C. Deane

发表

HOMSTRAD: A database of protein structure alignments for homologous families

John P. Overington, K. Mizuguchi, C. Deane, 1998, Protein science : a publication of the Protein Society.

Protein Interactions

C. Deane, D. Eisenberg, Łukasz Salwiński, 2002, Molecular & Cellular Proteomics.

An iterative structure‐assisted approach to sequence alignment and comparative modeling

K. Mizuguchi, C. Deane, T. Blundell, 1999, Proteins.

Structurally Mapping Antibody Repertoires

C. Deane, Jiye Shi, K. Krawczyk, 2018, Front. Immunol..

Antibody i-Patch prediction of the antibody binding site improves rigid local antibody-antigen docking.

C. Deane, Jiye Shi, K. Krawczyk, 2013, Protein engineering, design & selection : PEDS.

i‐Patch: Interprotein contact prediction using local network information

C. Deane, G. Reinert, J. Armitage, 2010, Proteins.

Antibody–antigen complex modelling in the era of immunoglobulin repertoire sequencing

C. Deane, W. K. Wong, M. Raybould, 2019, Molecular Systems Design & Engineering.

Observed Antibody Space: A Resource for Data Mining Next-Generation Sequencing of Antibody Repertoires

C. Deane, K. Krawczyk, S. Kelm, 2018, The Journal of Immunology.

CoV-AbDab: the Coronavirus Antibody Database

C. Deane, Aleksandr Kovaltsuk, M. Raybould, 2020, Bioinformatics.

Deep Sequencing of B Cell Receptor Repertoires From COVID-19 Patients Reveals Strong Convergent Immune Signatures

C. Deane, J. Dias, C. Caldas, 2020, bioRxiv.

Local Network Patterns in Protein-Protein Interfaces

Gesine Reinert, Charlotte M. Deane, Rebecca Hamer, 2013, PloS one.

Predicting Inter-Species Cross-Talk in Two-Component Signalling Systems

C. Deane, G. Wadhams, R. Hamer, 2012, PloS one.

Functional module detection through integration of single-cell RNA sequencing data with protein–protein interaction networks

C. Deane, G. Reinert, F. Klimm, 2020, BMC genomics.

Functional module detection through integration of single-cell RNA sequencing data with protein–protein interaction networks

Gesine Reinert, Charlotte M. Deane, Fang Zhang, 2019, BMC Genomics.

Misato Controls Mitotic Microtubule Generation by Stabilizing the Tubulin Chaperone Protein-1 Complex

C. Deane, K. B. Rogala, C. Pellacani, 2015, Current Biology.

A novel exhaustive search algorithm for predicting the conformation of polypeptide segments in proteins

C. Deane, T. Blundell, 2000, Proteins.

Length-independent structural similarities enrich the antibody CDR canonical class model

C. Deane, Jiye Shi, S. Kelm, 2016, mAbs.

Helix kinks are equally prevalent in soluble and membrane proteins

C. Deane, Jiye Shi, H. Wilman, 2014, Proteins.

Learning from the ligand: using ligand-based features to improve binding affinity prediction

C. Deane, G. Morris, F. Boyles, 2019, Bioinform..

The imprint of codons on protein structure

Charlotte M Deane, Rhodri Saunders, C. Deane, 2011, Biotechnology journal.

Synonymous codon usage influences the local protein structure observed

Charlotte M. Deane, Rhodri Saunders, C. Deane, 2010, Nucleic acids research.

Protein structure prediction begins well but ends badly

Charlotte M Deane, Rhodri Saunders, C. Deane, 2010, Proteins.

Building a Better Fragment Library for De Novo Protein Structure Prediction

Jiye Shi, Charlotte M. Deane, Saulo H. P. de Oliveira, 2015, PloS one.

Examining the Conservation of Kinks in Alpha Helices

Sebastian Kelm, Jiye Shi, Charlotte M Deane, 2016, PloS one.

Comparing co-evolution methods and their application to template-free protein structure prediction.

Saulo H. P. de Oliveira, C. Deane, Jiye Shi, 2016, Bioinformatics.

Sphinx: merging knowledge-based and ab initio approaches to improve protein loop prediction

Sebastian Kelm, Jiye Shi, Claire Marks, 2017, Bioinformatics.

ABangle: characterising the VH-VL orientation in antibodies.

C. Deane, J. Shi, A. Fuchs, 2013, Protein engineering, design & selection : PEDS.

The H3 loop of antibodies shows unique structural characteristics

Jiye Shi, Cristian Regep, Guy Georges, 2017, Proteins.

Humanization of antibodies using a machine learning approach on large-scale repertoire data

C. Deane, C. Marks, Mark Chin, 2021, bioRxiv.

Rapid, Precise, and Reproducible Prediction of Peptide-MHC Binding Affinities from Molecular Dynamics That Correlate Well with Experiment.

Charlotte M. Deane, Bernhard Knapp, Peter V. Coveney, 2015, Journal of chemical theory and computation.

