All Stories

  1. Foldclass and Merizo-search: scalable structural similarity search for single- and multi-domain proteins using geometric learning

    Article • Bioinformatics, May 2025, Oxford University Press (OUP)

    Shaun Kandathil

  2. Metagenomic-scale analysis of the predicted protein structure universe

    Article • April 2025, Cold Spring Harbor Laboratory Press

    Shaun Kandathil

  3. CATH v4.4: major expansion of CATH by experimental and predicted structural data

    Article • Nucleic Acids Research, November 2024, Oxford University Press (OUP)

    Shaun Kandathil

  4. Exploring structural diversity across the protein universe with The Encyclopedia of Domains

    Article • Science, November 2024, American Association for the Advancement of Science

    Shaun Kandathil

  5. Deep learning for the PSIPRED Protein Analysis Workbench

    Article • Nucleic Acids Research, May 2024, Oxford University Press (OUP)

    Shaun Kandathil

  6. Foldclass and Merizo-search: embedding-based deep learning tools for protein domain segmentation, fold recognition and comparison

    Article • March 2024, Cold Spring Harbor Laboratory Press

    Shaun Kandathil

  7. Exploring structural diversity across the protein universe with The Encyclopedia of Domains

    Article • March 2024, Cold Spring Harbor Laboratory Press

    Shaun Kandathil

  8. Merizo: a rapid and accurate protein domain segmentation method using invariant point attention

    Article • Nature Communications, December 2023, Springer Science + Business Media

    Shaun Kandathil

  9. Merizo: a rapid and accurate domain segmentation method using invariant point attention

    Article • February 2023, Cold Spring Harbor Laboratory Press

    Shaun Kandathil

  10. Design in the DARK: Learning Deep Generative Models for De Novo Protein Design

    Article • January 2022, Cold Spring Harbor Laboratory Press

    Shaun Kandathil

  11. Ultrafast end-to-end protein structure prediction enables high-throughput exploration of uncharacterized proteins

    Article • Proceedings of the National Academy of Sciences, January 2022, Proceedings of the National Academy of Sciences

    Shaun Kandathil

  12. A guide to machine learning for biologists

    Article • Nature Reviews Molecular Cell Biology, September 2021, Springer Science + Business Media

    Shaun Kandathil

  13. Ultrafast end-to-end protein structure prediction enables high-throughput exploration of uncharacterised proteins

    Article • November 2020, Cold Spring Harbor Laboratory Press

    Shaun Kandathil

  14. Reliable Generation of Native-Like Decoys Limits Predictive Ability in Fragment-Based Protein Structure Prediction

    Article • Biomolecules, October 2019, MDPI AG

    Shaun Kandathil

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

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

    Shaun Kandathil

  16. 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

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

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

    Shaun Kandathil

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

    Article • March 2019, Cold Spring Harbor Laboratory Press

    Shaun Kandathil

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

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

    Shaun Kandathil

  20. 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

  21. 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

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

    Article • Evolutionary Computation, February 2016, The MIT Press

    Shaun Kandathil

  23. 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

  24. 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

  25. 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

  26. 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

  27. 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

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

    Article • Food Research International, August 2011, Elsevier

    Shaun Kandathil