Integrative Modelling
Group Leader:
Dr Xiao Fu
Complex and dynamic interactions between cancer cells and elements of the tumour microenvironment shape tumour progression and contribute to therapy resistance. To unravel the biological complexity, and to uncover novel vulnerabilities to target, our lab focuses on developing diverse computational approaches, ranging from mechanistic modelling and computer simulations to spatial data analysis and machine learning. Our vision is that these approaches, in integration with clinical and pre-clinical experimental research, will increase our insights into the fundamental mechanisms underpinning tumour progression and therapy resistance and, ultimately, improve our strategies for stratification and treatment of patients. The Integrative Modelling lab was established in August 2023. We are delighted to have welcome team members to the lab in 2024 and 2025. In our lab, we are interested in developing computational approaches to investigate the co-evolutionary dynamics and organisational principles of the tumour and its microenvironment. Our goal is to reveal a tumour’s vulnerabilities through the lens of computational modelling and identify novel strategies to tackle therapy resistance. We collaborate broadly with cancer biologists, experimentalists, and clinicians, in an iterative manner, to ensure the biological relevance and translational value of our computational research.
Lab Reports
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Recent Publications
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Lab Members
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Recent Publications
2026
van den Berg NI, Elphick M, Mulder K, Bouricha O, Sadeghi-Alavijeh O, Fu X, Turajlic S. Immunometabolic gatekeeping: How tissue metabolism conditions tumor immunity. Cancer Cell. 2026(4):689-695.
2025
Lim KHJ, Tippu Z, Corrie PG, Hubank M, Larkin J, Lawley TD, Stares M, Stewart GD, Strange A, Symeonides SN, Szabados B, Turner NC, Waddell T, Zelenay S, Salto-Tellez M, Dive C, Turajlic S. MANIFEST: Multiomic Platform for Cancer Immunotherapy. Cancer Discov. 2025(5):878-883.
2023
Clarence T, Robert NSM, Sarigol F, Fu X, Bates PA, Simakov O. Robust 3D modeling reveals spatiosyntenic properties of animal genomes. iScience. 2023;26:106136.
Kato T, Jenkins RP, Derzsi S, Tozluoglu M, Rullan A, Hooper S, Chaleil RAG, Joyce H, Fu X, Thavaraj S, Bates PA, Sahai E. Interplay of adherens junctions and matrix proteolysis determines the invasive pattern and growth of squamous cell carcinoma. Elife. 2023;12.
Fu X, Sahai E, Wilkins A. Application of digital pathology-based advanced analytics of tumour microenvironment organisation to predict prognosis and therapeutic response. The Journal of Pathology. 2023.
2022
Schmidbaur H, Kawaguchi A, Clarence T, Fu X, Hoang OP, Zimmermann B, Ritschard EA, Weissenbacher A, Foster JS, Nyholm SV, Bates PA, Albertin CB, Tanaka E, Simakov O. Emergence of novel cephalopod gene regulation and expression through large-scale genome reorganization. Nat Commun. 2022;13:2172.
Fu X, Zhao Y, Lopez JI, Rowan A, Au L, Fendler A, Hazell S, Xu H, Horswell S, Shepherd STC, Spencer CE, Spain L, Byrne F, Stamp G, O’Brien T, Nicol D, Augustine M, Chandra A, Rudman S, Toncheva A, Furness AJS, Pickering L, Kumar S, Koh DM, Messiou C, Dafydd DA, Orton MR, Doran SJ, Larkin J, Swanton C, Sahai E, Litchfield K, Turajlic S, Bates PA. Spatial patterns of tumour growth impact clonal diversification in a computational model and the TRACERx Renal study. Nat Ecol Evol. 2022;6:88-102.
Fu X, Bates PA. Application of deep learning methods: From molecular modelling to patient classification. Exp Cell Res. 2022;418:113278.
2021
Zhao Y, Fu X, Lopez JI, Rowan A, Au L, Fendler A, Hazell S, Xu H, Horswell S, Shepherd STC, Spain L, Byrne F, Stamp G, O’Brien T, Nicol D, Augustine M, Chandra A, Rudman S, Toncheva A, Pickering L, Sahai E, Larkin J, Bates PA, Swanton C, Turajlic S, Litchfield K. Selection of metastasis competent subclones in the tumour interior. Nat Ecol Evol. 2021;5:1033-1045.
Muffoletto M, Qureshi A, Zeidan A, Muizniece L, Fu X, Zhao J, Roy A, Bates PA, Aslanidi O. Toward Patient-Specific Prediction of Ablation Strategies for Atrial Fibrillation Using Deep Learning. Front Physiol. 2021;12:674106.
Gerguri T, Fu X, Kakui Y, Khatri BS, Barrington C, Bates PA, Uhlmann F. Comparison of loop extrusion and diffusion capture as mitotic chromosome formation pathways in fission yeast. Nucleic Acids Res. 2021;49:1294-1312.
2020
Kakui Y, Barrington C, Barry DJ, Gerguri T, Fu X, Bates PA, Khatri BS, Uhlmann F. Fission yeast condensin contributes to interphase chromatin organization and prevents transcription-coupled DNA damage. Genome Biol. 2020;21:272.
Adhyapok P, Fu X, Sluka JP, Clendenon SG, Sluka VD, Wang Z, Dunn K, Klaunig JE, Glazier JA. A computational model of liver tissue damage and repair. PLoS One. 2020;15:e0243451.
2019
Muffoletto M, Fu X, Roy A, Varela M, Bates PA, Aslanidi OV. Development of a Deep Learning Method to Predict Optimal Ablation Patterns for Atrial Fibrillation. 2019 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB); 9-11 July 2019.
