A full list of the group's publications can be found below. Click on the relevant years to see the corresponding papers. You can also download this information as a bibtex file here.

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Galson, J.D., Schaetzle, S., Bashford-Rogers, R.J.M., Raybould, M.I.J., Kovaltsuk, A., Kilpatrick, G.J., Minter, R., Finch, D.K., Dias, J., James, L., Thomas, G., Lee, W.Y.J., Betley, J., Cavlan, O., Leech, A., Deane, C.M., Seoane, J., Caldas, C., Pennington, D., Pfeffer, P. & Osbourn, J. (Rxiv) Deep sequencing of B cell receptor repertoires from COVID-19 patients reveals strong convergent immune signatures bioRxiv
Raybould, M.I.J., Kovaltsuk, A., Marks, C. & Deane, C.M. (Rxiv) CoV-AbDab: the Coronavirus Antibody Database bioRxiv
Scantlebury, J., Brown, N., Von Delft, F. & Deane, C.M. (Rxiv) Dataset Augmentation Allows Deep Learning-Based Virtual Screening To Better Generalise To Unseen Target Classes, And Highlight Important Binding Interactions. BioRxiv
Klimm, F., Toledo, E.M., Monfeuga, T., Zhang, F., Deane, C.M. & Reinert, G. (Rxiv) Functional module detection through integration of single-cell RNA sequencing data with protein-protein interaction networks. BioRxiv
Leung, S., Bodkin, M., von Delft, F., Brennan, P. & Morris, G.M. (Rxiv) SuCOS is Better than RMSD for Evaluating Fragment Elaboration and Docking Poses ChemRxiv
Ghraichy, M., Galson, J.D., Kovaltsuk, A., von Niederhäusern, V., Schmid, J.M., Miho, E., Kelly, D.F., Deane, C.M. & Trück, J. (Rxiv) Maturation of Naïve and Antigen-experienced B-cell Receptor Repertoires with Age BioRxiv
Pardo-Diaz, J., Bozhilova, L.V., Beguerisse-Diaz, M., Poole, P.S., Deane, C.M. & Reinert, G. (bioRxiv) Robust gene coexpression networks using signed distance correlation bioRxiv
Bozhilova, L.V., Pardo-Diaz, J., Reisert, G. & Deane, C.M. (Rxiv) COGENT: evaluating the consistency of gene co-expression networks bioRxiv
Richardson, E., Galson, J.D., Kellam, P., Kelly, D.F., Smith, S.E., Palser, A., Watson, S. & Deane, C.M. (Rxiv) A computational method for immune repertoire mining that identifies novel binders from different clonotypes, demonstrated by identifying anti-Pertussis toxoid antibodies bioRxiv
Wang, Y., Tsitsiklis, A., Gao, W., Chu, H., Zhang, Y., Li, W., Wong, W.K., Deane, C.M., Neau, D., Slansky, J.E., Thomas, P.G., Robey, E.A. & Dai, S. (Rxiv) Novel Vβ specific germline contacts shape an elite controller T cell response bioRxiv
Klimm, F., Deane, C.M. & Reinert, G. (Rxiv) Hypergraphs for predicting essential genes using multiprotein complex data BioRxiv
Outeiral, C., Morris, G.M., Shi, J., Strahm, M., Benjamin, S.C. & Deane, C.M. (Rxiv) Investigating the potential for a limited quantum speedup on protein lattice problems Rxiv
Wong, W.K., Robinson, S.A., Bujotzek, A., Georges, G., Lewis, A.P., Shi, J., Snowden, J., Taddese, B. & Deane, C.M. (Rxiv) Ab-Ligity: Identifying sequence-dissimilar antibodies that bind to the same epitope BioRxiv
Raybould, M.I.J., Marks, C., Kovaltsuk, A., Lewis, A.P., Shi, J. & Deane, C.M. (Rxiv) Evidence of Antibody Repertoire Functional Convergence through Public Baseline and Shared Response Structures BioRxiv
Outeiral, C., Strahm, M., Shi, J., Morris, G.M., Benjamin, S.C. & Deane, C.M. (2020) The prospects of quantum computing in computational molecular biology WIREs
Marks, C. & Deane, C.M. (2020) How repertoire data is changing antibody science Journal of Biological Chemistry
