Dr Yuanwei Xu

Dr Yuanwei Xu

Institute of Cancer and Genomic Sciences
Research Fellow

Contact details

Address
Centre for Health Data Science
IOEM Building
Institute of Cancer and Genomic Sciences
University of Birmingham
Edgbaston
Birmingham
B15 2TT
UK

Dr Xu is a Research Fellow (Statistical Computing) in the Centre for Health Data Science, Institute of Cancer and Genomic Science. He is currently involved in the EU-funded Hypermarker (Hypermarker | personalised hypertension care) project, as a core contributor to data analytics and machine learning. The project aims to develop an AI-based clinical decision support tool to better predict anti-hypertensive drug response for individual patients. Dr Xu also contributed to the Smart Triage project (Smart Triage Data Box | NIHR SRMRC - Surgical Reconstruction and Microbiology Research Centre), as a Data Scientist, developing ML-based triage tools in major incident settings for risk stratification of trauma patients.

Qualifications

  • PhD in Scientific Computing, University of Warwick, 2016
  • MSc in Financial Mathematics and Computation, University of Leicester, 2011

Biography

After obtaining his Master’s degree in Financial Mathematics, Dr Yuanwei Xu decided to pursue research in computational science. His PhD was in Scientific Computing, working in the area of computational chemistry and biophysics. Specifically, he studied molecular simulation methods and was focused on developing novel Monte Carlo methods for  efficient conformational sampling in complex energy landscape, with application in lattice-protein aggregation.Later, Dr Xu joined as a Research Associate in the Centre for Mathematics of Precision Healthcare, Imperial College London, working on genomic-based transmission inference in molecular epidemiology. In particular, his research involved development and application of Bayesian methods for outbreak reconstruction from pathogen genomes and epidemiological data. He joined Birmingham in 2020 and has been involved in several research projects.

Postgraduate supervision

 MSc Health Data Science Student Projects

Research

Dr Xu’s primary research interest lies in computational systems biology and health data science, in particular, developing computational approaches and mathematical tools to understand complex systems in life science, uncover hidden patterns in biological data and networks, and ultimately identify disease biomarkers that lead to changes in strategy to improve human health.

He is particularly interested in statistical and computational approaches to multi-omics integration and developing machine learning approaches to better understand the intricate interplay between human microbiome and diseases.

Publications

Recent publications

Article

Wang, J, Zhang, J, Pu, L, Qi, W, Xu, Y, Wan, K, Zhu, Y, Gkoutos, GV, Han, Y & Chen, Y 2024, 'The Prognostic Value of Left Ventricular Entropy From T1 Mapping in Patients With Hypertrophic Cardiomyopathy', JACC: Asia. https://doi.org/10.1016/j.jacasi.2024.01.005

Xu, Y, Malik, N, Chernbumroong, S, Vassallo, J, Keene, D, Foster, M, Lord, J, Belli, A, Hodgetts, T, Bowley, D & Gkoutos, G 2023, 'Triage in major incidents: development and external validation of novel machine learning-derived primary and secondary triage tools', Emergency Medicine Journal. https://doi.org/10.1136/emermed-2022-212440

Xu, Y, Nash, K, Acharjee, A & Gkoutos, GV 2022, 'CACONET: a novel classification framework for microbial correlation networks', Bioinformatics, vol. 38, no. 6, btab879, pp. 1639-1647. https://doi.org/10.1093/bioinformatics/btab879

Wang, J, Li, Y, Yang, F, Bravo, L, Wan, K, Xu, Y, Cheng, W, Sun, J, Zhu, Y, Zhu, T, Gkoutos, GV, Han, Y & Chen, Y 2021, 'Fractal analysis: prognostic value of left ventricular trabecular complexity cardiovascular MRI in participants with hypertrophic cardiomyopathy', Radiology, vol. 298, no. 1, pp. 71-79. https://doi.org/10.1148/radiol.2020202261

Bisht, V, Nash, K, Xu, Y, Agarwal, P, Bosch, S, Gkoutos, GV & Acharjee, A 2021, 'Integration of the microbiome, metabolome and transcriptomics data identified novel metabolic pathway regulation in colorectal cancer', International Journal of Molecular Sciences, vol. 22, no. 11, 5763. https://doi.org/10.3390/ijms22115763

Malik, NS, Chernbumroong, S, Xu, Y, Vassallo, J, Lee, J, Moran, CG, Newton, T, Arul, GS, Lord, JM, Belli, A, Keene, D, Foster, M, Hodgetts, T, Bowley, DM & Gkoutos, GV 2021, 'Paediatric major incident triage: UK military tool offers best performance in predicting the need for time-critical major surgical and resuscitative intervention', EClinicalMedicine, vol. 40, 101100. https://doi.org/10.1016/j.eclinm.2021.101100

Malik, NS, Chernbumroong, S, Xu, Y, Vassallo, J, Lee, J, Bowley, DM, Hodgetts, T, Moran, CG, Lord, JM, Belli, A, Keene, D, Foster, M & Gkoutos, GV 2021, 'The BCD Triage Sieve outperforms all existing major incident triage tools: comparative analysis using the UK national trauma registry population', EClinicalMedicine, vol. 36, 100888. https://doi.org/10.1016/j.eclinm.2021.100888

Acharjee, A, Larkman, J, Xu, Y, Cardoso, VR & Gkoutos, GV 2020, 'A random forest based biomarker discovery and power analysis framework for diagnostics research', BMC Medical Genomics, vol. 13, no. 1, 178. https://doi.org/10.1186/s12920-020-00826-6

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