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Our research group interests lie at the intersection of computational biology and human immunology, in particular in the applications of ‘omics, single cell and spatial technologies for the better understanding of tissue microenvironment, local tissue dynamics and cellular interactions, how they are established during development, and the molecular perturbations and tissue remodelling that occurs in disease states, in particular in autoimmune and autoinflammatory conditions. In order to address these types of questions, our group focuses on inter-disciplinary expertise in both biology and computational biology to both to extract relevant biological insights from complex datasets and to develop domain-tailored machine learning models and novel computational methods for high-dimensional sequencing data analysis.

About the Research

In recent years, the development of cutting-edge multi-modal single cell technologies have enabled diverse molecular read-outs of gene and protein expression, epigenetic states, T-cell and B-cell receptor sequences or even antigen specificity of thousands of individual cells at a time. These approaches generate vast amounts of high-dimensional sequencing data that require the application of advanced computational biology approaches and machine learning techniques. More recently, the emergence of spatial transcriptomics technologies has added further complexity to these datasets with the addition of spatial dimensionality and imaging data. While potentially incredibly powerful, due to the nascency of these experimental approaches, many challenges in computational data analysis are largely unaddressed and finding patterns in spatial gene expression remains one of the biggest challenges in single cell ‘omics today.

Understanding the mechanisms by which gene activity in individual cells guides complex cellular spatial arrangements in tissues has far-reaching implications in human biomedical research. Cellular organisation in tissues is ultimately linked to specific biological functions – cancer, infectious and inflammatory disease processes often lead to drastic spatial tissue remodelling and cellular re-arrangements. Indeed, histopathology is often used as a diagnostic tool precisely because many pathologies are characterised by perturbations in tissue cellular architecture.

Various research opportunities are currently available within the group, focusing on computational methods and model development in the area of spatial transcriptomics and integrative approaches with single cell multi-omics data.

In tissues, cells engage in complex cross-talk via secreted and cell surface molecules that coordinates their fate and behaviour from early developmental to mature tissue and pathological tissue remodelling in disease conditions. The emergence of single cell ‘omics technologies has contributed greatly to unravelling cellular interactions in a variety of biological contexts; however, extending these approaches to spatially resolved data remains challenging. This project will aim to first to reconstruct 3D tissue architecture using consecutive-cut spatial transcriptomics sections and focus on developing methodology to reconstruct 3D spatial cellular signalling networks and analyse network topology and patterns. This method will be applied to better characterise early paediatric human gut development and quantify spatial morphogen gradients that are established during this time, with a focus on immune cell colonisation of the colon.

Spatially resolved ‘omics often generates paired image data, which is often underutilized but can be used to extract high-resolution information. This project will focus on developing machine learning models for prediction of transcript-mics derived features from histology image data. This will enable quantifying spatial tissue niches across large numbers of tissue sections in order to assess structural, cellular and co-localisation changes, with the aim of applying this to in-house transcriptomics and image data of inflammatory bowel disease samples and generate insights into disease pathology.

These methods will be applied to better characterise the human immune system during development, maturation and pathological inflammation processes, working in collaboration with world-leading immunologists within the MRC Human Immunology Unit at the WIMM.

Training Opportunities

Our projects and work are mostly multidisciplinary, and usually lie at the intersection of data science (machine-learning and statical inference) and immunology and developmental biology and therefore motivated students from both computer science and biology backgrounds are encouraged to apply. Each project is supervised by a minimum of two supervisor (one from each discipline) to ensure proper training and supervision. Students will additionally have access to a wide variety of training and courses within Oxford University teaching and training schemes.

Students will be enrolled on the MRC Weatherall Institute of Molecular Medicine DPhil Course, which takes place in the autumn of their first year. Running over several days, this course helps students to develop basic research and presentation skills, as well as introducing them to a wide range of scientific techniques and principles, ensuring that students have the opportunity to build a broad-based understanding of differing research methodologies.

Generic skills training is offered through the Medical Sciences Division's Skills Training Programme. This programme offers a comprehensive range of courses covering many important areas of researcher development: knowledge and intellectual abilities, personal effectiveness, research governance and organisation, and engagement, influence, and impact. Students are actively encouraged to take advantage of the training opportunities available to them.

As well as the specific training detailed above, students will have access to a wide range of seminars and training opportunities through the many research institutes and centres based in Oxford.

The Department has a successful mentoring scheme, open to graduate students, which provides an additional possible channel for personal and professional development outside the regular supervisory framework. We hold an Athena SWAN Silver Award in recognition of our efforts to build a happy and rewarding environment where all staff and students are supported to achieve their full potential.



Fawkner-Corbett D, Antanaviciute A, Parikh K, Jagielowicz M, Geros AS, Gupta T, Ashley N, Khamis D, Fowler D, Morrissey E, Cunningham C, Johnson PRV, Koohy H, Simmons A. 2021. Spatiotemporal analysis of human intestinal development at single-cell resolution. Cell


Parikh K, Antanaviciute A, Fawkner-Corbett D, Jagielowicz M, Aulicino A, Lagerholm C, Davis S, Kinchen J, Chen HH, Alham NK, Ashley N, Johnson E, Hublitz P, Bao L, Lukomska J, Andev RS, Bjorklund E, Kessler BM, Fischer R, Goldin R, Koohy H, Simmons A. 2019. Colonic epithelial cell diversity in health and inflammatory bowel disease. Nature


Corridoni D, Antanaviciute A, Gupta T, Fawkner-Corbett D, Aulicino A, Jagielowicz M, Parikh K, Repapi E, Taylor S, Ishikawa D, Hatano R, Yamada T, Xin W, Slawinski H, Bowden R, Napolitani G, Brain O, Morimoto C, Koohy H, Simmons A. 2020. Single-cell atlas of colonic CD8(+) T cells in ulcerative colitis. Nat Med 26: 1480-90



Structural remodeling of the human colonic mesenchyme in inflammatory bowel disease

James Kinchen, Hannah H Chen, Kaushal Parikh, Agne Antanaviciute, Marta Jagielowicz, David Fawkner-Corbett, Neil Ashley, Laura Cubitt, Esther Mellado-Gomez, Moustafa Attar, Eshita Sharma, Quin Wills, Rory Bowden, Felix C Richter, David Ahern, Kamal D Puri, Jill Henault, Francois Gervais, Hashem Koohy, Alison Simmons, Cell