How B-Cell Receptor Repertoire Sequencing Can Be Enriched with Structural Antibody Data

C. Deane, K. Krawczyk, Aleksandr Kovaltsuk, 2017, Front. Immunol..

Comparative Analysis of the CDR Loops of Antigen Receptors

C. Deane, Jinwoo Leem, W. K. Wong, 2019, Front. Immunol..

Antibody H3 Structure Prediction

C. Deane, C. Marks, C. Marks, 2017, Computational and structural biotechnology journal.

Structural diversity of B-cell receptor repertoires along the B-cell differentiation axis in humans and mice

C. Deane, S. Kelm, Aleksandr Kovaltsuk, 2020, PLoS computational biology.

How repertoire data are changing antibody science

C. Deane, C. Marks, Claire Marks, 2020, The Journal of Biological Chemistry.

Predicting antibody complementarity determining region structures without classification.

Charlotte M Deane, Yoonjoo Choi, C. Deane, 2011, Molecular bioSystems.

Prediction of VH–VL domain orientation for antibody variable domain modeling

James Dunbar, Guy Georges, Iris Antes, 2015, Proteins.

Maturation of naiÌˆve and antigen-experienced B-cell receptor repertoires with age

Enkelejda Miho, C. Deane, Aleksandr Kovaltsuk, 2019 .

Thera-SAbDab: the Therapeutic Structural Antibody Database

Jiye Shi, Charlotte M. Deane, Claire Marks, 2020, Nucleic Acids Res..

Comparative Analysis of the CDR Loops of Antigen Receptors

C. Deane, Jinwoo Leem, W. K. Wong, 2019, bioRxiv.

The allosteric modulation of complement C5 by knob domain peptides

Alastair D G Lawson, Sarah A. Robinson, C. Deane, 2020, bioRxiv.

Fold usage on genomes and protein fold evolution

Sanne Abeln, Charlotte M Deane, C. Deane, 2005, Proteins.

Faculty Opinions recommendation of How precise are reported protein coordinate data

Charlotte M. Deane, Nicholas Pearce, C. Deane, 2014 .

Hidden Markov Models for Protein Sequence Alignment

C. Deane, G. Lunter, N. Mimouni, 2004 .

27 – PROTEIN COMPARATIVE MODELLING AND DRUG DISCOVERY

C. Deane, T. Blundell, 2003 .

Co-evolutionary Distance Prediction for Flexibility Prediction

C. Deane, Jiye Shi, S. Kelm, 2020, bioRxiv.

CODA: A combined algorithm for predicting the structurally variable regions of protein models

C. Deane, T. Blundell, 2001, Protein science : a publication of the Protein Society.

Maturation of the Human Immunoglobulin Heavy Chain Repertoire With Age

Enkelejda Miho, C. Deane, Aleksandr Kovaltsuk, 2020, Frontiers in Immunology.

Computational Tools for Aiding Rational Antibody Design.

Konrad Krawczyk, James Dunbar, Charlotte M Deane, 2017, Methods in molecular biology.

Protein three-dimensional structural databases: domains, structurally aligned homologues and superfamilies.

John P. Overington, N Srinivasan, K Mizuguchi, 1998, Acta crystallographica. Section D, Biological crystallography.

Identifying and quantifying radiation damage at the atomic level

C. Deane, E. Garman, Markus Gerstel, 2015, Journal of synchrotron radiation.

Exploring Folding Features in Protein Structure Prediction

Charlotte M. Deane, Saulo H. P. de Oliveira, C. Deane, 2018 .

Observed Antibody Space: A Resource for Data Mining Next-Generation Sequencing of Antibody Repertoires

C. Deane, K. Krawczyk, S. Kelm, 2018, The Journal of Immunology.

Antibody side chain conformations are position‐dependent

Jiye Shi, Jinwoo Leem, Guy Georges, 2018, Proteins.

A Multi-Crystal Method for Extracting Obscured Signal from Crystallographic Electron Density

C. Deane, Jiye Shi, F. von Delft, 2016, bioRxiv.

Membranome 3.0: Database of single‐pass membrane proteins with AlphaFold models

C. Deane, C. Outeiral, A. Lomize, 2022, Protein science : a publication of the Protein Society.

Deep Sequencing of B Cell Receptor Repertoires From COVID-19 Patients Reveals Strong Convergent Immune Signatures

C. Deane, C. Caldas, R. Bashford-Rogers, 2020, Frontiers in Immunology.

JOY: protein sequence-structure representation and analysis

Charlotte M. Deane, Kenji Mizuguchi, John P. Overington, 1998, Bioinform..

Reduced amounts and abnormal forms of phospholipase C zeta (PLCzeta) in spermatozoa from infertile men.

C. Deane, R. Hamer, D. Deforce, 2009, Human reproduction.

Modeling conformational flexibility of kinases in inactive states

C. Deane, B. Merget, S. Fulle, 2019, Proteins.

Measuring rank robustness in scored protein interaction networks

Lyuba V. Bozhilova, C. Deane, G. Reinert, 2019, BMC Bioinform..

Editorial: A Journey Through 50 Years of Structural Bioinformatics in Memoriam of Cyrus Chothia

A. Lesk, C. Deane, S. Teichmann, 2022, Frontiers in Molecular Biosciences.

1 Supporting Information : What Evidence is There for the Homology of Protein-Protein Interactions ?

C. Deane, M. Porter, N. Jones, 2012 .

Heisenberg Community Detection and Protein Domains

C. Deane, M. Porter, N. Jones, 2008 .

Testing the limits of SMILES-based de novo molecular generation with curriculum and deep reinforcement learning

C. Deane, A. Bradley, Fergus Imrie, 2022, bioRxiv.

A computational method for immune repertoire mining that identifies novel binders from different clonotypes, demonstrated by identifying anti-pertussis toxoid antibodies

C. Deane, P. Kellam, A. Palser, 2020, bioRxiv.

A statistical model for helices with applications

C. Deane, K. Mardia, Karthik Sriram, 2018, Biometrics.

Misato Controls Mitotic Microtubule Generation by Stabilizing the TCP-1 Tubulin Chaperone Complex

C. Deane, K. B. Rogala, C. Pellacani, 2015, Current Biology.

BIOINFORMATICS ORIGINAL PAPER Exploring the potential of template-based modelling

Braddon K. Lance, C. Deane, Graham R. Wood, 2010 .