Wong, W.K., Marks, C., Leem, J., Lewis, A.P., Shi, J. & Deane, C.M. (2020) TCRBuilder: Multi-state T-cell receptor structure prediction Bioinformatics, ():btaa194
Chan, L., Hutchison, G.R. & Morris, G.M. (2020) BOKEI: Bayesian optimization using knowledge of correlated torsions and expected improvement for conformer generation Physical Chemistry Chemical Physics, 22(9):5211-5219
Imrie, F., Bradley, A.R., van der Schaar, M. & Deane, C.M. (2020) Deep Generative Models for 3D Linker Design Journal of Chemical Information Modeling, 60(4):1983-1995
Kovaltsuk, A., Raybould, M.I.J., Wong, W.K., Marks, C., Kelm, S., Snowden, J., Trück, J. & Deane, C.M. (2020) Structural Diversity of B-cell Receptor Repertoires along the B-cell Differentiation Axis in Humans and Mice PLoS Computational Biology, 16(2):e1007636
Raybould, M.I.J., Marks, C., Lewis, A.P., Shi, J., Bujotzek, A., Taddese, B. & Deane, C.M. (2020) Thera-SAbDab: the Therapeutic Structural Antibody Database Nucleic Acids Research, 48(D1):D383-D388
Knapp, B., van der Merwe, P.A., Dushek, O. & Deane, C.M. (2019) MHC binding affects the dynamics of different T-cell receptors in different ways PLoS Computational Biology, 15:1-17
Wong, W.K., Leem, J. & Deane, C.M. (2019) Comparative analysis of the CDR loops of antigen receptors Frontiers in Immunology, 10:2454
Ebejer, J.P., Finn, P.W., Wong, W.K., Deane, C.M. & Morris, G.M. (2019) Ligity: A Non-Superpositional, Knowledge-Based Approach to Virtual Screening Journal of Chemical Information and Modeling, 59(6):2600-2616
Chan, L., Hutchison, G.R. & Morris, G.M. (2019) Bayesian Optimization for Conformer Generation Journal of Cheminformatics, 11:32
Raybould, M.I.J., Marks, C., Krawczyk, K., Taddese, B., Nowak, J., Lewis, A.P., Bujotzek, A., Shi, J. & Deane, C.M. (2019) Five Computational Developability Guidelines for Therapeutic Antibody Profiling Proceedings of the National Academy of Sciences USA, 116(10):4025-4030
Chonofsky, M., de Oliveira, S.H.P., Krawczyk, K. & Deane, C.M. (2019) The evolution of contact prediction: Evidence that contact selection in statistical contact prediction is changing Bioinformatics, ():btz816
West, C.E., de Oliveira, S.H.P. & Deane, C.M. (2019) RFQAmodel: Random Forest Quality Assessment to identify a predicted protein structure in the correct fold PLoS One, 14(10):1-16
Bozhilova, L.V., Whitmore, A.V., Wray, J., Reinert, G. & Deane, C.M. (2019) Measuring rank robustness in scored protein interaction networks BMC Bioinformatics, 20:446
Boyles, F., Deane, C.M. & Morris, G.M. (2019) Learning From The Ligand: Using Ligand-Based Features To Improve Binding Affinity Prediction Bioinformatics, ():btz665
Schwarz, D., Merget, B., Deane, C.M. & Fulle, S. (2019) Modeling conformational flexibility of kinases in inactive states Proteins, 87(11):943-951
Krawczyk, K., Raybould, M.I.J., Kovaltsuk, A. & Deane, C.M. (2019) Looking for Therapeutic Antibodies in Next Generation Sequencing Repositories mAbs, 11(7):1197-1205
Raybould, M.I.J., Wong, W.K. & Deane, C.M. (2019) Antibody-antigen Complex Modelling in the Era of Immunoglobulin Repertoire Sequencing Molecular Systems Design & Engineering, 4:679-688
Demharter, S., Knapp, B., Deane, C.M. & Minary, P. (2019) HLA-DM stabilises the empty MHCII binding groove: A model using customised Natural Move Monte Carlo Journal of Chemical Information and Modeling, 59(6):2894-2899
