Publications
Within Research you can find these highlighted papers under different research themes.
At the end of this page, you can find the Full List of Publications of the research group.
Up-to-date citation information about these papers can be found on Google Scholar.
Group Highlights
MCbiclust is a novel method that can extract patterns from massive transcriptomics data collections. We show that it can effectively stratify patients based on their intrinsic gene expression signatures.
Bentham, Robert B., Kevin Bryson, and Gyorgy Szabadkai.
Nucleic Acids Research 45, no. 15 (6 September 2017): 8712–30.
This system took the abstract ideas of the GeneWeaver multi-agent system and deployed it for genome annotation at INRA in France. A system was developed that allowed different labs at INRA to collaboratively annotate related species of lactobacillus (lactis, debrukei and sakei). Each lab had control over its own annotation processes while the systems collaborated on sharing annotation when relevant.
Bryson, K., V. Loux, R. Bossy, P. Nicolas, S. Chaillou, M. van de Guchte, S. Penaud, et al.
Nucleic Acids Research 34, no. 12 (1 June 2006): 3533–45.
Seminal paper outlining the GeneWeaver multi-agent system (MAS) for cooperative genome annotation.
Bryson, K., M. Luck, M. Joy, and D. T. Jones.
Thousands of years ago, humans accidentally introduced Lactobacillus Bulgaricus to milk where it produced yogurt. This paper used the AGMIAL genome annotation system to reveal the novel finding that this bacteria has been rapidly evolving over these thousands of years to move from its original plant host to the richer environment of milk, for instance, loosing genes for cellulose processing amongst other functions.
Guchte, M. van de, S. Penaud, C. Grimaldi, V. Barbe, K. Bryson, P. Nicolas, C. Robert, et al.
Proceedings of the National Academy of Sciences 103, no. 24 (13 June 2006): 9274–79.
A large-scale genomic analsis, based on decision trees, using PrimerFinder was used to identify the most informative PCR primer pairs for identifying different serotypes of streptococcus pneumoniae. This was experimentally validated in the lab and provides a cheap and easy way to monitor the spread of different serotypes across Tanzania and other countries.
Leung, Marcus H., Kevin Bryson, Kathrin Freystatter, Bruno Pichon, Giles Edwards, Bambos M. Charalambous, and Stephen H. Gillespie.
Journal of Clinical Microbiology 50, no. 7 (21 December 2020): 2419–27.
This applies machine learning to epigenetic data from identical twins where one has major depressive disorder and the other does not. This identifies biological networks that potentially involved in the diseased mechanism.
Malki, K., E. Koritskaya, F. Harris, K. Bryson, M. Herbster, and M. G. Tosto.
Translational Psychiatry 6, no. 6 (June 2016): e839–e839.
Presented a number of novel algorithms for mass spectrometry instruments that showed a significant improvement over previous ones.
McBride, Ross, Joe Wandy, Stefan Weidt, Simon Rogers, Vinny Davies, Rónán Daly, and Kevin Bryson.
Bioinformatics 39, no. 7 (1 July 2023): btad406.
One of the most successful neural network architectures for predicting ab-initio secondary structure from protein sequences.
McGuffin, Liam J., Kevin Bryson, and David T. Jones.
Bioinformatics 16, no. 4 (1 April 2000): 404–5.
Human pedigree analysis is often used to identify regions of the genome that are invovled in rare diseases. The analysis of large human pedigrees is incredibly computational; particularly consanguineous ones which often results in rare recessive diseases showing themselves. In this paper we develop an parallel MCMC genetic linkage algorithm that uses multicore CPUs and GPUs, resulting in a magnitute improvement in speed over other popular methods at the time.
Medlar, Alan, Dorota Głowacka, Horia Stanescu, Kevin Bryson, and Robert Kleta.
Bioinformatics 29, no. 4 (15 February 2013): 413–19.
Application of our MCbiclust software to breast cancer samples and experimental validation using metabolomics.
Menegollo, Michela, Robert B. Bentham, Tiago Henriques, Seow Q. Ng, Ziyu Ren, Clarinde Esculier, Sia Agarwal, et al.
Cancer Research 84, no. 17 (4 September 2024): 2911–25.
A new probabilistic matching algorithm was developed which was used by the Anthony Nolan Trust for bone marrow transplant matching.
