Programme directors

Professor Chris Ponting

Prof Chris Ponting is a Professor of Medical Bioinformatics at the University of Edinburgh, and the Director of Data Innovation at the Institute of Genetics and Cancer.

Prof Ponting leads the XDF Programme. He was trained first in particle physics before pursuing a successful career in biomedicine, so knows first-hand the skills necessary for Fellows to transition into “Big Data Biomedicine”. He was Chair of the MRC Bioinformatics Training Panel, Founding Director of the MRC CGAT Training Centre, and jointly led the ELIXIR European Training Platform. His research is in computational and experimental genomics, specifically on the molecular and genetic mechanisms of disease, and he has recruited individuals with diverse backgrounds, from physics and computer science, to biology and biochemistry, to his research group.

Chris Ponting Group website

Professor Davide Marenduzzo

Prof. Davide Marenduzzo is a Professor of Computational Biophysics at the University of Edinburgh, within the School of Physics and Astronomy.

He was first trained as a particle physicist, then did his PhD and post-doctoral training in biophysics and soft matter, so that he has followed a similar pathway to that of an XDF in his early career. His current research deals mainly with models for 3D chromosome organisation and for chromatin transcription, in close collaborations with experimentalists in biology and medicine. Among other things, he is well known for discovering together with his team the bridging-induced attraction, a biophysical mechanism leading to the spontaneous formation of clusters of proteins associated with transcription in living cells.

Dr Diego Oyarzún

Dr Diego Oyarzún is a Reader in Computational Biology at the University of Edinburgh. He holds a joint appointment at the School of Informatics and School of Biological Sciences.

Dr Oyarzún has a background in systems and control theory. His team develops computational methods for studying molecular systems in biomedicine and biotechnology. He has authored over 70 research papers in systems & synthetic biology, applied mathematics and control theory. He is member of the executive board of the UKRI Centre for Doctoral Training in Biomedical AI, co-Director of the Edinburgh Science for Sustainability Hub and has had roles with various international bodies (WEF, G20). He is an associate editor for journals in biotechnology and synthetic biology, and has participated in programme committees for several international conferences. Dr Oyarzún is Fellow of the Alan Turing Institute and the Royal Society of Biology.

Diego Oyarzún Group website

Diego Oyarzún Personal website

Dr Catalina Vallejos

Dr Catalina Vallejos is a Reader at the MRC Human Genetics Unit.

Dr Catalina Vallejos is a Bayesian statistician and leads the Biomedical Data Science research group at the MRC Human Genetics Unit within the University of Edinburgh. She is also a Fellow of The Alan Turing Institute. Her research group focuses on the development, implementation and application of Bayesian statistical methodology that is motivated by the multiple sources of heterogeneity that are typically encountered in complex biomedical data: from technical noise to population structure and different data modalities. Catalina’s research involves various types of complex biomedical data from single cell sequencing to electronic health records.

Catalina Vallejos Group website

Dr Duncan Sproul

Dr Duncan Sproul is a programme leader at the MRC Human Genetics Unit and Institute of Genetics and Cancer.

Duncan started as a geneticist who was frustrated by the fact he was not allowed to combine physics and biology for his undergraduate degree. Following his degree in Genetics at the University of Edinburgh, he was awarded an MRC pre-doctoral fellowship to undertake a PhD on the regulation of gene clusters with Professor Wendy Bickmore at the MRC Human Genetics Unit. During his postdoctoral training at the Edinburgh Breakthrough Breast Cancer Research Unit with Dr Andrew Sims, Duncan applied emerging epigenomic technologies to understand the role of epigenetic dysfunction in breast carcinogenesis. He joined the MRC Human Genetics Unit in 2013 as a research fellow and was awarded a Career Development Fellowship from CRUK in 2016. He is also an alumnus of the Scottish Crucible interdisciplinary training program.

Duncan Sproul Group website

Dr Robert Kitchen

Dr Robert Kitchen leads a global computational biology team at Novo Nordisk.

