Henrique Pires de Oliveira; Eleanor C. Law; Jiye Shi; Charlotte M. Deane (Bioinform., 2018)

Identifying networks with common organizational principles. - Anatol E. Wegner; Luis Ospina-Forero; Robert E. Gaunt; Charlotte M. Deane; Gesine Reinert (J. Complex Networks, 2018)

Protein Family-Specific Models Using Deep Neural Networks and Transfer Learning Improve Virtual Screening and Highlight the Need for More Data. - Fergus Imrie; Anthony R. Bradley; Mihaela van der Schaar; Charlotte M. Deane (J. Chem. Inf. Model., 2018)

STCRDab: the structural T-cell receptor database. - Jinwoo Leem; Saulo Henrique Pires de Oliveira; Konrad Krawczyk; Charlotte M. Deane (Nucleic Acids Res., 2018)

Increasing the accuracy of protein loop structure prediction with evolutionary constraints. - Claire Marks; Charlotte M. Deane (Bioinform., 2019)

SCALOP: sequence-based antibody canonical loop structure annotation. - Wing Ki Wong; Guy Georges; Francesca Ros; Sebastian Kelm; Alan P. Lewis; Bruck Taddese; Jinwoo Leem; Charlotte M. Deane (Bioinform., 2019)

Measuring rank robustness in scored protein interaction networks. - Lyuba V. Bozhilova; Alan Whitmore; Jonny Wray; Gesine Reinert; Charlotte M. Deane (BMC Bioinform., 2019)

Assessment of model fit via network comparison methods based on subgraph counts. - Luis Ospina-Forero; Charlotte M. Deane; Gesine Reinert (J. Complex Networks, 2019)

HLA-DM Stabilizes the Empty MHCII Binding Groove: A Model Using Customized Natural Move Monte Carlo. - Samuel Demharter; Bernhard Knapp; Charlotte M. Deane; Peter Minary (J. Chem. Inf. Model., 2019)

Ligity: A Non-Superpositional, Knowledge-Based Approach to Virtual Screening. - Jean-Paul Ebejer; Paul W. Finn; Wing Ki Wong; Charlotte M. Deane; Garrett M. Morris (J. Chem. Inf. Model., 2019)

MHC binding affects the dynamics of different T-cell receptors in different ways. - Bernhard Knapp; P. Anton van der Merwe; Omer Dushek; Charlotte M. Deane (PLoS Comput. Biol., 2019)

Learning from the ligand: using ligand-based features to improve binding affinity prediction. - Fergus Boyles; Charlotte M. Deane; Garrett M. Morris (Bioinform., 2020)

The evolution of contact prediction: evidence that contact selection in statistical contact prediction is changing. - Mark Chonofsky; Saulo Henrique Pires de Oliveira; Konrad Krawczyk; Charlotte M. Deane (Bioinform., 2020)

TCRBuilder: multi-state T-cell receptor structure prediction. - Wing Ki Wong; Claire Marks; Jinwoo Leem; Alan P. Lewis; Jiye Shi; Charlotte M. Deane (Bioinform., 2020)

Deep Generative Models for 3D Linker Design. - Fergus Imrie; Anthony R. Bradley; Mihaela van der Schaar; Charlotte M. Deane (J. Chem. Inf. Model., 2020)

Data Set Augmentation Allows Deep Learning-Based Virtual Screening to Better Generalize to Unseen Target Classes and Highlight Important Binding Interactions. - Jack Scantlebury; Nathan Brown; Frank von Delft; Charlotte M. Deane (J. Chem. Inf. Model., 2020)

Thera-SAbDab: the Therapeutic Structural Antibody Database. - Matthew I. J. Raybould; Claire Marks; Alan P. Lewis; Jiye Shi; Alexander Bujotzek; Bruck Taddese; Charlotte M. Deane (Nucleic Acids Res., 2020)

Structural diversity of B-cell receptor repertoires along the B-cell differentiation axis in humans and mice. - Aleksandr Kovaltsuk; Matthew I. J. Raybould; Wing Ki Wong; Claire Marks; Sebastian Kelm; James Snowden; Johannes Trück; Charlotte M. Deane (PLoS Comput. Biol., 2020)

COGENT: evaluating the consistency of gene co-expression networks. - Lyuba V. Bozhilova; Javier Pardo-Diaz; Gesine Reinert; Charlotte M. Deane (Bioinform., 2021)

Generating property-matched decoy molecules using deep learning. - Fergus Imrie; Anthony R. Bradley; Charlotte M. Deane (Bioinform., 2021)

Humanization of antibodies using a machine learning approach on large-scale repertoire data. - Claire Marks; Alissa M. Hummer; Mark Chin; Charlotte M. Deane (Bioinform., 2021)

Ribosome occupancy profiles are conserved between structurally and evolutionarily related yeast domains. - Daniel A. Nissley; Anna Carbery; Mark Chonofsky; Charlotte M. Deane (Bioinform., 2021)

Robust gene coexpression networks using signed distance correlation. - Javier Pardo-Diaz; Lyuba V. Bozhilova; Mariano Beguerisse-Díaz; Philip S. Poole; Charlotte M. Deane; Gesine Reinert (Bioinform., 2021)