Patel, Z, Patel, ZI, Robinson, J, Robertson, DP, Stein, JE, Chenery, P, Latham, K, Evseeva, I, Bryson, K, and Marsh, SGE.
25th British Society for Histocompatibility and Immunogenetics Conference
This study looked at how gut bacteria can alter the affect of drugs and nutrients on a host organism. It used the worm host C. elegans and the gut bacteria E. coli for high-throughout multi-omics screening. Data analysis of this four-way screen combined with metabolic modelling showed that microbes integrate cues from metformin and the diet through the phosphotransferase signaling pathway that converges on the transcriptional regulator Crp.
Pryor, Rosina, Povilas Norvaisas, Georgios Marinos, Lena Best, Louise B. Thingholm, Leonor M. Quintaneiro, Wouter De Haes, Daniela Esser, Silvio Waschina, and Celia Lujan.
Cell 178, no. 6 (2019): 1299–1312.
A competition involving prediction Gene Ontology protein function prediction for protein sequences. The method of our research group at UCL was ranked first in the competition.
Radivojac, Predrag, Wyatt T. Clark, Tal Ronnen Oron, Alexandra M. Schnoes, Tobias Wittkop, Artem Sokolov, Kiley Graim, et al.
Nature Methods 10, no. 3 (March 2013): 221–27.
Fluoropyrimidines are the first-line treatment for colorectal cancer, but their efficacy is highly variable between patients. We queried whether gut microbes, a known source of inter-individual variability, impacted drug efficacy. Integrating multi-omics data for our host/microbe system, our findings highlight the potential therapeutic power of manipulating intestinal microbiota to ensure host metabolic health and treat disease.
Scott, Timothy A., Leonor M. Quintaneiro, Povilas Norvaisas, Prudence P. Lui, Matthew P. Wilson, Kit-Yi Leung, Lucia Herrera-Dominguez, Sonia Sudiwala, Alberto Pessia, and Peter T. Clayton.
Cell 169, no. 3 (2017): 442–56.
We introduce the first deep learning GAN method with word embeddings to simulate gene expression data for a wide range of biological systems from bacteria to different types of cancer tissue. We demonstrate that the method generates realistic cancer gene expression data.
Viñas, Ramon, Helena Andrés-Terré, Pietro Liò, and Kevin Bryson.
Bioinformatics 38, no. 3 (12 January 2022): 730–37.
A significant finding of this paper is the application of the ViMMS ‘digital twin’ to do optimization of mass spectrometry instruments that would be expensive, difficult or impossible to do on real instruments.
Wandy, Joe, Ross McBride, Simon Rogers, Nikolaos Terzis, Stefan Weidt, Justin J. J. van der Hooft, Kevin Bryson, Rónán Daly, and Vinny Davies.
Frontiers in Molecular Biosciences 10 (7 March 2023).
This paper looked at the effectiveness of AI models at diagnosing Covid-19 from Electronic Health Records of patients in real time at the height of the Covid pandemic. Our model was ranked 3rd out of 90 teams.
Yan, Yao, Thomas Schaffter, Timothy Bergquist, Thomas Yu, Justin Prosser, Zafer Aydin, Amhar Jabeer, et al.
JAMA Network Open 4, no. 10 (11 October 2021): e2124946.
Full List of Publications
Bentham, Robert B., Kevin Bryson, and Gyorgy Szabadkai. ‘Biclustering Analysis of Co-Regulation Patterns in Nuclear-Encoded Mitochondrial Genes and Metabolic Pathways’. In Cancer Metabolism, edited by Majda Haznadar, 1928:469–78. Methods in Molecular Biology. New York, NY: Springer New York, 2019. https://doi.org/10.1007/978-1-4939-9027-6_24.
Bentham, Robert B., Kevin Bryson, and Gyorgy Szabadkai. ‘MCbiclust: A Novel Algorithm to Discover Large-Scale Functionally Related Gene Sets from Massive Transcriptomics Data Collections’. Nucleic Acids Research 45, no. 15 (6 September 2017): 8712–30. https://doi.org/10.1093/nar/gkx590.
Bryson, K., V. Loux, R. Bossy, P. Nicolas, S. Chaillou, M. van de Guchte, S. Penaud, et al. ‘AGMIAL: Implementing an Annotation Strategy for Prokaryote Genomes as a Distributed System’. Nucleic Acids Research 34, no. 12 (1 June 2006): 3533–45. https://doi.org/10.1093/nar/gkl471.