The department focuses on applying systems biology and machine learning to identify drug target candidates from high-throughput in-vitro functional screening and unveiling endotypes of cardiometabolic diseases.  Prior to joining Novo Nordisk’s research centre in Oxford, UK, Robert was a Principal Investigator in the cardiology research faculty at the Massachusetts General Hospital and Harvard Medical School, Boston, USA.  There, his laboratory specialised in applying machine learning methods to model neurological and cardiovascular disorders and has substantial experience in working with transcriptomics and with multi-omics data integration.  Prior to his academic appointment, he led biomarker development and companion-diagnostics programs at Exosome Diagnostics (now part of Bio-Techne). Robert holds a PhD from the University of Edinburgh, UK, and undertook his post-doctoral training in the Gerstein and Nairn labs at Yale University, USA, focussing on systems biology, functional genomics, and molecular psychiatry.

Dr Xiao Fu

Dr Xiao Fu is a Junior Group Leader at the CRUK Scotland Institute.

Dr Xiao Fu leads the Integrative Modelling Lab at the CRUK Scotland Institute. His research team focuses on developing computational approaches to investigate organisational principles of the tumour microenvironment and mechanisms of therapy resistance, in collaboration with research groups with expertise in pre-clinical in vivo experiments, advanced imaging, and patient data analysis. He studied biophysics during his PhD training and developed multi-scale agent-based models to study disease progression in liver toxicity and in diabetic retinopathy. During his Postdoctoral research, his work spanned agent-based models to study the evolutionary dynamics of tumours and spatial data analysis to study architectural features of the tumour microenvironment, in collaboration with cancer cell biologists, experimentalists, clinicians, and data scientists.

Dr Kristina Kirschner 

Dr Kristina is a Reader in the School of Cancer Sciences and the CRUK Beatson Institute, University of Glasgow, UK, with an interest in cancer heterogeneity and age-related changes in carcinogenesis. Her group investigates stem cell aging and senescence alongside age-associated clonal haemopoiesis on a functional, metabolic and multi-omics level. Dr Kristina has experience working in interdisciplinary teams and is interested in modelling stem cell dynamics.

Kristina obtained her Ph.D. from the University of Edinburgh, characterising one of the first DNA damage-dependent premature ageing mouse model. During her post-doc at the CRUK Cambridge Institute, she revealed previously unanticipated levels of complexity in p53’s response to stress, identifying specific transcriptional patterns in senescence. Seeking a more readily translatable disease model and appreciating the pioneering history of leukaemia studies for understanding cancer Kristina joined Prof. Anthony Green’s lab at the University of Cambridge. Ageing is the biggest single cause for cancer and she therefore combined her expertise in ageing and cancer leading the way in identifying JAK/STAT driven transcriptional clonal haemopoiesis by single cell RNA-seq.

Kristina Kirschner website

Professor Tim Aitman

Prof Aitman is a Professor of Molecular Pathology and Genetics at the University of Edinburgh. He is the Director of the Centre for Genomic and Experimental Medicine within the Institute of Genetics and Cancer, Clinical Director of the HiSeq X genome sequencing facility in Edinburgh Genomics and Consultant Physician in NHS Lothian.

Prof Aitman trained in both physiology/biochemistry and medicine. His research uses genome technology and information to elucidate the genetic basis of both common and rare human disorders and to relate genotype and epigenotype to phenotype. Increasingly, the challenge is to use large datasets - genetic, epigenetic, genomic and phenotypic - to diagnose and stratify human disease, and to use advances in these areas to move research findings towards routine healthcare. Clinical areas of interest include rare Mendelian disorders and cancer. Wet lab approaches include high-throughput sequencing and bespoke quantitative assays of somatic mutation and DNA methylation. In silico approaches include mining of large public and host-generated datasets, computational modelling of disease states and integration of multiple data modalities to understand and manage human disease.

