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2020 – today
- 2024
[j101]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)- [j100]Carlos Outeiral
, Charlotte M. Deane:
Codon language embeddings provide strong signals for use in protein engineering. Nat. Mac. Intell. 6(2): 170-179 (2024) - [j99]Guy Durant, Fergus Boyles, Kristian Birchall, Charlotte M. Deane:
The future of machine learning for small-molecule drug discovery will be driven by data. Nat. Comput. Sci. 4(10): 735-743 (2024) - [c6]Pierre Glaser, Steffanie Paul, Alissa M. Hummer, Charlotte M. Deane, Debora Susan Marks, Alan Nawzad Amin:
Kernel-Based Evaluation of Conditional Biological Sequence Models. ICML 2024 - [c5]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. ICML 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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last updated on 2024-11-06 20:31 CET by the dblp team
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