Bryson, K., M. Luck, M. Joy, and D. T. Jones. ‘Agent Interaction for Bioinformatics Data Management’. Applied Artificial Intelligence 15, no. 10 (1 November 2001): 917–47. https://doi.org/10.1080/088395101753242688.
Bryson, K., M. Luck, M. Joy, and D. T. Jones. ‘Applying Agents to Bioinformatics in GeneWeaver’. In Cooperative Information Agents IV - The Future of Information Agents in Cyberspace, edited by Matthias Klusch and Larry Kerschberg, 60–71. Berlin, Heidelberg: Springer, 2000. https://doi.org/10.1007/978-3-540-45012-2_7.
Bryson, K., Michael (Michael M. ) Luck, Mike Joy, and D. T. Jones. ‘GeneWeaver : A Novel Genome Annotation System Based on Software Agents’. Heidelberg, Germany, 1999. https://wrap.warwick.ac.uk/id/eprint/61074/.
Bryson, K., Michael (Michael M. ) Luck, Mike Joy, D. T. Jones, P. Nicolas, P. Bessieres, and J.-F. Gibrat. ‘From GeneWeaver to Agmial’. Bologna, Italy, 2002. https://wrap.warwick.ac.uk/id/eprint/61211/.
Bryson, Kevin, Domenico Cozzetto, and David T. Jones. ‘Computer-Assisted Protein Domain Boundary Prediction Using the Dom-Pred Server’. Current Protein and Peptide Science 8, no. 2 (1 April 2007): 181–88. https://doi.org/10.2174/138920307780363415.
Bryson, Kevin, and Robert J. Greenall. ‘Molecular Dynamics of Putrescine’. Journal of the Chemical Society, Faraday Transactions 92, no. 6 (1 January 1996): 913–19. https://doi.org/10.1039/FT9969200913.
Bryson, Kevin, Liam J. McGuffin, Russell L. Marsden, Jonathan J. Ward, Jaspreet S. Sodhi, and David T. Jones. ‘Protein Structure Prediction Servers at University College London’. Nucleic Acids Research 33, no. suppl_2 (1 July 2005): W36–38. https://doi.org/10.1093/nar/gki410.
Bryson, K., and R. J. Greenall. ‘Binding Sites of the Polyamines Putrescine, Cadaverine, Spermidine and Spermine on A- and B-DNA Located by Simulated Annealing’. Journal of Biomolecular Structure and Dynamics 18, no. 3 (1 December 2000): 393–412. https://doi.org/10.1080/07391102.2000.10506676.
Buchan, D. W. A., S. M. Ward, A. E. Lobley, T. C. O. Nugent, K. Bryson, and D. T. Jones. ‘Protein Annotation and Modelling Servers at University College London’. Nucleic Acids Research 38, no. suppl_2 (1 July 2010): W563–68. https://doi.org/10.1093/nar/gkq427.
Buchan, Daniel W. A., Federico Minneci, Tim C. O. Nugent, Kevin Bryson, and David T. Jones. ‘Scalable Web Services for the PSIPRED Protein Analysis Workbench’. Nucleic Acids Research 41, no. W1 (1 July 2013): W349–57. https://doi.org/10.1093/nar/gkt381.
Chai, B., F. M. Amary, D. Lindsay, R. Tirabosco, A. M. Flanagan, K. Bryson, and N. Pillay. ‘The Role of Deep Learning in the Classification of Tumours of Fat’. In JOURNAL OF PATHOLOGY, 249:S20–S20. WILEY 111 RIVER ST, HOBOKEN 07030-5774, NJ USA, 2019. https://scholar.google.com/scholar?cluster=3208396695874038079&hl=en&oi=scholarr.
Cozzetto, Domenico, Daniel WA Buchan, Kevin Bryson, and David T. Jones. ‘Protein Function Prediction by Massive Integration of Evolutionary Analyses and Multiple Data Sources’. BMC Bioinformatics 14, no. 3 (28 February 2013): S1. https://doi.org/10.1186/1471-2105-14-S3-S1.
Edwards, Yvonne J. K., Kevin Bryson, and David T. Jones. ‘A Meta-Analysis of Microarray Gene Expression in Mouse Stem Cells: Redefining Stemness’. PLOS ONE 3, no. 7 (16 July 2008): e2712. https://doi.org/10.1371/journal.pone.0002712.