Marks, C. & Deane, C.M. (2018) Increasing the accuracy of protein loop structure prediction with evolutionary constraints Bioinformatics, ():bty996
Kovaltsuk, A., Krawczyk, K., Kelm, S., Snowden, J. & Deane, C.M. (2018) Filtering Next-Generation Sequencing of the Ig Gene Repertoire Data Using Antibody Structural Information Journal of Immunology, 201(12):3694-3704
Leem, J., Georges, G., Shi, J. & Deane, C.M. (2018) Antibody side chain conformations are position-dependent Proteins: Structure, Function, and Bioinformatics, 86(4):383-392
Knapp, B., Alcala, M., Zhang, H., West, C.E., van der Merwe, P.A. & Deane, C.M. (2018) pyHVis3D: Visualising Molecular Simulation deduced H-bond networks in 3D: Application to T-cell receptor interactions Bioinformatics, ():btx842
Wegner, A.E., Ospina-Forero, L., Gaunt, R.E., Deane, C.M. & Reinert, G. (2018) Identifying networks with common organizational principles Journal of Complex Networks, ():cny003
Marks, C., Shi, J. & Deane, C.M. (2018) Predicting loop conformational ensembles Bioinformatics, 34(6):949-956
Knapp, B., Ospina, L. & Deane, C.M. (2018) Avoiding false positive conclusions in molecular simulation: the importance of replicas Journal of Chemical Theory and Computation, 14(12):6127-6138
Wong, W.K., Georges, G., Ros, F., Kelm, S., Lewis, A.P., Taddese, B., Leem, J. & Deane, C.M. (2018) SCALOP: sequence-based antibody canonical loop structure annotation Bioinformatics, 35(10):1774-1776
Imrie, F., Bradley, A.R., van der Schaar, M. & Deane, C.M. (2018) Protein Family-specific Models using Deep Neural Networks and Transfer Learning Improve Virtual Screening and Highlight the Need for More Data Journal of Chemical Information and Modeling, 58(11):2319-2330
Ospina-Forero, L., Deane, C.M. & Reinert, G. (2018) Assessment of model fit via network comparison methods based on subgraph counts Journal of Complex Networks, ():cny017
Kovaltsuk, A., Leem, J., Kelm, S., Snowden, J., Deane, C.M. & Krawczyk, K. (2018) Observed Antibody Space: a resource for data mining next generation sequencing of antibody repertoires Journal of Immunology, 201(7):2502-2509
Krawczyk, K., Kelm, S., Kovaltsuk, A., Galson, J.D., Kelly, D., Trück, J., Regep, C., Leem, J., Wong, W.K., Nowak, J., Snowden, J., Wright, M., Starkie, L., Scott-Turner, A., Shi, J. & Deane, C.M. (2018) Structurally Mapping Antibody Repertoires Frontiers in Immunology, 9:1698
de Oliveira, S.H.P. & Deane, C.M. (2018) Combining co-evolution and secondary structure prediction to improve fragment library generation Bioinformatics, ():bty084
Mardia, K.V., Sriram, K. & Deane, C.M. (2018) A statistical model for helices with applications Biometrics, 74(3):845-854
Kovaltsuk, A., Krawczyk, K., Galson, J.D., Kelly, D.F., Deane, C.M. & Trück, J. (2017) How B-Cell Receptor Repertoire Sequencing Can Be Enriched with Structural Antibody Data Frontiers in Immunology, 8:1753
de Oliveira, S.H.P., Law, E.C., Shi, J. & Deane, C.M. (2017) Sequential search leads to faster, more efficient fragment-based de novo protein structure prediction Bioinformatics, 10
Knapp, B., Dunbar, J., Alcala, M. & Deane, C.M. (2017) Variable Regions of Antibodies and T-Cell Receptors May Not Be Sufficient in Molecular Simulations Investigating Binding Journal of Chemical Theory and Computation, 13(7):3097-3105