CoV-AbDab: the coronavirus antibody database. - Matthew I. J. Raybould; Aleksandr Kovaltsuk; Claire Marks; Charlotte M. Deane (Bioinform., 2021)

Co-evolutionary distance predictions contain flexibility information. - Dominik Schwarz; Guy Georges; Sebastian Kelm; Jiye Shi; Anna Vangone; Charlotte M. Deane (Bioinform., 2021)

Hypergraphs for predicting essential genes using multiprotein complex data. - Florian Klimm; Charlotte M. Deane; Gesine Reinert (J. Complex Networks, 2021)

Public Baseline and shared response structures support the theory of antibody repertoire functional commonality. - Matthew I. J. Raybould; Claire Marks; Aleksandr Kovaltsuk; Alan P. Lewis; Jiye Shi; Charlotte M. Deane (PLoS Comput. Biol., 2021)

Epitope profiling using computational structural modelling demonstrated on coronavirus-binding antibodies. - Sarah A. Robinson; Matthew I. J. Raybould; Constantin Schneider; Wing Ki Wong; Claire Marks; Charlotte M. Deane (PLoS Comput. Biol., 2021)

Ranking of communities in multiplex spatiotemporal models of brain dynamics. - James B. Wilsenach; Catherine E. Warnaby; Charlotte M. Deane; Gesine Reinert (Appl. Netw. Sci., 2022)

ABlooper: fast accurate antibody CDR loop structure prediction with accuracy estimation. - Brennan Abanades; Guy Georges; Alexander Bujotzek; Charlotte M. Deane (Bioinform., 2022)

Current structure predictors are not learning the physics of protein folding. - Carlos Outeiral; Daniel A. Nissley; Charlotte M. Deane (Bioinform., 2022)

DLAB: deep learning methods for structure-based virtual screening of antibodies. - Constantin Schneider; Andrew Buchanan; Bruck Taddese; Charlotte M. Deane (Bioinform., 2022)

Extracting Information from Gene Coexpression Networks of Rhizobium leguminosarum. - Javier Pardo-Diaz; Mariano Beguerisse-Díaz; Philip S. Poole; Charlotte M. Deane; Gesine Reinert (J. Comput. Biol., 2022)

Learning from Docked Ligands: Ligand-Based Features Rescue Structure-Based Scoring Functions When Trained on Docked Poses. - Fergus Boyles; Charlotte M. Deane; Garrett M. Morris (J. Chem. Inf. Model., 2022)

Incorporating Target-Specific Pharmacophoric Information into Deep Generative Models for Fragment Elaboration. - Thomas E. Hadfield; Fergus Imrie; Andy Merritt; Kristian Birchall; Charlotte M. Deane (J. Chem. Inf. Model., 2022)

SAbDab in the age of biotherapeutics: updates including SAbDab-nano, the nanobody structure tracker. - Constantin Schneider; Matthew I. J. Raybould; Charlotte M. Deane (Nucleic Acids Res., 2022)

Generating weighted and thresholded gene coexpression networks using signed distance correlation. - Javier Pardo-Diaz; Philip S. Poole; Mariano Beguerisse-Díaz; Charlotte M. Deane; Gesine Reinert (Netw. Sci., 2022)

Computationally profiling peptide:MHC recognition by T-cell receptors and T-cell receptor-mimetic antibodies. - Matthew I. J. Raybould; Daniel A. Nissley; Sandeep Kumar; Charlotte M. Deane (Zenodo, 2022)

Computationally profiling peptide:MHC recognition by T-cell receptors and T-cell receptor-mimetic antibodies. - Matthew I. J. Raybould; Daniel A. Nissley; Sandeep Kumar; Charlotte M. Deane (Zenodo, 2022)

Drug Discovery under Covariate Shift with Domain-Informed Prior Distributions over Functions. - Leo Klarner; Tim G. J. Rudner; Michael Reutlinger; Torsten Schindler; Garrett M. Morris; Charlotte M. Deane; Yee Whye Teh (ICML, 2023)

Inverse folding for antibody sequence design using deep learning. - Frédéric A. Dreyer; Daniel Cutting; Constantin Schneider; Henry Kenlay; Charlotte M. Deane (CoRR, 2023)

Paragraph - antibody paratope prediction using graph neural networks with minimal feature vectors. - Lewis Chinery; Newton Wahome; Iain Moal; Charlotte M. Deane (Bioinform., 2023)

Testing the limits of SMILES-based de novo molecular generation with curriculum and deep reinforcement learning. - Maranga Mokaya; Fergus Imrie; Willem P. van Hoorn; Aleksandra Kalisz; Anthony R. Bradley; Charlotte M. Deane (Nat. Mac. Intell., 2023)

Prediction of polyspecificity from antibody sequence data by machine learning. - Szabolcs Elias; Clemens Wrzodek; Charlotte M. Deane; Alain C. Tissot; Stefan Klostermann; Francesca Ros (Frontiers Bioinform., 2023)