Peptide Centric Vβ Specific Germline Contacts Shape a Specialist T Cell Response

C. Deane, P. Thomas, W. K. Wong, 2022, Frontiers in Immunology.

The role and predicted propensity of conserved proline residues in the 5-HT3 receptor.

C. Deane, S. Lummis, 2001, The Journal of biological chemistry.

Why Many Molecular Simulation Research Findings Might Be False: An Analysis of Inter-Simulations Differences Based on Simulation Time and Number of Replicas

C. Deane, B. Knapp, 2022, bioRxiv.

Side chain prediction — Protein structure prediction — Antibodies — Antibody Design — Rotamer Library Authors

C. Deane, Jiye Shi, G. Georges, 2017 .

Structure of a Chordin-like Cysteine-rich Repeat (VWC module) from Collagen IIA

C. Deane, A. Downing, N. Valeyev, 2004 .

Paragraph - Antibody Paratope prediction using Graph Neural Networks with minimal feature vectors

C. Deane, I. Moal, Newton Wahome, 2022, bioRxiv.

Maturation of the human B-cell receptor repertoire with age

Enkelejda Miho, C. Deane, J. Galson, 2019, bioRxiv.

A functional Bayesian model for hydrogen-deuterium exchange mass-spectrometry

C. Deane, C. Chung, O. Crook, 2022, bioRxiv.

KA-Search: Rapid and exhaustive sequence identity search of known antibodies

C. Deane, I. Moal, T. H. Olsen, 2022, bioRxiv.

Computationally profiling peptide:MHC recognition by T-cell receptors and T-cell receptor-mimetic antibodies

Daniel A. Nissley, C. Deane, M. Raybould, 2022, bioRxiv.

ImmuneBuilder: Deep-Learning models for predicting the structures of immune proteins

C. Deane, W. K. Wong, A. Bujotzek, 2022, bioRxiv.

Evidence of Antibody Repertoire Functional Convergence through Public Baseline and Shared Response Structures

C. Deane, Jiye Shi, M. Raybould, 2020, bioRxiv.

Challenges in antibody structure prediction

Patrick K. Quoika, C. Deane, K. Liedl, 2022, bioRxiv.

Codon language embeddings provide strong signals for protein engineering

C. Deane, C. Outeiral, 2022, bioRxiv.

PointVS: A Machine Learning Scoring Function that Identifies Important Binding Interactions

Thomas E. Hadfield, C. Deane, F. Delft, 2022, bioRxiv.

Mutual information and variants for protein domain-domain contact prediction

C. Deane, G. Reinert, R. Hamer, 2012, BMC Research Notes.

Microfluidics-enabled fluorescence-activated cell sorting of single pathogen-specific antibody secreting cells for the rapid discovery of monoclonal antibodies

C. Deane, F. Hollfelder, M. Raybould, 2023, bioRxiv.

CoV-AbDab: the Coronavirus Antibody Database

Charlotte M. Deane, Claire Marks, Aleksandr Kovaltsuk, 2020, bioRxiv.

A multi-crystal method for extracting obscured crystallographic states from conventionally uninterpretable electron density

Sebastian Kelm, Jiye Shi, Charlotte M Deane, 2017, Nature Communications.

iMembrane: homology-based membrane-insertion of proteins

C. Deane, Jiye Shi, S. Kelm, 2009, Bioinform..

Protein Modeling and Structural Prediction

Sebastian Kelm, Charlotte M. Deane, Yoonjoo Choi, 2014 .

How threshold behaviour affects the use of subgraphs for network comparison

Gesine Reinert, Charlotte M. Deane, Zi Wang, 2010, Bioinform..

In silico structural modeling of multiple epigenetic marks on DNA

Charlotte M. Deane, Konrad Krawczyk, Samuel Demharter, 2018, Bioinform..

Current strategies for detecting functional convergence across B-cell receptor repertoires

C. Deane, A. Rees, M. Raybould, 2021, mAbs.

Carbonyl-carbonyl interactions stabilize the partially allowed Ramachandran conformations of asparagine and aspartic acid.

C. Deane, T. Blundell, F. Allen, 1999, Protein engineering.

Public Baseline and shared response structures support the theory of antibody repertoire functional commonality

Jiye Shi, Charlotte M. Deane, Claire Marks, 2021, PLoS Comput. Biol..

CommWalker: correctly evaluating modules in molecular networks in light of annotation bias

Gesine Reinert, Charlotte M. Deane, S. Mason, 2017, Bioinform..

Protein Interaction Networks and Their Statistical Analysis

Gesine Reinert, Charlotte M. Deane, Waqar Ali, 2011 .

Revisiting Date and Party Hubs: Novel Approaches to Role Assignment in Protein Interaction Networks

Charlotte M. Deane, Mason A. Porter, Nick S. Jones, 2009, PLoS Comput. Biol..