Pearce, N.M., Bradley, A.R., Krojer, T., Marsden, B.D., Deane, C.M. & von Delft, F. (2017) Partial-occupancy binders identified by the Pan-Dataset Density Analysis method offer new chemical opportunities and reveal cryptic binding sites Structural Dynamics, 4(3):32104
de Oliveira, S. & Deane, C. (2017) Co-evolution techniques are reshaping the way we do structural bioinformatics F1000Research, 6:1224
Marks, C., Nowak, J., Klostermann, S., Georges, G., Dunbar, J., Shi, J., Kelm, S. & Deane, C.M. (2017) Sphinx: merging knowledge-based and ab initio approaches to improve protein loop prediction Bioinformatics, 33(9):1346-1353
Marks, C. & Deane, C.M. (2017) Antibody H3 Structure Prediction Computional and Structural Biotechnology Journal, 15:222-231
Chen, J.W.C., Chen, Z.A., Rogala, K.B., Metz, J., Deane, C.M., Rappsilber, J. & Wakefield, J.G. (2017) Cross-linking mass spectrometry identifies new interfaces of Augmin required to localise the gamma-tubulin ring complex to the mitotic spindle. Biology open, 6(5):654-663
Deane, C.M. & Vásquez, M. (2017) Developability of Biotherapeutics: Computational Approaches . Edited by Sandeep Kumar and Satish K. Singh MAbs, 9(1):12-14
Demharter, S., Pearce, N., Beattie, K., Frost, I., Leem, J., Martin, A., Oppenheimer, R., Regep, C., Rukat, T., Skates, A., Trendel, N., Gavaghan, D.J., Deane, C.M. & Knapp, B. (2017) Ten simple rules for surviving an interdisciplinary PhD PLOS Computational Biology, 13(5):e1005512
Krawczyk, K., Demharter, S., Knapp, B., Deane, C.M. & Minary, P. (2017) In silico structural modeling of multiple epigenetic marks on DNA Bioinformatics
Luecken, M.D., Page, M.J.T., Crosby, A.J., Mason, S., Reinert, G. & Deane, C.M. (2017) CommWalker: Correctly Evaluating Modules in Molecular Networks in Light of Annotation Bias Bioinformatics
Leem, J., de Oliveira, S., Krawczyk, K. & Deane, C. (2017) STCRDab: the structural T-cell receptor database Nucleic Acids Research
Pearce, N.M., Krojer, T., Bradley, A.R., Collins, P., Nowak, R.P., Talon, R., Marsden, B.D., Kelm, S., Shi, J., Deane, C.M. & von Delft, F. (2017) A multi-crystal method for extracting obscured crystallographic states from conventionally uninterpretable electron density Nature Communications, 8:15123
Parks, T., Mirabel, M.M., Kado, J., Auckland, K., Nowak, J., Rautanen, A., Mentzer, A.J., Marijon, E., Jouven, X., Perman, M.L., Cua, T., Kauwe, J.K., Allen, J.B., Taylor, H., Robson, K.J., Deane, C.M., Steer, A.C. & Hill, A.V.S. (2017) Association between a common immunoglobulin heavy chain allele and rheumatic heart disease risk in Oceania Nature Communications, 8(14946)
Krawczyk, K., Dunbar, J. & Deane, C.M. (2017) Computational Tools for Aiding Rational Antibody Design Methods in Molecular Biology, 1529:399-416
de Oliveira, S.H.P., Shi, J. & Deane, C.M. (2017) Comparing co-evolution methods and their application to template-free protein structure prediction Bioinformatics, 33(3):373-381
Regep, C., Georges, G., Shi, J., Popovic, B. & Deane, C.M. (2017) The H3 loop of antibodies shows unique structural characteristics Proteins: Structure, Function, and Bioinformatics, 85(7):1311-1318
Dunbar, J., Krawczyk, K., Leem, J., Marks, C., Nowak, J., Regep, C., Georges, G., Kelm, S., Popovic, B. & Deane, C.M. (2016) SAbPred: a structure-based antibody prediction server. Nucleic Acids Research, 44(W1):W474-W478
Demharter, S., Knapp, B., Deane, C.M. & Minary, P. (2016) Modeling Functional Motions of Biological Systems by Customized Natural Moves Biophys. J., 111(4):710-721
