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Charlotte M. Deane
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2020 – today
- 2024
- [j100]Anna Carbery, Martin Buttenschoen, Rachael Skyner, Frank von Delft, Charlotte M. Deane:
Learnt representations of proteins can be used for accurate prediction of small molecule binding sites on experimentally determined and predicted protein structures. J. Cheminformatics 16(1): 32 (2024) - [j99]Carlos Outeiral
, Charlotte M. Deane
:
Codon language embeddings provide strong signals for use in protein engineering. Nat. Mac. Intell. 6(2): 170-179 (2024) - [i8]Henry Kenlay, Frédéric A. Dreyer, Aleksandr Kovaltsuk, Dom Miketa, Douglas Pires, Charlotte M. Deane:
Large scale paired antibody language models. CoRR abs/2403.17889 (2024) - [i7]Daniel Cutting, Frédéric A. Dreyer, David Errington, Constantin Schneider, Charlotte M. Deane:
De novo antibody design with SE(3) diffusion. CoRR abs/2405.07622 (2024) - [i6]Henry Kenlay, Frédéric A. Dreyer, Daniel Cutting, Daniel A. Nissley, Charlotte M. Deane:
ABodyBuilder3: Improved and scalable antibody structure predictions. CoRR abs/2405.20863 (2024) - [i5]Leo Klarner, Tim G. J. Rudner, Garrett M. Morris, Charlotte M. Deane, Yee Whye Teh:
Context-Guided Diffusion for Out-of-Distribution Molecular and Protein Design. CoRR abs/2407.11942 (2024) - 2023
- [j98]Lewis Chinery
, Newton Wahome, Iain Moal, Charlotte M. Deane
:
Paragraph - antibody paratope prediction using graph neural networks with minimal feature vectors. Bioinform. 39(1) (2023) - [j97]Szabolcs Elias, Clemens Wrzodek, Charlotte M. Deane, Alain C. Tissot, Stefan Klostermann, Francesca Ros:
Prediction of polyspecificity from antibody sequence data by machine learning. Frontiers Bioinform. 3 (2023) - [j96]Thomas E. Hadfield, Jack Scantlebury, Charlotte M. Deane:
Exploring the ability of machine learning-based virtual screening models to identify the functional groups responsible for binding. J. Cheminformatics 15(1): 84 (2023) - [j95]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:
A Small Step Toward Generalizability: Training a Machine Learning Scoring Function for Structure-Based Virtual Screening. J. Chem. Inf. Model. 63(10): 2960-2974 (2023) - [j94]Stephanie Wills
, Ruben Sanchez-Garcia
, Tim Dudgeon, Stephen D. Roughley
, Andy Merritt
, Roderick E. Hubbard
, James Davidson
, Frank von Delft
, Charlotte M. Deane
:
Fragment Merging Using a Graph Database Samples Different Catalogue Space than Similarity Search. J. Chem. Inf. Model. 63(11): 3423-3437 (2023) - [j93]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
:
PEP-Patch: Electrostatics in Protein-Protein Recognition, Specificity, and Antibody Developability. J. Chem. Inf. Model. 63(22): 6964-6971 (2023) - [j92]Maranga Mokaya
, Fergus Imrie, Willem P. van Hoorn
, Aleksandra Kalisz
, Anthony R. Bradley, Charlotte M. Deane
:
Testing the limits of SMILES-based de novo molecular generation with curriculum and deep reinforcement learning. Nat. Mac. Intell. 5(4): 386-394 (2023) - [c4]Leo Klarner, Tim G. J. Rudner, Michael Reutlinger, Torsten Schindler, Garrett M. Morris, Charlotte M. Deane, Yee Whye Teh:
Drug Discovery under Covariate Shift with Domain-Informed Prior Distributions over Functions. ICML 2023: 17176-17197 - [i4]Leo Klarner, Tim G. J. Rudner, Michael Reutlinger, Torsten Schindler, Garrett M. Morris, Charlotte M. Deane, Yee Whye Teh:
Drug Discovery under Covariate Shift with Domain-Informed Prior Distributions over Functions. CoRR abs/2307.15073 (2023) - [i3]Frédéric A. Dreyer, Daniel Cutting, Constantin Schneider, Henry Kenlay, Charlotte M. Deane:
Inverse folding for antibody sequence design using deep learning. CoRR abs/2310.19513 (2023) - 2022
- [j91]James B. Wilsenach
, Catherine E. Warnaby, Charlotte M. Deane, Gesine Reinert:
Ranking of communities in multiplex spatiotemporal models of brain dynamics. Appl. Netw. Sci. 7(1): 15 (2022) - [j90]Constantin Schneider
, Andrew Buchanan
, Bruck Taddese
, Charlotte M. Deane
:
DLAB: deep learning methods for structure-based virtual screening of antibodies. Bioinform. 38(2): 377-383 (2022) - [j89]Brennan Abanades
, Guy Georges, Alexander Bujotzek, Charlotte M. Deane
:
ABlooper: fast accurate antibody CDR loop structure prediction with accuracy estimation. Bioinform. 38(7): 1877-1880 (2022) - [j88]Carlos Outeiral
, Daniel A. Nissley
, Charlotte M. Deane
:
Current structure predictors are not learning the physics of protein folding. Bioinform. 38(7): 1881-1887 (2022) - [j87]Javier Pardo-Diaz
, Mariano Beguerisse-Díaz, Philip S. Poole, Charlotte M. Deane, Gesine Reinert:
Extracting Information from Gene Coexpression Networks of Rhizobium leguminosarum. J. Comput. Biol. 29(7): 752-768 (2022) - [j86]Thomas E. Hadfield
, Fergus Imrie
, Andy Merritt
, Kristian Birchall, Charlotte M. Deane
:
Incorporating Target-Specific Pharmacophoric Information into Deep Generative Models for Fragment Elaboration. J. Chem. Inf. Model. 62(10): 2280-2292 (2022) - [j85]Fergus Boyles
, Charlotte M. Deane
, Garrett M. Morris
:
Learning from Docked Ligands: Ligand-Based Features Rescue Structure-Based Scoring Functions When Trained on Docked Poses. J. Chem. Inf. Model. 62(22): 5329-5341 (2022) - [j84]Constantin Schneider
, Matthew I. J. Raybould
, Charlotte M. Deane
:
SAbDab in the age of biotherapeutics: updates including SAbDab-nano, the nanobody structure tracker. Nucleic Acids Res. 50(D1): 1368-1372 (2022) - [j83]Javier Pardo-Diaz
, Philip S. Poole, Mariano Beguerisse-Díaz, Charlotte M. Deane, Gesine Reinert:
Generating weighted and thresholded gene coexpression networks using signed distance correlation. Netw. Sci. 10(2): 131-145 (2022) - [i2]James B. Wilsenach, Catherine E. Warnaby, Charlotte M. Deane, Gesine D. Reinert:
Ranking of Communities in Multiplex Spatiotemporal Models of Brain Dynamics. CoRR abs/2203.09281 (2022) - 2021
- [j82]Matthew I. J. Raybould
, Aleksandr Kovaltsuk, Claire Marks, Charlotte M. Deane
:
CoV-AbDab: the coronavirus antibody database. Bioinform. 37(5): 734-735 (2021) - [j81]Daniel A. Nissley
, Anna Carbery
, Mark Chonofsky
, Charlotte M. Deane
:
Ribosome occupancy profiles are conserved between structurally and evolutionarily related yeast domains. Bioinform. 37(13): 1853-1859 (2021) - [j80]Lyuba V. Bozhilova
, Javier Pardo-Diaz
, Gesine Reinert, Charlotte M. Deane
:
COGENT: evaluating the consistency of gene co-expression networks. Bioinform. 37(13): 1928-1929 (2021) - [j79]Javier Pardo-Diaz
, Lyuba V. Bozhilova
, Mariano Beguerisse-Díaz, Philip S. Poole, Charlotte M. Deane
, Gesine Reinert:
Robust gene coexpression networks using signed distance correlation. Bioinform. 37(14): 1982-1989 (2021) - [j78]Fergus Imrie
, Anthony R. Bradley, Charlotte M. Deane
:
Generating property-matched decoy molecules using deep learning. Bioinform. 37(15): 2134-2141 (2021) - [j77]Claire Marks
, Alissa M. Hummer
, Mark Chin, Charlotte M. Deane
:
Humanization of antibodies using a machine learning approach on large-scale repertoire data. Bioinform. 37(22): 4041-4047 (2021) - [j76]Dominik Schwarz
, Guy Georges, Sebastian Kelm
, Jiye Shi, Anna Vangone
, Charlotte M. Deane
:
Co-evolutionary distance predictions contain flexibility information. Bioinform. 38(1): 65-72 (2021) - [j75]Florian Klimm, Charlotte M. Deane, Gesine Reinert:
Hypergraphs for predicting essential genes using multiprotein complex data. J. Complex Networks 9(2) (2021) - [j74]Matthew I. J. Raybould
, Claire Marks
, Aleksandr Kovaltsuk
, Alan P. Lewis, Jiye Shi
, Charlotte M. Deane:
Public Baseline and shared response structures support the theory of antibody repertoire functional commonality. PLoS Comput. Biol. 17(3) (2021) - [j73]Sarah A. Robinson
, Matthew I. J. Raybould
, Constantin Schneider
, Wing Ki Wong
, Claire Marks
, Charlotte M. Deane:
Epitope profiling using computational structural modelling demonstrated on coronavirus-binding antibodies. PLoS Comput. Biol. 17(12) (2021) - 2020
- [j72]Fergus Boyles
, Charlotte M. Deane, Garrett M. Morris
:
Learning from the ligand: using ligand-based features to improve binding affinity prediction. Bioinform. 36(3): 758-764 (2020) - [j71]Mark Chonofsky
, Saulo Henrique Pires de Oliveira, Konrad Krawczyk
, Charlotte M. Deane
:
The evolution of contact prediction: evidence that contact selection in statistical contact prediction is changing. Bioinform. 36(6): 1750-1756 (2020) - [j70]Wing Ki Wong
, Claire Marks, Jinwoo Leem
, Alan P. Lewis, Jiye Shi, Charlotte M. Deane
:
TCRBuilder: multi-state T-cell receptor structure prediction. Bioinform. 36(11): 3580-3581 (2020) - [j69]Fergus Imrie
, Anthony R. Bradley, Mihaela van der Schaar, Charlotte M. Deane
:
Deep Generative Models for 3D Linker Design. J. Chem. Inf. Model. 60(4): 1983-1995 (2020) - [j68]Jack Scantlebury
, Nathan Brown
, Frank von Delft
, Charlotte M. Deane
:
Data Set Augmentation Allows Deep Learning-Based Virtual Screening to Better Generalize to Unseen Target Classes and Highlight Important Binding Interactions. J. Chem. Inf. Model. 60(8): 3722-3730 (2020) - [j67]Matthew I. J. Raybould
, Claire Marks
, Alan P. Lewis, Jiye Shi
, Alexander Bujotzek, Bruck Taddese
, Charlotte M. Deane
:
Thera-SAbDab: the Therapeutic Structural Antibody Database. Nucleic Acids Res. 48(Database-Issue): D383-D388 (2020) - [j66]Aleksandr Kovaltsuk
, Matthew I. J. Raybould
, Wing Ki Wong
, Claire Marks
, Sebastian Kelm
, James Snowden
, Johannes Trück
, Charlotte M. Deane
:
Structural diversity of B-cell receptor repertoires along the B-cell differentiation axis in humans and mice. PLoS Comput. Biol. 16(2) (2020)
2010 – 2019
- 2019
- [j65]Wing Ki Wong
, Guy Georges, Francesca Ros, Sebastian Kelm
, Alan P. Lewis, Bruck Taddese
, Jinwoo Leem
, Charlotte M. Deane
:
SCALOP: sequence-based antibody canonical loop structure annotation. Bioinform. 35(10): 1774-1776 (2019) - [j64]Claire Marks
, Charlotte M. Deane
:
Increasing the accuracy of protein loop structure prediction with evolutionary constraints. Bioinform. 35(15): 2585-2592 (2019) - [j63]Lyuba V. Bozhilova
, Alan Whitmore, Jonny Wray, Gesine Reinert, Charlotte M. Deane
:
Measuring rank robustness in scored protein interaction networks. BMC Bioinform. 20(1): 446:1-446:14 (2019) - [j62]Luis Ospina-Forero
, Charlotte M. Deane
, Gesine Reinert:
Assessment of model fit via network comparison methods based on subgraph counts. J. Complex Networks 7(2): 226-253 (2019) - [j61]Jean-Paul Ebejer
, Paul W. Finn, Wing Ki Wong
, Charlotte M. Deane
, Garrett M. Morris
:
Ligity: A Non-Superpositional, Knowledge-Based Approach to Virtual Screening. J. Chem. Inf. Model. 59(6): 2600-2616 (2019) - [j60]Samuel Demharter
, Bernhard Knapp
, Charlotte M. Deane
, Peter Minary:
HLA-DM Stabilizes the Empty MHCII Binding Groove: A Model Using Customized Natural Move Monte Carlo. J. Chem. Inf. Model. 59(6): 2894-2899 (2019) - [j59]Bernhard Knapp
, P. Anton van der Merwe, Omer Dushek, Charlotte M. Deane
:
MHC binding affects the dynamics of different T-cell receptors in different ways. PLoS Comput. Biol. 15(9) (2019) - 2018
- [j58]Konrad Krawczyk
, Samuel Demharter
, Bernhard Knapp, Charlotte M. Deane
, Peter Minary:
In silico structural modeling of multiple epigenetic marks on DNA. Bioinform. 34(1): 41-48 (2018) - [j57]Claire Marks, Jiye Shi, Charlotte M. Deane
:
Predicting loop conformational ensembles. Bioinform. 34(6): 949-956 (2018) - [j56]Malte Lücken
, M. J. T. Page, A. J. Crosby, S. Mason, Gesine Reinert, Charlotte M. Deane
:
CommWalker: correctly evaluating modules in molecular networks in light of annotation bias. Bioinform. 34(6): 994-1000 (2018) - [j55]Saulo Henrique Pires de Oliveira, Eleanor C. Law
, Jiye Shi, Charlotte M. Deane
:
Sequential search leads to faster, more efficient fragment-based de novo protein structure prediction. Bioinform. 34(7): 1132-1140 (2018) - [j54]Bernhard Knapp
, Marta Alcalá, Hao Zhang, Clare E. West
, P. Anton van der Merwe, Charlotte M. Deane
:
pyHVis3D: visualising molecular simulation deduced H-bond networks in 3D: application to T-cell receptor interactions. Bioinform. 34(11): 1941-1943 (2018) - [j53]Saulo Henrique Pires de Oliveira, Charlotte M. Deane
:
Combining co-evolution and secondary structure prediction to improve fragment library generation. Bioinform. 34(13): 2219-2227 (2018) - [j52]Anatol E. Wegner, Luis Ospina-Forero
, Robert E. Gaunt, Charlotte M. Deane
, Gesine Reinert:
Identifying networks with common organizational principles. J. Complex Networks 6(6): 887-913 (2018) - [j51]Fergus Imrie
, Anthony R. Bradley, Mihaela van der Schaar
, Charlotte M. Deane
:
Protein Family-Specific Models Using Deep Neural Networks and Transfer Learning Improve Virtual Screening and Highlight the Need for More Data. J. Chem. Inf. Model. 58(11): 2319-2330 (2018) - [j50]Jinwoo Leem
, Saulo Henrique Pires de Oliveira, Konrad Krawczyk
, Charlotte M. Deane
:
STCRDab: the structural T-cell receptor database. Nucleic Acids Res. 46(Database-Issue): D406-D412 (2018) - 2017
- [j49]Saulo Henrique Pires de Oliveira, Jiye Shi, Charlotte M. Deane
:
Comparing co-evolution methods and their application to template-free protein structure prediction. Bioinform. 33(3): 373-381 (2017) - [j48]Claire Marks
, Jaroslaw Nowak, Stefan Klostermann, Guy Georges, James Dunbar, Jiye Shi, Sebastian Kelm