The function of communities in protein interaction networks at multiple scales

Charlotte M. Deane, Mason A. Porter, Nick S. Jones, 2009, BMC Systems Biology.

A structural model of the human thrombopoietin receptor complex.

C. Deane, R. Kroemer, W. Richards, 1997, Journal of molecular graphics & modelling.

The prospects of quantum computing in computational molecular biology

Charlotte M. Deane, Garrett M. Morris, Carlos Outeiral, 2020, WIREs Computational Molecular Science.

Type II Inhibitors Targeting CDK2.

C. Deane, S. Knapp, O. Fedorov, 2015, ACS chemical biology.

Current status and future challenges in T-cell receptor/peptide/MHC molecular dynamics simulations

Charlotte M. Deane, Samuel Demharter, Bernhard Knapp, 2015, Briefings Bioinform..

MEDELLER: homology-based coordinate generation for membrane proteins

Sebastian Kelm, Jiye Shi, Charlotte M. Deane, 2010, Bioinform..

Filtering Next-Generation Sequencing of the Ig Gene Repertoire Data Using Antibody Structural Information

Sebastian Kelm, Aleksandr Kovaltsuk, James Snowden, 2018, The Journal of Immunology.

Protein protein interactions, evolutionary rate, abundance and age

Charlotte M. Deane, Ramazan Saeed, C. Deane, 2006, BMC Bioinformatics.

Protein-Ligand Interaction Graphs: Learning from Ligand-Shaped 3D Interaction Graphs to Improve Binding Affinity Prediction

C. Deane, G. Morris, Dominik Klein, 2022, bioRxiv.

Data Set Augmentation Allows Deep Learning-Based Virtual Screening to Better Generalize to Unseen Target Classes and Highlight Important Binding Interactions

Charlotte M. Deane, Nathan Brown, Jack Scantlebury, 2020, J. Chem. Inf. Model..

Dataset Augmentation Allows Deep Learning-Based Virtual Screening To Better Generalize To Unseen Target Classes, And Highlight Important Binding Interactions

Nathan Brown, Charlotte M. Deane, Jack Scantlebury, 2020, bioRxiv.

Five computational developability guidelines for therapeutic antibody profiling

Jiye Shi, Claire Marks, Konrad Krawczyk, 2019, Proceedings of the National Academy of Sciences.

Alignment-free protein interaction network comparison

Gesine Reinert, Charlotte M. Deane, Waqar Ali, 2014, Bioinform..

Predicting protein-protein interactions in the context of protein evolution.

Charlotte M Deane, Ramazan Saeed, C. Deane, 2010, Molecular bioSystems.

Association between a common immunoglobulin heavy chain allele and rheumatic heart disease risk in Oceania

C. Deane, É. Marijon, X. Jouven, 2017, Nature Communications.

SAbDab: the structural antibody database

Jiye Shi, Charlotte M. Deane, Konrad Krawczyk, 2013, Nucleic Acids Res..

Using Phylogeny to Improve Genome-Wide Distant Homology Recognition

Charlotte M. Deane, Sanne Abeln, Carlo Teubner, 2006, PLoS Comput. Biol..

How old is your fold?

Charlotte M. Deane, Sanne Abeln, Henry F. Winstanley, 2005, ISMB.

ANARCI: antigen receptor numbering and receptor classification

Charlotte M. Deane, James Dunbar, C. Deane, 2015, Bioinform..

Exploring the potential of template-based modelling

Charlotte M. Deane, Graham R. Wood, Braddon K. Lance, 2010, Bioinform..

Different B cell subpopulations show distinct patterns in their IgH repertoire metrics

C. Deane, J. Galson, J. Trück, 2021, bioRxiv.

Structural diversity of B-cell receptor repertoires along the B-cell differentiation axis in humans and mice

Sebastian Kelm, Charlotte M. Deane, Claire Marks, 2019, bioRxiv.

Sphinx: merging knowledge‐based and ab initio approaches to improve protein loop prediction

Sebastian Kelm, Jiye Shi, Charlotte M. Deane, 2017, Bioinform..

Current advances in biopharmaceutical informatics: guidelines, impact and challenges in the computational developability assessment of antibody therapeutics

Sarah A. Robinson, C. Deane, J. Warwicker, 2022, mAbs.

Exploring Fold Space Preferences of New-born and Ancient Protein Superfamilies

Charlotte M. Deane, Sanne Abeln, Hannah Edwards, 2013, PLoS Comput. Biol..

Memoir: template-based structure prediction for membrane proteins

Sebastian Kelm, Jiye Shi, Charlotte M. Deane, 2013, Nucleic Acids Res..

Progress and challenges in predicting protein interfaces

Jean-Christophe Nebel, Charlotte M. Deane, Konrad Krawczyk, 2015, Briefings Bioinform..

Improving B-cell epitope prediction and its application to global antibody-antigen docking

Jiye Shi, Charlotte M. Deane, Konrad Krawczyk, 2014, Bioinform..

Current structure predictors are not learning the physics of protein folding

Daniel A. Nissley, C. Deane, C. Outeiral, 2022, Bioinform..

What Evidence Is There for the Homology of Protein-Protein Interactions?

Charlotte M. Deane, Mason A. Porter, Nick S. Jones, 2012, PLoS Comput. Biol..