Nowak, J., Baker, T., Georges, G., Kelm, S., Klostermann, S., Shi, J., Sridharan, S. & Deane, C.M. (2016) Length-independent structural similarities enrich the antibody CDR canonical class model. MAbs, 8(4):751-760
Ali, W., Wegner, A.E., Gaunt, R.E., Deane, C.M. & Reinert, G. (2016) Comparison of large networks with sub-sampling strategies Sci. Rep., 6:28955
Leem, J., Dunbar, J., Georges, G., Shi, J. & Deane, C.M. (2016) ABodyBuilder: automated antibody structure prediction with data-driven accuracy estimation MAbs, 8(7):1259-1268
Krawczyk, K., Sim, A.Y.L., Knapp, B., Deane, C.M. & Minary, P. (2016) Tertiary Element Interaction in HIV-1 TAR J. Chem. Inf. Model., 56(9):1746-1754
Law, E.C., Wilman, H.R., Kelm, S., Shi, J. & Deane, C.M. (2016) Examining the Conservation of Kinks in Alpha Helices PLoS One, 11(6):e0157553
Zhang, H., Lim, H.S., Knapp, B., Deane, C.M., Aleksic, M., Dushek, O. & van der Merwe, P.A. (2016) The contribution of major histocompatibility complex contacts to the affinity and kinetics of T cell receptor binding Sci. Rep., 6:35326
Wan, S., Knapp, B., Wright, D.W., Deane, C.M. & Coveney, P.V. (2015) Rapid, Precise, and Reproducible Prediction of Peptide.MHC Binding Affinities from Molecular Dynamics That Correlate Well with Experiment J. Chem. Theory Comput., 11(7):3346-3356
de Oliveira, S.H.P., Shi, J. & Deane, C.M. (2015) Building a Better Fragment Library for De Novo Protein Structure Prediction PLoS One, 10(4):e0123998
Alexander, L.T., Möbitz, H., Drueckes, P., Savitsky, P., Fedorov, O., Elkins, J.M., Deane, C.M., Cowan-Jacob, S.W. & Knapp, S. (2015) Type II Inhibitors Targeting CDK2. ACS Chem. Biol., 10(9):2116-2125
Knapp, B. & Deane, C.M. (2015) T-cell Receptor Binding Affects the Dynamics of the Peptide/MHC-I Complex. J. Chem. Inf. Model.
Knapp, B., Demharter, S., Deane, C.M. & Minary, P. (2015) Exploring peptide/MHC detachment processes using Hierarchical Natural Move Monte Carlo Bioinformatics, pages btv502
Dunbar, J. & Deane, C.M. (2015) ANARCI: Antigen receptor numbering and receptor classification Bioinformatics, pages btv552
Edwards, H. & Deane, C.M. (2015) Structural Bridges through Fold Space. PLoS Comput. Biol., 11(9):e1004466
Bujotzek, A., Dunbar, J., Lipsmeier, F., Schäfer, W., Antes, I., Deane, C.M. & Georges, G. (2015) Prediction of VH-VL domain orientation for antibody variable domain modeling. Proteins, 83(4):681-695
Knapp, B., Demharter, S., Esmaielbeiki, R. & Deane, C.M. (2015) Current status and future challenges in T-cell receptor/peptide/MHC molecular dynamics simulations Brief. Bioinform.
Knapp, B., Bardenet, R., Bernabeu, M.O., Bordas, R., Bruna, M., Calderhead, B., Cooper, J., Fletcher, A.G., Groen, D., Kuijper, B., Lewis, J., McInerny, G., Minssen, T., Osborne, J., Paulitschke, V., Pitt-Francis, J., Todoric, J., Yates, C.A., Gavaghan, D. & Deane, C.M. (2015) Ten Simple Rules for a Successful Cross-Disciplinary Collaboration. PLoS Comput. Biol., 11(4):e1004214
Esmaielbeiki, R., Krawczyk, K., Knapp, B., Nebel, J.C. & Deane, C.M. (2015) Progress and challenges in predicting protein interfaces Brief. Bioinform.
Palumbo, V., Pellacani, C., Heesom, K.J., Rogala, K.B., Deane, C.M., Mottier-Pavie, V., Gatti, M., Bonaccorsi, S. & Wakefield, J.G. (2015) Misato Controls Mitotic Microtubule Generation by Stabilizing the Tubulin Chaperone Protein-1 Complex. Curr. Biol.