, Charlotte M. Deane
:
Sphinx: merging knowledge-based and ab initio approaches to improve protein loop prediction. Bioinform. 33(9): 1346-1353 (2017) - [j47]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, Charlotte M. Deane
, Bernhard Knapp:
Ten simple rules for surviving an interdisciplinary PhD. PLoS Comput. Biol. 13(5) (2017) - [i1]Anatol E. Wegner, Luis Ospina-Forero, Robert E. Gaunt, Charlotte M. Deane, Gesine Reinert:
Identifying networks with common organizational principles. CoRR abs/1704.00387 (2017) - 2016
- [j46]Reyhaneh Esmaielbeiki, Konrad Krawczyk
, Bernhard Knapp, Jean-Christophe Nebel
, Charlotte M. Deane
:
Progress and challenges in predicting protein interfaces. Briefings Bioinform. 17(1): 117-131 (2016) - [j45]Bernhard Knapp, Samuel Demharter, Charlotte M. Deane
, Peter Minary:
Exploring peptide/MHC detachment processes using hierarchical natural move Monte Carlo. Bioinform. 32(2): 181-186 (2016) - [j44]James Dunbar, Charlotte M. Deane
:
ANARCI: antigen receptor numbering and receptor classification. Bioinform. 32(2): 298-300 (2016) - [j43]Bernhard Knapp, Charlotte M. Deane
:
T-Cell Receptor Binding Affects the Dynamics of the Peptide/MHC-I Complex. J. Chem. Inf. Model. 56(1): 46-53 (2016) - [j42]Konrad Krawczyk
, Adelene Y. L. Sim, Bernhard Knapp, Charlotte M. Deane
, Peter Minary:
Tertiary Element Interaction in HIV-1 TAR. J. Chem. Inf. Model. 56(9): 1746-1754 (2016) - [j41]James Dunbar, Konrad Krawczyk
, Jinwoo Leem
, Claire Marks
, Jaroslaw Nowak, Cristian Regep, Guy Georges, Sebastian Kelm
, Bojana Popovic, Charlotte M. Deane
:
SAbPred: a structure-based antibody prediction server. Nucleic Acids Res. 44(Webserver-Issue): W474-W478 (2016) - 2015
- [j40]Bernhard Knapp, Samuel Demharter
, Reyhaneh Esmaielbeiki, Charlotte M. Deane
:
Current status and future challenges in T-cell receptor/peptide/MHC molecular dynamics simulations. Briefings Bioinform. 16(6): 1035-1044 (2015) - [j39]Anthony R. Bradley, Ian D. Wall, Frank von Delft
, Darren V. S. Green
, Charlotte M. Deane
, Brian D. Marsden:
WONKA: objective novel complex analysis for ensembles of protein-ligand structures. J. Comput. Aided Mol. Des. 29(10): 963-973 (2015) - [j38]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, Timo Minssen
, James M. Osborne
, Verena Paulitschke, Joe Pitt-Francis
, Jelena Todoric, Christian A. Yates
, David Gavaghan
, Charlotte M. Deane
:
Ten Simple Rules for a Successful Cross-Disciplinary Collaboration. PLoS Comput. Biol. 11(4) (2015) - [j37]Hannah Edwards, Charlotte M. Deane
:
Structural Bridges through Fold Space. PLoS Comput. Biol. 11(9) (2015) - 2014
- [j36]Konrad Krawczyk
, Xiaofeng Liu, Terry Baker, Jiye Shi
, Charlotte M. Deane
:
Improving B-cell epitope prediction and its application to global antibody-antigen docking. Bioinform. 30(16): 2288-2294 (2014) - [j35]Waqar Ali, Tiago Rito
, Gesine Reinert
, Fengzhu Sun, Charlotte M. Deane
:
Alignment-free protein interaction network comparison. Bioinform. 30(17): 430-437 (2014) - [j34]Hung Dien, Charlotte M. Deane
, Bernhard Knapp:
Gro2mat: A package to efficiently read gromacs output in MATLAB. J. Comput. Chem. 35(20): 1528-1531 (2014) - [j33]Henry R. Wilman
, Jean-Paul Ebejer
, Jiye Shi
, Charlotte M. Deane
, Bernhard Knapp:
Crowdsourcing Yields a New Standard for Kinks in Protein Helices. J. Chem. Inf. Model. 54(9): 2585-2593 (2014) - [j32]Anthony R. Bradley, Ian D. Wall, Darren V. S. Green
, Charlotte M. Deane
, Brian D. Marsden:
OOMMPPAA: A Tool To Aid Directed Synthesis by the Combined Analysis of Activity and Structural Data. J. Chem. Inf. Model. 54(10): 2636-2646 (2014) - [j31]James Dunbar, Konrad Krawczyk
, Jinwoo Leem
, Terry Baker, Angelika Fuchs, Guy Georges, Jiye Shi
, Charlotte M. Deane
:
SAbDab: the structural antibody database. Nucleic Acids Res. 42(Database-Issue): 1140-1146 (2014) - [j30]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, Gary R. Mirams
, Joe Pitt-Francis
, Biswa Sengupta
, David W. Wright, Christian A. Yates
, David Gavaghan
, Stephen Emmott, Charlotte M. Deane
:
Ten Simple Rules for Effective Computational Research. PLoS Comput. Biol. 10(3) (2014) - [j29]Bernhard Knapp, James Dunbar, Charlotte M. Deane
:
Large Scale Characterization of the LC13 TCR and HLA-B8 Structural Landscape in Reaction to 172 Altered Peptide Ligands: A Molecular Dynamics Simulation Study. PLoS Comput. Biol. 10(8) (2014) - [j28]James Dunbar, Bernhard Knapp, Angelika Fuchs, Jiye Shi
, Charlotte M. Deane
:
Examining Variable Domain Orientations in Antigen Receptors Gives Insight into TCR-Like Antibody Design. PLoS Comput. Biol. 10(9) (2014) - 2013
- [j27]Jamie R. Hill, Charlotte M. Deane
:
MP-T: improving membrane protein alignment for structure prediction. Bioinform. 29(1): 54-61 (2013) - [j26]Jean-Paul Ebejer
, Jamie R. Hill, Sebastian Kelm
, Jiye Shi
, Charlotte M. Deane
:
Memoir: template-based structure prediction for membrane proteins. Nucleic Acids Res. 41(Webserver-Issue): 379-383 (2013) - [j25]Hannah Edwards, Sanne Abeln
, Charlotte M. Deane
:
Exploring Fold Space Preferences of New-born and Ancient Protein Superfamilies. PLoS Comput. Biol. 9(11) (2013) - 2012
- [j24]Martin Mann
, Rhodri Saunders
, Cameron Smith, Rolf Backofen, Charlotte M. Deane
:
Producing High-Accuracy Lattice Models from Protein Atomic Coordinates Including Side Chains. Adv. Bioinformatics 2012: 148045:1-148045:6 (2012) - [j23]Tiago Rito
, Charlotte M. Deane
, Gesine Reinert
:
The Importance of Age and High Degree, in Protein-Protein Interaction Networks. J. Comput. Biol. 19(6): 785-795 (2012) - [j22]Jean-Paul Ebejer
, Garrett M. Morris
, Charlotte M. Deane
:
Freely Available Conformer Generation Methods: How Good Are They? J. Chem. Inf. Model. 52(5): 1146-1158 (2012) - [j21]Anna C. F. Lewis, Nick S. Jones
, Mason A. Porter, Charlotte M. Deane
:
What Evidence Is There for the Homology of Protein-Protein Interactions? PLoS Comput. Biol. 8(9) (2012) - 2011
- [j20]Jamie R. Hill, Sebastian Kelm
, Jiye Shi
, Charlotte M. Deane
:
Environment specific substitution tables improve membrane protein alignment. Bioinform. 27(13): 15-23 (2011) - 2010
- [j19]Braddon K. Lance, Charlotte M. Deane
, Graham R. Wood:
Exploring the potential of template-based modelling. Bioinform. 26(15): 1849-1856 (2010) - [j18]Tiago Rito
, Zi Wang, Charlotte M. Deane
, Gesine Reinert
:
How threshold behaviour affects the use of subgraphs for network comparison. Bioinform. 26(18) (2010) - [j17]Sebastian Kelm
, Jiye Shi
, Charlotte M. Deane
:
MEDELLER: homology-based coordinate generation for membrane proteins. Bioinform. 26(22): 2833-2840 (2010) - [j16]Jonathan J. Ellis