A Small Step Toward Generalizability: Training a Machine Learning Scoring Function for Structure-Based Virtual Screening. - Jack Scantlebury; Lucy Vost; Anna Carbery; Thomas E. Hadfield; Oliver M. Turnbull; Nathan Brown; Vijil Chenthamarakshan; Payel Das; Harold Grosjean; Frank von Delft; Charlotte M. Deane (J. Chem. Inf. Model., 2023)

Fragment Merging Using a Graph Database Samples Different Catalogue Space than Similarity Search. - Stephanie Wills; Ruben Sanchez-Garcia; Tim Dudgeon; Stephen D. Roughley; Andy Merritt; Roderick E. Hubbard; James Davidson; Frank von Delft; Charlotte M. Deane (J. Chem. Inf. Model., 2023)

PEP-Patch: Electrostatics in Protein-Protein Recognition, Specificity, and Antibody Developability. - Valentin J. Hoerschinger; Franz Waibl; Nancy D. Pomarici; Johannes R. Loeffler; Charlotte M. Deane; Guy Georges; Hubert Kettenberger; Monica L. Fernández-Quintero; Klaus R. Liedl (J. Chem. Inf. Model., 2023)

Exploring the ability of machine learning-based virtual screening models to identify the functional groups responsible for binding. - Thomas E. Hadfield; Jack Scantlebury; Charlotte M. Deane (J. Cheminformatics, 2023)

Kernel-Based Evaluation of Conditional Biological Sequence Models. - Pierre Glaser; Steffanie Paul; Alissa M. Hummer; Charlotte M. Deane; Debora Susan Marks; Alan Nawzad Amin (ICML, 2024)

Context-Guided Diffusion for Out-of-Distribution Molecular and Protein Design. - Leo Klarner; Tim G. J. Rudner; Garrett M. Morris; Charlotte M. Deane; Yee Whye Teh (ICML, 2024)

De novo antibody design with SE(3) diffusion. - Daniel Cutting; Frédéric A. Dreyer; David Errington; Constantin Schneider; Charlotte M. Deane (CoRR, 2024)

ABodyBuilder3: Improved and scalable antibody structure predictions. - Henry Kenlay; Frédéric A. Dreyer; Daniel Cutting; Daniel A. Nissley; Charlotte M. Deane (CoRR, 2024)

Codon language embeddings provide strong signals for use in protein engineering. - Carlos Outeiral; Charlotte M. Deane (Nat. Mac. Intell., 2024)

It is theoretically possible to avoid misfolding into non-covalent lasso entanglements using small molecule drugs. - Yang Jiang 004; Charlotte M. Deane; Garrett M. Morris; Edward P. O'Brien (PLoS Comput. Biol., 2024)

Large scale paired antibody language models. - Henry Kenlay; Frédéric A. Dreyer; Aleksandr Kovaltsuk; Dom Miketa; Douglas Pires; Charlotte M. Deane (PLoS Comput. Biol., 2024)

The future of machine learning for small-molecule drug discovery will be driven by data. - Guy Durant; Fergus Boyles; Kristian Birchall; Charlotte M. Deane (Nat. Comput. Sci., 2024)

Learnt representations of proteins can be used for accurate prediction of small molecule binding sites on experimentally determined and predicted protein structures. - Anna Carbery; Martin Buttenschoen; Rachael Skyner; Frank von Delft; Charlotte M. Deane (J. Cheminformatics, 2024)

STCRpy: a software suite for T-cell receptor structure parsing, interaction profiling, and machine learning dataset preparation. - Nele P. Quast; Charlotte M. Deane; Matthew I. J. Raybould (Bioinform., 2025)

De Novo Antibody Design with SE(3) Diffusion. - Daniel Cutting; Frédéric A. Dreyer; David Errington; Constantin Schneider; Charlotte M. Deane (J. Comput. Biol., 2025)

MolSnapper: Conditioning Diffusion for Structure-Based Drug Design. - Yael Ziv; Fergus Imrie; Brian D. Marsden; Charlotte M. Deane (J. Chem. Inf. Model., 2025)

Transformers trained on proteins can learn to attend to Euclidean distance. - Isaac Ellmen; Constantin Schneider; Matthew I. J. Raybould; Charlotte M. Deane (Trans. Mach. Learn. Res., 2025)

Assessing the Chemical Intelligence of Large Language Models. - Nicholas T. Runcie; Charlotte M. Deane; Fergus Imrie (CoRR, 2025)

Investigating the volume and diversity of data needed for generalizable antibody-antigen ΔΔG prediction. - Alissa M. Hummer; Constantin Schneider; Lewis Chinery; Charlotte M. Deane (Nat. Comput. Sci., 2025)

Fragmenstein: predicting protein-ligand structures of compounds derived from known crystallographic fragment hits using a strict conserved-binding-based methodology. - Matteo P. Ferla; Ruben Sanchez-Garcia; Rachael Skyner; Stefan Gahbauer; Jenny C. Taylor; Frank von Delft; Brian D. Marsden; Charlotte M. Deane (J. Cheminformatics, 2025)