Bradley, A.R., Wall, I.D., von Delft, F., Green, D.V.S., Deane, C.M. & Marsden, B.D. (2015) WONKA: objective novel complex analysis for ensembles of protein-ligand structures. J. Comput. Aided. Mol. Des.
Rogala, K.B., Dynes, N.J., Hatzopoulos, G.N., Yan, J., Pong, S.K., Robinson, C.V., Deane, C.M., Gönczy, P. & Vakonakis, I. (2015) The Caenorhabditis elegans protein SAS-5 forms large oligomeric assemblies critical for centriole formation Elife, 4:e07410
Dunbar, J., Knapp, B., Fuchs, A., Shi, J. & Deane, C.M. (2014) Examining Variable Domain Orientations in Antigen Receptors Gives Insight into TCR-Like Antibody Design PLoS Comput Biol, 10:e1003852
Dien, H., Deane, C.M. & Knapp, B. (2014) Gro2mat: A package to efficiently read gromacs output in MATLAB J. Comput. Chem., 35(20):1528-1531
Knapp, B., Dunbar, J. & Deane, C.M. (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 PLoS Comput Biol(8)pages e1003748
Ali, W., Rito, T., Reinert, G., Sun, F. & Deane, C.M. (2014) Alignment-free protein interaction network comparison Bioinformatics, 30(17):i430-i437
Dunbar, J., Krawczyk, K., Leem, J., Baker, T., Fuchs, A., Georges, G., Shi, J. & Deane, C.M. (2014) SAbDab: the structural antibody database Nucleic Acids Res., 42(Database issue):D1140--D1146
Wilman, H.R., Ebejer, J.P., Shi, J., Deane, C.M. & Knapp, B. (2014) Crowdsourcing Yields a New Standard for Kinks in Protein Helices. J. Chem. Inf. Model., 54(9):2585-2593
Krawczyk, K., Liu, X., Baker, T., Shi, J. & Deane, C.M. (2014) Improving B-cell epitope prediction and its application to global antibody-antigen docking Bioinformatics, 30(16):2288-2294
Wilman, H.R., Shi, J. & Deane, C.M. (2014) Helix kinks are equally prevalent in soluble and membrane proteins. Proteins, 82(9):1960-1970
Kelm, S., Vangone, A., Choi, Y., Ebejer, J.P., Shi, J. & Deane, C.M. (2014) Fragment-based modeling of membrane protein loops: successes, failures, and prospects for the future Proteins, 82(2):175-186
Osborne, J.M., Bernabeu, M.O., Bruna, M., Calderhead, B., Cooper, J., Dalchau, N., Dunn, S.J., Fletcher, A.G., Freeman, R., Groen, D., Knapp, B., McInerny, G.J., Mirams, G.R., Pitt-Francis, J., Sengupta, B., Wright, D.W., Yates, C.A., Gavaghan, D.J., Emmott, S. & Deane, C.M. (2014) Ten Simple Rules for Effective Computational Research PLoS Comput. Biol., 10(3):e1003506
Bradley, A.R., Wall, I.D., Green, D.V.S., Deane, C.M. & Marsden, B.D. (2014) OOMMPPAA: A Tool To Aid Directed Synthesis by the Combined Analysis of Activity and Structural Data J. Chem. Inf. Model., 54(10):2636-2646
Zheng, S., Moehlenbrink, J., Lu, Y.C., Zalmas, L.P., Sagum, C.A., Carr, S., McGouran, J.F., Alexander, L.T., Fedorov, O., Munro, S., Kessler, B., Bedford, M.T., Yu, Q. & La Thangue, N.B. (2013) Arginine methylation-dependent reader-writer interplay governs growth control by E2F-1 Mol. Cell, 52(1):37-51
Hischenhuber, B., Havlicek, H., Todoric, J., Höllrigl-Binder, S., Schreiner, W. & Knapp, B. (2013) Differential Geometric Analysis of Alterations in MH \alpha-Helices J. Comput. Chem., 34(21):1862-1879
Choi, Y., Agarwal, S. & Deane, C.M. (2013) How long is a piece of loop? PeerJ, 1
Ebejer, J.P., Fulle, S., Morris, G.M. & Finn, P.W. (2013) The emerging role of cloud computing in molecular modelling J. Mol. Graph. Model., 44:177-187