Modelling sequential protein folding under kinetic control

Charlotte M. Deane, Graham R. Wood, Fabien P. E. Huard, 2006, ISMB.

SAbPred: a structure-based antibody prediction server

Sebastian Kelm, Charlotte M. Deane, Claire Marks, 2016, Nucleic Acids Res..

Proteomic Analysis of Microtubule-associated Proteins during Macrophage Activation*

C. Deane, R. Harrison, K. Fisher, 2009, Molecular & Cellular Proteomics.

Exploring peptide/MHC detachment processes using hierarchical natural move Monte Carlo

Charlotte M. Deane, Samuel Demharter, Bernhard Knapp, 2015, Bioinform..

ABodyBuilder: Automated antibody structure prediction with data–driven accuracy estimation

Jiye Shi, Charlotte M. Deane, James Dunbar, 2016, mAbs.

Extracting Information from Gene Coexpression Networks of Rhizobium leguminosarum

C. Deane, G. Reinert, P. Poole, 2022, J. Comput. Biol..

Directionality in protein fold prediction

Charlotte M. Deane, Graham R. Wood, Fabien P. E. Huard, 2010, BMC Bioinformatics.

Functionally guided alignment of protein interaction networks for module detection

Charlotte M. Deane, Waqar Ali, C. Deane, 2009, Bioinform..

An assessment of the uses of homologous interactions

Charlotte M. Deane, Ramazan Saeed, C. Deane, 2008, Bioinform..

Signatures of co-translational folding.

C. Deane, Martin Mann, Rhodri Saunders, 2011, Biotechnology journal.

Identifying networks with common organizational principles

Gesine Reinert, Charlotte M. Deane, Anatol E. Wegner, 2017, J. Complex Networks.

Novel Vβ specific germline contacts shape an elite controller T cell response

C. Deane, P. Thomas, W. K. Wong, 2020, bioRxiv.

Examining Variable Domain Orientations in Antigen Receptors Gives Insight into TCR-Like Antibody Design

Jiye Shi, Charlotte M. Deane, Bernhard Knapp, 2014, PLoS Comput. Biol..

The Importance of Age and High Degree, in Protein-Protein Interaction Networks

Gesine Reinert, Charlotte M. Deane, Tiago Rito, 2012, J. Comput. Biol..

Large Scale Characterization of the LC13 TCR and HLA-B8 Structural Landscape in Reaction to 172 Altered Peptide Ligands: A Molecular Dynamics Simulation Study

Charlotte M. Deane, Bernhard Knapp, James Dunbar, 2014, PLoS Comput. Biol..

Variable Regions of Antibodies and T-Cell Receptors May Not Be Sufficient in Molecular Simulations Investigating Binding.

Bernhard Knapp, James Dunbar, Charlotte M Deane, 2017, Journal of chemical theory and computation.

Solution Structure and Dynamics of a Prototypical Chordin-like Cysteine-rich Repeat (von Willebrand Factor Type C Module) from Collagen IIA*

C. Deane, A. Downing, N. Valeyev, 2004, Journal of Biological Chemistry.

Advances in computational structure-based antibody design.

Alissa M. Hummer, C. Deane, Brennan Abanades, 2022, Current opinion in structural biology.

STCRDab: the structural T-cell receptor database

Charlotte M. Deane, Konrad Krawczyk, Jinwoo Leem, 2017, Nucleic Acids Res..

Co-evolutionary distance predictions contain flexibility information

Sebastian Kelm, Jiye Shi, Charlotte M. Deane, 2021, Bioinform..

ABlooper: fast accurate antibody CDR loop structure prediction with accuracy estimation

C. Deane, A. Bujotzek, G. Georges, 2021, bioRxiv.

Challenges and Opportunities for Bayesian Statistics in Proteomics

C. Deane, C. Chung, O. Crook, 2022, Journal of proteome research.

Ribosome occupancy profiles are conserved between structurally and evolutionarily related yeast domains

Charlotte M. Deane, Mark Chonofsky, Daniel A. Nissley, 2021, Bioinform..

ImmuneBuilder: Deep-Learning models for predicting the structures of immune proteins

C. Deane, W. K. Wong, A. Bujotzek, 2022, bioRxiv.

Observed Antibody Space: A diverse database of cleaned, annotated, and translated unpaired and paired antibody sequences

C. Deane, T. H. Olsen, Fergus Boyles, 2021, Protein science : a publication of the Protein Society.

FREAD revisited: Accurate loop structure prediction using a database search algorithm

Yoonjoo Choi, Charlotte M Deane, C. Deane, 2010, Proteins.

Hypergraphs for predicting essential genes using multiprotein complex data

Gesine Reinert, Charlotte M. Deane, Florian Klimm, 2020, bioRxiv.

Evolutionary analysis reveals low coverage as the major challenge for protein interaction network alignment.

Charlotte M Deane, C. Deane, Waqar Ali, 2010, Molecular bioSystems.

Predicting and Validating Protein Interactions Using Network Structure

Gesine Reinert, Charlotte M. Deane, Pao-Yang Chen, 2008, PLoS Comput. Biol..

A statistical approach using network structure in the prediction of protein characteristics

Gesine Reinert, Charlotte M. Deane, Pao-Yang Chen, 2007, Bioinform..

Ten Simple Rules for Effective Computational Research

Alexander G. Fletcher, Charlotte M. Deane, David Gavaghan, 2014, PLoS Comput. Biol..