, Fabien P. E. Huard, Charlotte M. Deane
, Sheenal Srivastava, Graham R. Wood:
Directionality in protein fold prediction. BMC Bioinform. 11: 172 (2010) - [j15]Rebecca Hamer, Pao-Yang Chen
, Judith P. Armitage, Gesine Reinert
, Charlotte M. Deane
:
Deciphering chemotaxis pathways using cross species comparisons. BMC Syst. Biol. 4: 3 (2010) - [j14]Anna C. F. Lewis, Nick S. Jones
, Mason A. Porter, Charlotte M. Deane
:
The function of communities in protein interaction networks at multiple scales. BMC Syst. Biol. 4: 100 (2010) - [j13]Sumeet Agarwal
, Charlotte M. Deane
, Mason A. Porter, Nick S. Jones
:
Revisiting Date and Party Hubs: Novel Approaches to Role Assignment in Protein Interaction Networks. PLoS Comput. Biol. 6(6) (2010)
2000 – 2009
- 2009
- [j12]Sebastian Kelm
, Jiye Shi
, Charlotte M. Deane
:
iMembrane: homology-based membrane-insertion of proteins. Bioinform. 25(8): 1086-1088 (2009) - [j11]Waqar Ali, Charlotte M. Deane
:
Functionally guided alignment of protein interaction networks for module detection. Bioinform. 25(23): 3166-3173 (2009) - 2008
- [j10]Ramazan Saeed, Charlotte M. Deane
:
An assessment of the uses of homologous interactions. Bioinform. 24(5): 689-695 (2008) - [j9]Pao-Yang Chen
, Charlotte M. Deane
, Gesine Reinert
:
Predicting and Validating Protein Interactions Using Network Structure. PLoS Comput. Biol. 4(7) (2008) - 2007
- [j8]Pao-Yang Chen
, Charlotte M. Deane
, Gesine Reinert:
A statistical approach using network structure in the prediction of protein characteristics. Bioinform. 23(17): 2314-2321 (2007) - [j7]Ramazan Saeed, Charlotte M. Deane:
Using the protein interaction network to predict protein folds without homology. BMC Syst. Biol. 1(S-1): P69 (2007) - [j6]Sanne Abeln
, Charlotte M. Deane:
Linking evolution of protein structures through fragments. BMC Syst. Biol. 1(S-1): S12 (2007) - [j5]Sanne Abeln
, Carlo Teubner, Charlotte M. Deane
:
Using Phylogeny to Improve Genome-Wide Distant Homology Recognition. PLoS Comput. Biol. 3(1) (2007) - [c3]Charlotte M. Deane
, Mingqiang Dong, Fabien P. E. Huard, Braddon K. Lance, Graham R. Wood:
Cotranslational protein folding - fact or fiction? ISMB/ECCB (Supplement of Bioinformatics) 2007: 142-148 - 2006
- [j4]Ramazan Saeed, Charlotte M. Deane
:
Protein protein interactions, evolutionary rate, abundance and age. BMC Bioinform. 7: 128 (2006) - [c2]Fabien P. E. Huard, Charlotte M. Deane
, Graham R. Wood:
Modelling sequential protein folding under kinetic control. ISMB (Supplement of Bioinformatics) 2006: 203-210 - 2005
- [c1]Henry F. Winstanley, Sanne Abeln
, Charlotte M. Deane
:
How old is your fold? ISMB (Supplement of Bioinformatics) 2005: 449-458 - 2001
- [j3]Charlotte M. Deane
, Quentin Kaas
, Tom L. Blundell:
SCORE: predicting the core of protein models. Bioinform. 17(6): 541-550 (2001) - 2000
- [j2]David F. Burke
, Charlotte M. Deane
, Tom L. Blundell:
Browsing the SLoop database of structurally classified loops connecting elements of protein secondary structure. Bioinform. 16(6): 513-519 (2000)
1990 – 1999
- 1998
- [j1]Kenji Mizuguchi
, Charlotte M. Deane
, Tom L. Blundell, Mark S. Johnson, John P. Overington
:
JOY: protein sequence-structure representation and analysis. Bioinform. 14(7): 617-623 (1998)
Coauthor Index
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