All Stories

  1. Recent developments in deep learning applied to protein structure prediction

    Article • Proteins Structure Function and Bioinformatics, October 2019, Wiley

    Shaun Kandathil

  2. Deep learning extends de novo protein modelling coverage of genomes using iteratively predicted structural constraints

    Article • Nature Communications, September 2019, Springer Science + Business Media

    Shaun Kandathil

  3. Prediction of inter‐residue contacts with DeepMetaPSICOV in CASP13

    Article • Proteins Structure Function and Bioinformatics, July 2019, Wiley

    Shaun Kandathil

  4. Prediction of inter-residue contacts with DeepMetaPSICOV in CASP13

    Article • March 2019, Cold Spring Harbor Laboratory Press

    Shaun Kandathil

  5. Improved fragment-based protein structure prediction by redesign of search heuristics

    Article • Scientific Reports, September 2018, Springer Science + Business Media

    Shaun Kandathil

  6. High precision in protein contact prediction using fully convolutional neural networks and minimal sequence features

    Article • Bioinformatics, April 2018, Oxford University Press (OUP)

    Shaun Kandathil

  7. Toward a detailed understanding of search trajectories in fragment assembly approaches to protein structure prediction

    Article • Proteins Structure Function and Bioinformatics, February 2016, Wiley

    Shaun Kandathil

  8. Generating, Maintaining, and Exploiting Diversity in a Memetic Algorithm for Protein Structure Prediction

    Article • Evolutionary Computation, February 2016, The MIT Press

    Shaun Kandathil

  9. Using Machine Learning to Explore the Relevance of Local and Global Features During Conformational Search in Rosetta

    Article • July 2015, ACM (Association for Computing Machinery)

    Shaun Kandathil

  10. Accurate prediction of polarised high order electrostatic interactions for hydrogen bonded complexes using the machine learning method kriging

    Article • Spectrochimica Acta Part A Molecular and Biomolecular Spectroscopy, February 2015, Elsevier

    Professor Paul Popelier, Shaun Kandathil

  11. The prediction of atomic kinetic energies from coordinates of surrounding atoms using kriging machine learning

    Article • Theoretical Chemistry Accounts, May 2014, Springer Science + Business Media

    Professor Paul Popelier, Shaun Kandathil

  12. Proton tunnelling and promoting vibrations during the oxidation of ascorbate by ferricyanide?

    Article • Physical Chemistry Chemical Physics, January 2014, Royal Society of Chemistry

    Shaun Kandathil

  13. Accuracy and tractability of a kriging model of intramolecular polarizable multipolar electrostatics and its application to histidine

    Article • Journal of Computational Chemistry, May 2013, Wiley

    Professor Paul Popelier, Shaun Kandathil

  14. A review of the chemistry and pharmacology of the date fruits (Phoenix dactylifera L.)

    Article • Food Research International, August 2011, Elsevier

    Shaun Kandathil