Avoiding False Positive Conclusions in Molecular Simulation: The Importance of Replicas.

Bernhard Knapp, Charlotte M Deane, Luis Ospina, 2018, Journal of chemical theory and computation.

The contribution of major histocompatibility complex contacts to the affinity and kinetics of T cell receptor binding

Charlotte M. Deane, Omer Dushek, C. Deane, 2016, Scientific Reports.

The functional domain grouping of microtubule associated proteins

C. Deane, K. Fisher, J. Wakefield, 2008, Communicative & integrative biology.

The Caenorhabditis elegans protein SAS-5 forms large oligomeric assemblies critical for centriole formation

C. Deane, P. Gönczy, C. Robinson, 2015, eLife.

Electrostatic and Functional Analysis of the Seven-Bladed WD β-Propellers

Charlotte Deane, Najl V. Valeyev, A. Kristina Downing, 2008, Evolutionary bioinformatics online.

Epitope profiling using computational structural modelling demonstrated on coronavirus-binding antibodies

Sarah A. Robinson, C. Deane, W. K. Wong, 2021, PLoS Comput. Biol..

Epitope profiling of coronavirus-binding antibodies using computational structural modelling

Sarah A. Robinson, C. Deane, W. K. Wong, 2021, bioRxiv.

i-Patch: inter protein contact prediction

C. Deane, G. Reinert, J. Armitage, 2010 .

Deep Generative Models for 3D Linker Design

Charlotte M. Deane, Mihaela van der Schaar, Fergus Imrie, 2020, J. Chem. Inf. Model..

How long is a piece of loop?

Charlotte M. Deane, Sumeet Agarwal, Yoonjoo Choi, 2013, PeerJ.

Improved protein loop prediction from sequence alone.

C M Deane, D F Burke, C. Deane, 2001, Protein engineering.

Browsing the SLoop database of structurally classified loops connecting elements of protein secondary structure

Charlotte M. Deane, David F. Burke, Tom L. Blundell, 2000, Bioinform..

High-Throughput Antibody Structure Modeling and Design Using ABodyBuilder.

Jinwoo Leem, Charlotte M Deane, C. Deane, 2018, Methods in molecular biology.

Fragment‐based modeling of membrane protein loops: Successes, failures, and prospects for the future

Sebastian Kelm, Jiye Shi, Anna Vangone, 2014, Proteins.

WONKA and OOMMPPAA: analysis of protein–ligand interaction data to direct structure-based drug design

Charlotte M. Deane, Darren V. S. Green, Anthony R. Bradley, 2017, Acta crystallographica. Section D, Structural biology.

SAbDab in the age of biotherapeutics: updates including SAbDab-nano, the nanobody structure tracker

C. Deane, M. Raybould, Constantin Schneider, 2021, Nucleic Acids Res..

The evolution of contact prediction: Evidence that contact selection in statistical contact prediction is changing

Charlotte M. Deane, Konrad Krawczyk, Saulo H. P. de Oliveira, 2019, bioRxiv.

WONKA: objective novel complex analysis for ensembles of protein–ligand structures

Charlotte M. Deane, Darren V. S. Green, Anthony R. Bradley, 2015, Journal of Computer-Aided Molecular Design.

Measuring rank robustness in scored protein interaction networks

Gesine Reinert, Charlotte M. Deane, Lyuba V. Bozhilova, 2018, BMC Bioinformatics.

Generating property-matched decoy molecules using deep learning

Fergus Imrie, Anthony R. Bradley, Charlotte M. Deane, 2020, bioRxiv.

Learning from Docked Ligands: Ligand-Based Features Rescue Structure-Based Scoring Functions When Trained on Docked Poses

Charlotte M. Deane, Garrett M. Morris, F Boyles, 2021, J. Chem. Inf. Model..

Deep generative design with 3D pharmacophoric constraints

Charlotte M. Deane, Fergus Imrie, Anthony R. Bradley, 2021, bioRxiv.

T-Cell Receptor Binding Affects the Dynamics of the Peptide/MHC-I Complex

Charlotte M. Deane, Bernhard Knapp, C. Deane, 2016, J. Chem. Inf. Model..

Combining co‐evolution and secondary structure prediction to improve fragment library generation

Charlotte M. Deane, Saulo Henrique Pires de Oliveira, C. Deane, 2018, Bioinform..

DLAB: deep learning methods for structure-based virtual screening of antibodies

C. Deane, Andrew Buchanan, Bruck Taddese, 2021, bioRxiv.

Producing High-Accuracy Lattice Models from Protein Atomic Coordinates Including Side Chains

Charlotte M. Deane, Rolf Backofen, Martin Mann, 2012, Adv. Bioinformatics.

Cross-linking mass spectrometry identifies new interfaces of Augmin required to localise the γ-tubulin ring complex to the mitotic spindle

C. Deane, J. Rappsilber, K. B. Rogala, 2017, Biology Open.

A Microtubule Interactome: Complexes with Roles in Cell Cycle and Mitosis

C. Deane, Ángel García, N. Zitzmann, 2008, PLoS biology.

Deciphering chemotaxis pathways using cross species comparisons

Gesine Reinert, Charlotte M. Deane, Pao-Yang Chen, 2010, BMC Systems Biology.