Elliman, S. J., K. Bryson, M. W. B. Trotter, S. Cellek, C. Kyriakou, K. L. Yong, C. Boshoff, and M. O. Clements. ‘Extending the Lineage Potential of Human Mesenchymal Stem Cells’. York, UK, 2006. https://westminsterresearch.westminster.ac.uk/item/92531/extending-the-lineage-potential-of-human-mesenchymal-stem-cells.
Ellul, Claire, Suneeta Gupta, Mordechai Muki Haklay, and Kevin Bryson. ‘A Platform for Location Based App Development for Citizen Science and Community Mapping’. In Progress in Location-Based Services, edited by Jukka M. Krisp, 71–90. Berlin, Heidelberg: Springer, 2013. https://doi.org/10.1007/978-3-642-34203-5_5.
Fischer, Daniel, Christian Barret, Kevin Bryson, Arne Elofsson, Adam Godzik, David Jones, Kevin J. Karplus, et al. ‘CAFASP-1: Critical Assessment of Fully Automated Structure Prediction Methods’. Proteins: Structure, Function, and Bioinformatics 37, no. S3 (1999): 209–17. https://doi.org/10.1002/(SICI)1097-0134(1999)37:3+<209::AID-PROT27>3.0.CO;2-Y.
Guchte, M. van de, S. Penaud, C. Grimaldi, V. Barbe, K. Bryson, P. Nicolas, C. Robert, et al. ‘The Complete Genome Sequence of Lactobacillus Bulgaricus Reveals Extensive and Ongoing Reductive Evolution’. Proceedings of the National Academy of Sciences 103, no. 24 (13 June 2006): 9274–79. https://doi.org/10.1073/pnas.0603024103.
Harris, Fraser, Karim Malki, Elena Koritskaya, Kevin Bryson, Mark Herbster, and Maria Grazia Tosto. ‘M24 - Epigenetic Differences In Monozygotic Twins Discordant For Major Depressive Disorder’. European Neuropsychopharmacology, Abstracts of the XXIV World Congress of Psychiatric Genetics (WCPG), 30 October - 4 November 2016, Jerusalem, Israel, 27 (1 January 2017): S382–83. https://doi.org/10.1016/j.euroneuro.2016.09.415.
Itan, Yuval, Kevin Bryson, and Mark G. Thomas. ‘Detecting Gene Duplications in the Human Lineage’. Annals of Human Genetics 74, no. 6 (2010): 555–65. https://doi.org/10.1111/j.1469-1809.2010.00609.x.
Jiang, Yuxiang, Tal Ronnen Oron, Wyatt T. Clark, Asma R. Bankapur, Daniel D’Andrea, Rosalba Lepore, Christopher S. Funk, et al. ‘An Expanded Evaluation of Protein Function Prediction Methods Shows an Improvement in Accuracy’. Genome Biology 17, no. 1 (December 2016): 184. https://doi.org/10.1186/s13059-016-1037-6.
Jones, D., J. Sodhi, S. Lise, L. McGuffin, and K. Bryson. ‘Prediction of Protein-Protein and Protein-Ligand Interactions from Protein Structures’. In FEBS JOURNAL, 272:397–98. Budapest, Hungary, 2005. https://febs.onlinelibrary.wiley.com/doi/10.1111/j.1742-4658.2005.4739_9.x.
Jones, D. T., K. Bryson, A. Coleman, L. J. McGuffin, M. I. Sadowski, J. S. Sodhi, and J. J. Ward. ‘Prediction of Novel and Analogous Folds Using Fragment Assembly and Fold Recognition’. Proteins: Structure, Function, and Bioinformatics 61, no. S7 (2005): 143–51. https://doi.org/10.1002/prot.20731.
Jones, David T., Michael Tress, Kevin Bryson, and Caroline Hadley. ‘Successful Recognition of Protein Folds Using Threading Methods Biased by Sequence Similarity and Predicted Secondary Structure’. Proteins: Structure, Function, and Bioinformatics 37, no. S3 (1999): 104–11. https://doi.org/10.1002/(SICI)1097-0134(1999)37:3+<104::AID-PROT14>3.0.CO;2-P.
Karr, Jonathan R., Alex H. Williams, Jeremy D. Zucker, Andreas Raue, Bernhard Steiert, Jens Timmer, Clemens Kreutz, et al. ‘Summary of the DREAM8 Parameter Estimation Challenge: Toward Parameter Identification for Whole-Cell Models’. PLOS Computational Biology 11, no. 5 (28 May 2015): e1004096. https://doi.org/10.1371/journal.pcbi.1004096.
