Publications (Computational Statistics and Machine Learning) Publications Bozhilova, L. et al. (2020) “COGENT: evaluating the consistency of gene co-expression networks”, Bioinformatics, 37(13), pp. 1928–1929. Cruz Rivera, S. et al. (2020) “Guidelines for clinical trial protocols for interventions involving artificial intelligence: the SPIRIT-AI extension”, Lancet Digital Health, 2(10), pp. e549 - e560. Liu, X. et al. (2020) “Reporting guidelines for clinical trial reports for interventions involving artificial intelligence: the CONSORT-AI extension”, Lancet Digital Health, 2(10), pp. e537 - e548. Elliott, A. et al. (2020) “Core-periphery structure in directed networks”, Proceedings of the Royal Society of London. Series A, Mathematical and Physical Sciences, 476(2241). Chan, A.-W. et al. (2020) “Reporting guidelines for clinical trial reports for interventions involving artificial intelligence: the CONSORT-AI extension”, Nature Medicine, 26(9), pp. 1364–1374. Fitzsimons, J. et al. (2020) “A note on blind contact tracing at scale with applications to the COVID-19 pandemic”, in. Association for Computing Machinery (ACM), pp. 1–6. Xu, J. et al. (2020) “MetaFun: meta-learning with iterative functional updates”, Proceedings of the 37th International Conference on Machine Learning, pp. 10617–10627. Baddock, H. et al. (2020) “Characterisation of the SARS-CoV-2 ExoN (nsp14ExoN-nsp10) complex: implications for its role in viral genome stability and inhibitor identification.” Baddock, H. et al. (2020) “Characterisation of the SARS-CoV-2 ExoN (nsp14ExoN-nsp10) complex: implications for its role in viral genome stability and inhibitor identification”, bioRxiv [Preprint]. Chan, L., Morris, G. and Hutchison, G. (2020) “Understanding Conformational Entropy in Small Molecules.” Pagination First page First Previous page ‹ … Page 39 Page 40 Page 41 Page 42 Page 43 Page 44 Page 45 Page 46 Page 47 … Next page › Last page Last