Investigating the potential for a limited quantum speedup on protein lattice problems

C. Deane, G. Morris, Jiye Shi, 2020, New Journal of Physics.

Crowdsourcing Yields a New Standard for Kinks in Protein Helices

Jiye Shi, Charlotte M. Deane, Bernhard Knapp, 2014, J. Chem. Inf. Model..

Looking for therapeutic antibodies in next-generation sequencing repositories

Aleksandr Kovaltsuk, Konrad Krawczyk, Charlotte M. Deane, 2019, bioRxiv.

AbLang: an antibody language model for completing antibody sequences

C. Deane, I. Moal, T. H. Olsen, 2022, bioRxiv.

Thera-SAbDab: the Therapeutic Structural Antibody Database

Claire Marks, Matthew I. J. Raybould, Bruck Taddese, 2019, bioRxiv.

Ten Simple Rules for a Successful Cross-Disciplinary Collaboration

Alexander G. Fletcher, Charlotte M. Deane, David Gavaghan, 2015, PLoS Comput. Biol..

Investigating the Volume and Diversity of Data Needed for Generalizable Antibody-Antigen ∆∆G Prediction

Alissa M. Hummer, C. Deane, Lewis Chinery, 2023, bioRxiv.

Deep Generative Models for 3D Compound Design

Charlotte M. Deane, Fergus Imrie, Mihaela van der Schaar, 2019, bioRxiv.

A maternally inherited autosomal point mutation in human phospholipase C zeta (PLCζ) leads to male infertility.

C. Deane, R. Hamer, B. Heindryckx, 2012, Human reproduction.

Incorporating Target-Specific Pharmacophoric Information into Deep Generative Models for Fragment Elaboration

Thomas E. Hadfield, C. Deane, A. Merritt, 2021, bioRxiv.

AI in 3D compound design.

Thomas E. Hadfield, C. Deane, 2022, Current opinion in structural biology.

Freely Available Conformer Generation Methods: How Good Are They?

Charlotte M. Deane, Garrett M. Morris, Jean-Paul Ebejer, 2012, J. Chem. Inf. Model..

The use of a graph database is a complementary approach to a classical similarity search for identifying commercially available fragment merges

C. Deane, F. von Delft, R. Hubbard, 2022, bioRxiv.

Fragment Libraries Designed to Be Functionally Diverse Recover Protein Binding Information More Efficiently Than Standard Structurally Diverse Libraries

C. Deane, F. von Delft, R. Skyner, 2022, bioRxiv.

A Maternally Inherited Autosomal Point in Human Phospholipase C Zeta Leads to Male Infertility

C. Deane, R. Hamer, B. Heindryckx, 2012 .

TCRBuilder: multi-state T-cell receptor structure prediction

Claire Marks, Wing Ki Wong, Jinwoo Leem, 2020, Bioinform..

SCORE: predicting the core of protein models

Charlotte M. Deane, Tom L. Blundell, Quentin Kaas, 2001, Bioinform..

Co-evolution techniques are reshaping the way we do structural bioinformatics

Charlotte Deane, Saulo H. P. de Oliveira, Saulo de Oliveira, 2017, F1000Research.

Ligity: A Non-Superpositional, Knowledge-Based Approach to Virtual Screening

Garrett M Morris, Wing Ki Wong, Paul W Finn, 2019, J. Chem. Inf. Model..

Protein Family-Specific Models Using Deep Neural Networks and Transfer Learning Improve Virtual Screening and Highlight the Need for More Data

Charlotte M. Deane, Mihaela van der Schaar, Fergus Imrie, 2018, J. Chem. Inf. Model..

The Therapeutic Antibody Profiler for Computational Developability Assessment.

C. Deane, M. Raybould, 2021, Methods in molecular biology.

The Therapeutic Antibody Profiler (TAP): Five Computational Developability Guidelines

Jiye Shi, Claire Marks, Matthew I. J. Raybould, 2018, bioRxiv.

Ab-Ligity: identifying sequence-dissimilar antibodies that bind to the same epitope

Wing Ki Wong, Charlotte M. Deane, Bruck Taddese, 2020, bioRxiv.

Increasing the accuracy of protein loop structure prediction with evolutionary constraints

Claire Marks, Charlotte M Deane, C. Deane, 2018, Bioinform..

Empirical Bayes functional models for hydrogen deuterium exchange mass spectrometry

C. Deane, C. Chung, O. Crook, 2021, Communications Biology.

Ranking of communities in multiplex spatiotemporal models of brain dynamics

C. Deane, G. Reinert, James B. Wilsenach, 2022, Appl. Netw. Sci..

MHC binding affects the dynamics of different T-cell receptors in different ways

Charlotte M. Deane, Bernhard Knapp, Omer Dushek, 2019, PLoS Comput. Biol..

1 Type II inhibitors targeting CDK 2

C. Deane, S. Knapp, O. Fedorov, 2016 .

Fragment Merging Using a Graph Database Samples Different Catalogue Space than Similarity Search

C. Deane, R. Hubbard, F. Delft, 2023, J. Chem. Inf. Model..

Modeling Functional Motions of Biological Systems by Customized Natural Moves

Samuel Demharter, Bernhard Knapp, Peter Minary, 2016, Biophysical journal.

Improved computational epitope profiling using structural models identifies a broader diversity of antibodies that bind the same epitope

C. Deane, W. K. Wong, M. Raybould, 2023, bioRxiv.

COGENT: evaluating the consistency of gene co-expression networks

Gesine Reinert, Lyuba V. Bozhilova, Charlotte M. Deane, 2020, bioRxiv.