Leung, Marcus H., Kevin Bryson, Kathrin Freystatter, Bruno Pichon, Giles Edwards, Bambos M. Charalambous, and Stephen H. Gillespie. ‘Sequetyping: Serotyping Streptococcus Pneumoniae by a Single PCR Sequencing Strategy’. Journal of Clinical Microbiology 50, no. 7 (21 December 2020): 2419–27. https://doi.org/10.1128/jcm.06384-11.
Malki, K., E. Koritskaya, F. Harris, K. Bryson, M. Herbster, and M. G. Tosto. ‘Epigenetic Differences in Monozygotic Twins Discordant for Major Depressive Disorder’. Translational Psychiatry 6, no. 6 (June 2016): e839–e839. https://doi.org/10.1038/tp.2016.101.
Malki, Karim, Maria Grazia Tosto, Héctor Mouriño‐Talín, Sabela Rodríguez‐Lorenzo, Oliver Pain, Irfan Jumhaboy, Tina Liu, et al. ‘Highly Polygenic Architecture of Antidepressant Treatment Response: Comparative Analysis of SSRI and NRI Treatment in an Animal Model of Depression’. American Journal of Medical Genetics Part B: Neuropsychiatric Genetics 174, no. 3 (April 2017): 235–50. https://doi.org/10.1002/ajmg.b.32494.
McBride, Ross, Joe Wandy, Stefan Weidt, Simon Rogers, Vinny Davies, Rónán Daly, and Kevin Bryson. ‘TopNEXt: Automatic DDA Exclusion Framework for Multi-Sample Mass Spectrometry Experiments’. Bioinformatics 39, no. 7 (1 July 2023): btad406. https://doi.org/10.1093/bioinformatics/btad406.
McGuffin, Liam J., Kevin Bryson, and David T. Jones. ‘The PSIPRED Protein Structure Prediction Server’. Bioinformatics 16, no. 4 (1 April 2000): 404–5. https://doi.org/10.1093/bioinformatics/16.4.404.
McGuffin, Liam J., Kevin Bryson, and David T. Jones. ‘What Are the Baselines for Protein Fold Recognition?’ Bioinformatics 17, no. 1 (1 January 2001): 63–72. https://doi.org/10.1093/bioinformatics/17.1.63.
McGuffin, Liam J., Richard T. Smith, Kevin Bryson, Søren-Aksel Sørensen, and David T. Jones. ‘High Throughput Profile-Profile Based Fold Recognition for the Entire Human Proteome’. BMC Bioinformatics 7, no. 1 (7 June 2006): 288. https://doi.org/10.1186/1471-2105-7-288.
McGuffin, Liam J., Stefano A. Street, Kevin Bryson, Søren‐Aksel Sørensen, and David T. Jones. ‘The Genomic Threading Database: A Comprehensive Resource for Structural Annotations of the Genomes from Key Organisms’. Nucleic Acids Research 32, no. suppl_1 (1 January 2004): D196–99. https://doi.org/10.1093/nar/gkh043.
Medlar, Alan, Dorota Głowacka, Horia Stanescu, Kevin Bryson, and Robert Kleta. ‘SwiftLink: Parallel MCMC Linkage Analysis Using Multicore CPU and GPU’. Bioinformatics 29, no. 4 (15 February 2013): 413–19. https://doi.org/10.1093/bioinformatics/bts704.
Menegollo, Michela, Robert B. Bentham, Tiago Henriques, Seow Q. Ng, Ziyu Ren, Clarinde Esculier, Sia Agarwal, et al. ‘Multistate Gene Cluster Switches Determine the Adaptive Mitochondrial and Metabolic Landscape of Breast Cancer’. Cancer Research 84, no. 17 (4 September 2024): 2911–25. https://doi.org/10.1158/0008-5472.CAN-23-3172.
Park, Gun Woo (Warren), and Kevin Bryson. ‘LDEncoder: Reference Deep Learning-Based Feature Detector for Transfer Learning in the Field of Epigenomics’. In Proceedings of the 12th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics, 1. BCB ’21. New York, NY, USA: Association for Computing Machinery, 2021. https://doi.org/10.1145/3459930.3469487.