Lori, C., Lantella, A., Pasquo, A., Alexander, L.T., Knapp, S., Chiaraluce, R. & Consalvi, V. (2013) Effect of Single Amino Acid Substitution Observed in Cancer on Pim-1 Kinase Thermodynamic Stability and Structure PLoS One, 8(6):e64824
Kelm, S., Choi, Y. & Deane, C.M.; Kasabov, N. (eds). (2013) Protein Modelling and Structural Prediction In Springer Handb. Bio-/Neuro-informatics
Hill, J.R. & Deane, C.M. (2013) MP-T: improving membrane protein alignment for structure prediction Bioinformatics, 29(1):54-61
Dunbar, J., Fuchs, A., Shi, J. & Deane, C.M. (2013) ABangle: characterising the VH–VL orientation in antibodies Protein Design Selection & Engineering, 26(10):611-620
Ebejer, J.P., Hill, J.R., Kelm, S., Shi, J. & Deane, C.M. (2013) Memoir: template-based structure prediction for membrane proteins Nucleic Acids Res., 41(Web Server issue):W379--W383
Edwards, H., Abeln, S. & Deane, C.M. (2013) Exploring Fold Space Preferences of New-born and Ancient Protein Superfamilies PLoS Comput Biol, 9(11):e1003325
Harrington, L., Cheley, S., Alexander, L.T., Knapp, S. & Bayley, H. (2013) Stochastic detection of Pim protein kinases reveals electrostatically enhanced association of a peptide substrate Proc. Natl. Acad. Sci., 110(47):E4417--E4426
Krawczyk, K., Baker, T., Shi, J. & Deane, C.M. (2013) Antibody i-Patch prediction of the antibody binding site improves rigid local antibody-antigen docking Protein Eng. Des. Sel., 26(10):621-629
Luo, Q., Hamer, R., Reinert, G. & Deane, C.M. (2013) Local Network Patterns in Protein-Protein Interfaces PLoS One, 8(3):e57031
Knapp, B., Dorffner, G. & Schreiner, W. (2013) Early Relaxation Dynamics in the LC 13 T Cell Receptor in Reaction to 172 Altered Peptide Ligands: A Molecular Dynamics Simulation Study PLoS One, 8(6):e64464
Kashir, J., Konstantinidis, M., Jones, C., Lemmon, B., Lee, H.C., Hamer, R., Heindryckz, B., Deane, C.M., De Sutter, P., Fissore, R.A., Parrington, J., Wells, D. & Coward, K. (2012) A maternally inherited autosomal point mutation in human phospholipase C zeta (PLCζ) leads to male infertility. Hum. Reprod., 27(1):222-231
Mann, M., Saunders, R., Smith, C., Backofen, R. & Deane, C.M. (2012) Producing High-Accuracy Lattice Models from Protein Atomic Coordinates Including Side Chains Adv. Bioinformatics, 2012:e148045
Withers-Martinez, C., Suarez, C., Fulle, S., Kher, S., Penzo, M., Ebejer, J.P., Koussis, K., Hackett, F., Jirgensons, A., Finn, P. & Blackman, M.J. (2012) Plasmodium subtilisin-like protease 1 (SUB1): Insights into the active-site structure, specificity and function of a pan-malaria drug target Int. J. Parasitol., 42(6):597-612
Ebejer, J.P., Morris, G.M. & Deane, C.M. (2012) Freely Available Conformer Generation Methods: How Good Are They? J. Chem. Inf. Model., 52(5):1146-1158
Lewis, A.C.F., Jones, N.S., Porter, M.A. & Deane, C.M. (2012) What Evidence Is There for the Homology of Protein-Protein Interactions? PLoS Comput Biol, 8(9):e1002645
Rito, T., Deane, C.M. & Reinert, G. (2012) The importance of age and high degree, in protein-protein interaction networks J. Comput. Biol. A J. Comput. Mol. Cell Biol., 19(6):785-795
Pawelczyk, S., Scott, K.A., Hamer, R., Blades, G., Deane, C.M. & Wadhams, G.H. (2012) Predicting Inter-Species Cross-Talk in Two-Component Signalling Systems PLoS One, 7(5):e37737
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