Kandathil, S., Jones, D., Greener, J., & Lau, A. (2022). Ultrafast end-to-end protein structure prediction enables high-throughput exploration of uncharacterised proteins. Proceedings of the National Academy of Sciences of USA.

Greener, J. G., Kandathil, S. M., Moffat, L., & Jones, D. T. (2021). A guide to machine learning for biologists. Nature Reviews Molecular Cell Biology. doi:10.1038/s41580-021-00407-0

Kryshtafovych, A., Moult, J., Billings, W. M., Della Corte, D., Fidelis, K., Kwon, S., . . . Zheng, W. (2021). Modeling SARS-CoV-2 proteins in the CASP-commons experiment. Proteins: Structure, Function and Bioinformatics. doi:10.1002/prot.26231

Kandathil, S., Greener, J., Lau, A., & Jones, D. (2020). Ultrafast end-to-end protein structure prediction enables high-throughput exploration of uncharacterised proteins. doi:10.1101/2020.11.27.401232

Greener, J. G., Kandathil, S. M., & Jones, D. T. (2019). Deep learning extends de novo protein modelling coverage of genomes using iteratively predicted structural constraints. Nature Communications, 10 (1), 3977. doi:10.1038/s41467-019-11994-0

Kandathil, S., Greener, J., & Jones, D. T. (2019). Prediction of inter-residue contacts with DeepMetaPSICOV in CASP13. Proteins. doi:10.1002/prot.25779

Kandathil, S., Greener, J., & Jones, D. (2019). Prediction of inter-residue contacts with DeepMetaPSICOV in CASP13. doi:10.1101/586800

Kandathil, S. M., Greener, J. G., & Jones, D. T. (2019). Recent Developments in Deep Learning Applied to Protein Structure Prediction. Proteins. doi:10.1002/prot.25824

Kandathil, S. M., Garza-Fabre, M., Handl, J., & Lovell, S. C. (2019). Reliable Generation of Native-Like Decoys Limits Predictive Ability in Fragment-Based Protein Structure Prediction. Biomolecules, 9 (10). doi:10.3390/biom9100612

Taylor, W. R., Kandathil, S., & Jones, D. T. (2019). Sequence covariation analysis in biological polymers. Handbook of Statistical Genomics (pp. 325-346). doi:10.1002/9781119487845.ch11