Patel, Z, Patel, ZI, Robinson, J, Robertson, DP, Stein, JE, Chenery, P, Latham, K, Evseeva, I, Bryson, K, and Marsh, SGE. ‘GENIUS: A New HLA Match Prediction Tool from Anthony Nolan’. Accessed 15 September 2024. https://onlinelibrary.wiley.com/doi/10.1111/iji.12142.
Pryor, Rosina, Povilas Norvaisas, Georgios Marinos, Lena Best, Louise B. Thingholm, Leonor M. Quintaneiro, Wouter De Haes, Daniela Esser, Silvio Waschina, and Celia Lujan. ‘Host-Microbe-Drug-Nutrient Screen Identifies Bacterial Effectors of Metformin Therapy’. Cell 178, no. 6 (2019): 1299–1312.
Radivojac, Predrag, Wyatt T. Clark, Tal Ronnen Oron, Alexandra M. Schnoes, Tobias Wittkop, Artem Sokolov, Kiley Graim, et al. ‘A Large-Scale Evaluation of Computational Protein Function Prediction’. Nature Methods 10, no. 3 (March 2013): 221–27. https://doi.org/10.1038/nmeth.2340.
Scott, Timothy A., Leonor M. Quintaneiro, Povilas Norvaisas, Prudence P. Lui, Matthew P. Wilson, Kit-Yi Leung, Lucia Herrera-Dominguez, Sonia Sudiwala, Alberto Pessia, and Peter T. Clayton. ‘Host-Microbe Co-Metabolism Dictates Cancer Drug Efficacy in C. Elegans’. Cell 169, no. 3 (2017): 442–56.
Sodhi, Jaspreet Singh, Kevin Bryson, Liam J. McGuffin, Jonathan J. Ward, Lorenz Wernisch, and David T. Jones. ‘Predicting Metal-Binding Site Residues in Low-Resolution Structural Models’. Journal of Molecular Biology 342, no. 1 (3 September 2004): 307–20. https://doi.org/10.1016/j.jmb.2004.07.019.
Sodhi, Jaspreet Singh, L.J. McGuffin, K. Bryson, J.J. Ward, L. Wernisch, and D.T. Jones. ‘Automatic Prediction of Functional Site Regions in Low-Resolution Protein Structures’. In Proceedings. 2004 IEEE Computational Systems Bioinformatics Conference, 2004. CSB 2004., 702–3, 2004. https://doi.org/10.1109/CSB.2004.1332551.
Viñas, Ramon, Helena Andrés-Terré, Pietro Liò, and Kevin Bryson. ‘Adversarial Generation of Gene Expression Data’. Bioinformatics 38, no. 3 (12 January 2022): 730–37. https://doi.org/10.1093/bioinformatics/btab035.
Wandy, Joe, Ross McBride, Simon Rogers, Nikolaos Terzis, Stefan Weidt, Justin J. J. van der Hooft, Kevin Bryson, Rónán Daly, and Vinny Davies. ‘Simulated-to-Real Benchmarking of Acquisition Methods in Untargeted Metabolomics’. Frontiers in Molecular Biosciences 10 (7 March 2023). https://doi.org/10.3389/fmolb.2023.1130781.
Ward, Jonathan J., Liam J. McGuffin, Kevin Bryson, Bernard F. Buxton, and David T. Jones. ‘The DISOPRED Server for the Prediction of Protein Disorder’. Bioinformatics 20, no. 13 (1 September 2004): 2138–39. https://doi.org/10.1093/bioinformatics/bth195.
Xu, Ruoyan, William Jones, Ewa Wilcz‐Villega, Ana Sh Costa, Vinothini Rajeeve, Robert B Bentham, Kevin Bryson, et al. ‘The Breast Cancer Oncogene IKKε Coordinates Mitochondrial Function and Serine Metabolism’. EMBO Reports 21, no. 9 (3 September 2020): e48260. https://doi.org/10.15252/embr.201948260.
Yan, Yao, Thomas Schaffter, Timothy Bergquist, Thomas Yu, Justin Prosser, Zafer Aydin, Amhar Jabeer, et al. ‘A Continuously Benchmarked and Crowdsourced Challenge for Rapid Development and Evaluation of Models to Predict COVID-19 Diagnosis and Hospitalization’. JAMA Network Open 4, no. 10 (11 October 2021): e2124946. https://doi.org/10.1001/jamanetworkopen.2021.24946.