Investigating the potential for a limited quantum speedup on protein lattice problems

Jiye Shi, Garrett M Morris, Simon C Benjamin, 2020, New Journal of Physics.

pyHVis3D: visualising molecular simulation deduced H-bond networks in 3D: application to T-cell receptor interactions

Charlotte M. Deane, Hao Zhang, Bernhard Knapp, 2018, Bioinform..

MP-T: improving membrane protein alignment for structure prediction

Charlotte M. Deane, Jamie R. Hill, C. Deane, 2013, Bioinform..

Drug Discovery under Covariate Shift with Domain-Informed Prior Distributions over Functions

Tim G. J. Rudner, Y. Teh, C. Deane, 2023, ICML.

Assessment of model fit via network comparison methods based on subgraph counts

Gesine Reinert, Charlotte M. Deane, Luis Ospina-Forero, 2018, J. Complex Networks.

Comparison of large networks with sub-sampling strategies

Gesine Reinert, Charlotte M. Deane, Anatol E. Wegner, 2016, Scientific Reports.

Ten Simple Rules for a Successful Cross-Disciplinary Collaboration

Christian A. Yates, C. Deane, R. Bardenet, 2015, PLoS Comput. Biol..

Ten simple rules for surviving an interdisciplinary PhD

Charlotte M. Deane, David Gavaghan, Samuel Demharter, 2017, PLoS Comput. Biol..

Ten Simple Rules for a Successful Cross- Disciplinary Collaboration

Christian A. Yates, C. Deane, R. Bardenet, 2015 .

Generating weighted and thresholded gene coexpression networks using signed distance correlation

C. Deane, G. Reinert, P. Poole, 2021, bioRxiv.

Robust gene coexpression networks using signed distance correlation

Gesine Reinert, Mariano Beguerisse-Díaz, Lyuba V. Bozhilova, 2020, bioRxiv.

A Small Step Toward Generalizability: Training a Machine Learning Scoring Function for Structure-Based Virtual Screening

Thomas E. Hadfield, C. Deane, F. von Delft, 2023, Journal of chemical information and modeling.

Current protein structure predictors do not produce meaningful folding pathways

Daniel A. Nissley, C. Deane, C. Outeiral, 2021, bioRxiv.

Tertiary Element Interaction in HIV-1 TAR

Charlotte M. Deane, Konrad Krawczyk, Bernhard Knapp, 2016, J. Chem. Inf. Model..

The Patent and Literature Antibody Database (PLAbDab): an evolving reference set of functionally diverse, literature-annotated antibody sequences and structures

C. Deane, W. K. Wong, M. Raybould, 2023, bioRxiv.

RFQAmodel: Random Forest Quality Assessment to identify a predicted protein structure in the correct fold

Charlotte M. Deane, Clare E. West, Saulo H. P. de Oliveira, 2019, bioRxiv.

A comparison of the binding sites of antibodies and single-domain antibodies

C. Deane, R. Stafford, Henriette Capel, 2023, bioRxiv.

SCALOP: sequence-based antibody canonical loop structure annotation

Sebastian Kelm, Wing Ki Wong, Jinwoo Leem, 2018, Bioinform..

Sequence‐structure homology recognition by iterative alignment refinement and comparative modeling

T L Blundell, M G Williams, H Shirai, 2001, Proteins.

Avoiding False Positive Conclusions in Molecular Simulation: The Importance of Replicas.

C. Deane, B. Knapp, Luis Ospina, 2018, Journal of chemical theory and computation.

Partial-occupancy binders identified by the Pan-Dataset Density Analysis method offer new chemical opportunities and reveal cryptic binding sites

Charlotte M. Deane, Brian D. Marsden, Frank von Delft, 2017, Structural dynamics.

HLA-DM Stabilizes the Empty MHCII Binding Groove: A Model Using Customized Natural Move Monte Carlo

Samuel Demharter, Bernhard Knapp, Peter Minary, 2019, J. Chem. Inf. Model..

PEP-Patch: Electrostatics in Protein-Protein Recognition, Specificity and Antibody Developability

C. Deane, H. Kettenberger, G. Georges, 2023, bioRxiv.

Structural Bridges through Fold Space

Charlotte M. Deane, Hannah Edwards, C. Deane, 2015, PLoS Comput. Biol..

The function of communities in protein interaction networks at multiple scales

Charlotte M. Deane, Nick S. Jones, Nick S. Jones, 2009, BMC Systems Biology.

distance correlation

Lyuba V. Bozhilova, C. Deane, G. Reinert, 2022 .

Predicting loop conformational ensembles

Jiye Shi, Charlotte M. Deane, Claire Marks, 2018, Bioinform..

A Step Towards Generalisability: Training a Machine Learning Scoring Function for Structure-Based Virtual Screening

Thomas E. Hadfield, C. Deane, F. von Delft, 2023, bioRxiv.

PoseBusters: AI-based docking methods fail to generate physically valid poses or generalise to novel sequences

C. Deane, G. Morris, Martin Buttenschoen, 2023, Chemical science.

Comparing co-evolution methods and their application to template-free protein structure prediction

Jiye Shi, Charlotte M. Deane, Saulo Henrique Pires de Oliveira, 2016, Bioinform..

The function of communities in protein interaction networks at multiple scales

C. Deane, M. Porter, N. Jones, 2009, BMC Systems Biology.