Clendenon SG, Fu X, Von Hoene RA, Clendenon JL, Sluka JP, Winfree S, Mang H, Martinez M, Filson AJ, Klaunig JE, Glazier JA, Dunn KW. A simple automated method for continuous fieldwise measurement of microvascular hemodynamics. Microvasc Res. 2019;123:7-13.
Clendenon SG, Fu X, Von Hoene RA, Clendenon JL, Sluka JP, Winfree S, Mang H, Martinez M, Filson A, Klaunig JE, Glazier JA, Dunn KW. Spatial Temporal Analysis of Fieldwise Flow in Microvasculature. J Vis Exp. 2019.
2018
Fu X, Sluka JP, Clendenon SG, Dunn KW, Wang Z, Klaunig JE, Glazier JA. Modeling of xenobiotic transport and metabolism in virtual hepatic lobule models. PLoS One. 2018;13:e0198060.
2016
Fu X, Gens JS, Glazier JA, Burns S, Gast TJ. An Explanatory Computational Simulation of Contiguous Capillary Occlusion in Diabetic Retinopathy based on Patient-derived Vasculature. The FASEB Journal. 2016;30:555.551.
Fu X, Sluka JP, Clendenon S, Glazier JA, Wang Z, Klaunig J, Ryan J, Dunn K. An in-Silico Model of Xenobiotic Distribution and Metabolism in a Simulated Mouse Hepatic Lobule. The FASEB Journal. 2016;30:1036.1038.
Sluka JP, Fu X, Swat M, Belmonte JM, Cosmanescu A, Clendenon SG, Wambaugh JF, Glazier JA. A Liver-Centric Multiscale Modeling Framework for Xenobiotics. PLoS One. 2016;11:e0162428.
Gast TJ, Fu X, Gens JS, Glazier JA. A Computational Model of Peripheral Photocoagulation for the Prevention of Progressive Diabetic Capillary Occlusion. J Diabetes Res. 2016;2016:2508381.
Fu X, Gens JS, Glazier JA, Burns SA, Gast TJ. Progression of Diabetic Capillary Occlusion: A Model. PLoS Comput Biol. 2016;12:e1004932.
Cross-Disciplinary Research Fellow
Luciana Luque
I am a cross-disciplinary research fellow (XDF), with a background in physics and computational modelling. Following my BSc/MSc in loop quantum gravity and DPhil in statistical mechanics, I did my postdocs in computational biology and biophysics. I became an XDF at the CRUK Scotland Institute, and I’m now working on immuno-oncology, with particular interest in immunotherapies, using techniques in the lab, bioinformatics, and computational modelling to understand the function and dysfunction of the immune system in cancer.
Postdoctoral Researcher
Naomi Van Der Berg
Hi I am Naomi – I am Dutch and the Mathematical Modeller for MANIFEST, which I joined in March 2025 co-supervised by Xiao Fu and Samra Turajlic. Before joining this role, I finished my PhD at the University of Cambridge, which was focused on mathematically capturing emergent interaction dynamics of the gut microbiome, so cancer is relatively new to me. During my studies, I was co-president of Cambridge University Students Against Pseudoscience; a student group dedicated to understanding and tackling the growing crisis of mis- and disinformation. I also was social secretary for my college (Darwin), organising formal dinner swaps with other colleges, recovering inter-collegiate connections after COVID. I am passionate about politics, the environment and public health (and advocate for flight-free conference attendance where possible). In my free time I like to dance, draw, socialise, write, hike with my partner, do amateur microscopy and engage in local political movements.
Postdoctoral Researcher
Xiaoyuan Liu
I joined the Fu lab as a postdoctoral research scientist in September 2024. In July 2024, I completed my PhD at the University of York, which focuses on the development of mechanistic mathematical models for eco-evolutionary problems, including the evolution of cell-fusion, evolution of sexual reproduction and the stability of macroecological systems.
For my postdoc, I will be applying mathematical and computational modelling techniques to uncover the mechanistic principles underpinning the diverse histological patterns that arise in colorectal liver metastases (CRLM), which can have significant clinical implications. Encapsulated growth in the liver characterised by a dense fibrous capsule coating the tumor invasive front is observed to have better prognosis than replacement growth whereby the capsule is absent.
Besides work, I enjoy hiking, nature and travelling.
Postdoctoral Researcher
Jayathilake Pahala Gedara
I am a postdoctoral researcher focused on developing mathematical models to simulate cancer progression and responses to therapeutic interventions. Originally from Sri Lanka, I have worked on various systems biology projects at research institutions in Singapore and the UK. My previous work includes mathematical modelling of muco-ciliary systems, bacterial populations, and tumour growth. Outside the lab, I enjoy listening to podcasts and exploring various hobbies.
PhD Student
Anh Nguyen Phuong
I’m a PhD student from Slovakia and Vietnam, joining the Integrative Modelling group in October 2024. My background in pharmacology and computational cancer research has led me to develop interest in leveraging spatial and omics data to untangle the complexities of cancer biology. Currently, I am focused on analysing spatial features of cellular graphs and integration of spatial transcriptomics to identify potential prognostic and predictive biomarkers of colorectal cancer. In my free time, I enjoy reading, playing video games, and hiking.
PhD Student
Diana Sirnikova
I am a Precision Medicine PhD student from Latvia who joined the team in September 2025. I completed my Bachelor’s degree in Pharmacology at the University of Huddersfield, where I first became involved in brain tumour research, and I have been working on related projects for the past four years in both academic and laboratory settings. For the next 4 years I will be focusing on using computational and mathematical modelling to better understand the role of microglia in glioblastoma and tumour progression. Outside of research, I enjoy playing rugby and tennis, or spending time reading.