Shaun M Kandathil
Shaun M Kandathil
Verified email at ucl.ac.uk
Title
Cited by
Cited by
Year
A review of the chemistry and pharmacology of the date fruits (Phoenix dactylifera L.)
MS Baliga, BRV Baliga, SM Kandathil, HP Bhat, PK Vayalil
Food research international 44 (7), 1812-1822, 2011
4732011
High precision in protein contact prediction using fully convolutional neural networks and minimal sequence features
DT Jones, SM Kandathil
Bioinformatics 34 (19), 3308-3315, 2018
892018
Deep learning extends de novo protein modelling coverage of genomes using iteratively predicted structural constraints
JG Greener, SM Kandathil, DT Jones
Nature communications 10 (1), 1-13, 2019
612019
Prediction of interresidue contacts with DeepMetaPSICOV in CASP13
SM Kandathil, JG Greener, DT Jones
Proteins: Structure, Function, and Bioinformatics 87 (12), 1092-1099, 2019
572019
Accuracy and tractability of a kriging model of intramolecular polarizable multipolar electrostatics and its application to histidine
SM Kandathil, TL Fletcher, Y Yuan, J Knowles, PLA Popelier
Journal of computational chemistry 34 (21), 1850–1861, 2013
512013
Recent developments in deep learning applied to protein structure prediction
SM Kandathil, JG Greener, DT Jones
Proteins: Structure, Function, and Bioinformatics 87 (12), 1179-1189, 2019
332019
The prediction of atomic kinetic energies from coordinates of surrounding atoms using kriging machine learning
TL Fletcher, SM Kandathil, PLA Popelier
Theoretical Chemistry Accounts 133 (7), 1-10, 2014
282014
Generating, maintaining, and exploiting diversity in a memetic algorithm for protein structure prediction
M Garza-Fabre, SM Kandathil, J Handl, J Knowles, SC Lovell
Evolutionary computation 24 (4), 577-607, 2016
272016
Toward a detailed understanding of search trajectories in fragment assembly approaches to protein structure prediction
SM Kandathil, J Handl, SC Lovell
Proteins: Structure, Function, and Bioinformatics 84, 411–426, 2016
162016
Accurate prediction of polarised high order electrostatic interactions for hydrogen bonded complexes using the machine learning method kriging
TJ Hughes, SM Kandathil, PLA Popelier
Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy 136, 32-41, 2015
142015
Proton tunnelling and promoting vibrations during the oxidation of ascorbate by ferricyanide?
SM Kandathil, MD Driscoll, RV Dunn, NS Scrutton, S Hay
Physical Chemistry Chemical Physics 16 (6), 2256-2259, 2014
112014
Adaptive HIV-1 evolutionary trajectories are constrained by protein stability
AS Olabode, SM Kandathil, SC Lovell, DL Robertson
Virus evolution 3 (2), 2017
82017
Improved fragment-based protein structure prediction by redesign of search heuristics
SM Kandathil, M Garza-Fabre, J Handl, SC Lovell
Scientific reports 8 (1), 1-14, 2018
72018
Deep learning extends de novo protein modelling coverage of genomes using iteratively predicted structural constraints. Nat Commun. 2019; 10: 1–13
JG Greener, SM Kandathil, DT Jones
6
Uncommon mutational profiles of metastatic colorectal cancer detected during routine genotyping using next generation sequencing
C Franczak, SM Kandathil, P Gilson, M Husson, M Rouyer, J Demange, ...
Scientific reports 9 (1), 1-8, 2019
32019
Deep learning-based prediction of protein structure using learned representations of multiple sequence alignments
SM Kandathil, JG Greener, AM Lau, DT Jones
bioRxiv, 2020
12020
DMPfold: fast de novo protein model generation from covarying sequences using predicted distances and iterative model building
JG Greener, SM Kandathil, DT Jones
arXiv preprint arXiv:1811.12355, 2018
12018
Using machine learning to explore the relevance of local and global features during conformational search in Rosetta
M Garza-Fabre, SM Kandathil, J Handl, JD Knowles, SC Lovell
Proceedings of the Companion Publication of the 2015 Annual Conference on …, 2015
12015
Near-complete protein structural modelling of the minimal genome
JG Greener, N Desai, SM Kandathil, DT Jones
arXiv preprint arXiv:2007.06623, 2020
2020
Reliable Generation of Native-Like Decoys Limits Predictive Ability in Fragment-Based Protein Structure Prediction
SM Kandathil, M Garza-Fabre, J Handl, SC Lovell
Biomolecules 9 (10), 612, 2019
2019
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Articles 1–20