Prof Aitman is a Fellow of the Royal Society of Edinburgh, the Royal College of Physicians, the Academy of Medical Sciences, and the Society of Biology. He is currently co-Director and Edinburgh PI of the Scottish Genomes Partnership, a nationally important collaboration with the NHS, and is also Director of the Edinburgh-St Andrews Consortium for Molecular Pathology, Informatics and Genome Sciences, one of only six MRC-EPSRC Molecular Pathology Nodes in the UK.

Tim Aitman Group website

Professor Guido Sanguinetti

Prof Guido Sanguinetti, Professor of Computational Bioinformatics at the University of Edinburgh.

Prof Sanguinetti obtained MSc in physics and DPhil in mathematics. His research group is part of the Institute of Adaptive and Neural Computation, within the School of Informatics. His general interests lie in the development of machine learning techniques to address challenges in scientific modelling. He has published over 80 publications in international journals and conferences including Science, Nature Methods, PNAS. He has supervised thirteen PhD students and served as external examiner in over 15 Universities in the UK, Germany, Italy, Sweden and Finland. He held an ERC Starting Grant 2012-17 and was the recipient of the 2012 PNAS Cozzarelli Award in Engineering and Applied Sciences, as well as several other best paper awards. He served as area chair for the International Conference on Machine Learning, the European Conference on Machine Learning, and is a steering committee member of the community of special interest on Machine Learning in Computational Systems Biology within the International Society for Computational Biology. He served on the Informatics Equality and Diversity Committee since its inception and formed part of the self-assessment team for the School's two successful Athena Swann Silver Award submissions.

Guido Sanguinetti Group website

Professor Jane Hillston

Prof Jane Hillston is a Professor of Quantitative Modelling at the University of Edinburgh, she is also the Director of Research and the Head of School in Informatics.

Prof Hillston gained a BA in Mathematics from the University of York, UK in 1985 and an MS in Mathematics from Lehigh University, USA in 1987.  After a short spell in industry, she studied for a PhD in Computer Science at the University of Edinburgh, which was awarded in 1994. She was appointed Professor of Quantitative Modelling in the School of Informatics at the University of Edinburgh in 2006, having joined the University as a Lecturer in Computer Science in 1995. 

Jane Hillston’s research is concerned with formal approaches to modelling dynamic behaviour, particularly for performance modelling and stochastic verification.  Her PhD dissertation was awarded the BCS/CPHC Distinguished Dissertation award in 1995 and she was the first recipient of the Roger Needham Award in 2005.  She held an EPSRC Advanced Research Fellowship 2001-2010. She has published over 100 journal and conference papers and held several Research Council and European Commission grants.  She is a fellow of the BCS and the Royal Society of Edinburgh.

Jane Hillston personal website

Professor Margaret Frame

Prof Margaret Frame (OBE) is a Professor of Cancer Research at the University of Edinburgh and the Director of the Institute of Genetics and Cancer.

Prof Frame has a background in biochemistry and molecular pathology. Her research focuses on protein networks biology and functions of cell-adhesion proteins in the context of cancer. A key feature of her lab’s work during the recent past has been to embrace inter-disciplinary team science that brings new innovative approaches to cancer biology questions. The overarching aims of her research are: (i) mapping cancer phenotypes on to cancer pathways, using mouse- and human patient-derived material as biological source; and (ii) to improve the predictivity of pre-clinical therapeutic testing. She has a special interest in inter-disciplinary doctoral and post-doctoral training, and the support and mentoring of all early- and mid-career researchers.

She serves (or served) on multiple decision-making bodies and in other advisory/management roles. Current and past examples include: President of the British Association for Cancer Research (BACR; from Jan 2016); AACR/CRUK – “Stand Up For Cancer“: panel 2014; European Research Council (ERC) Starter grants panel : sub-panel LS3; Chair: Academy of Medical Sciences, Genetics, Cellular and Developmental Biology, Microbiology and Immunology Panel; Royal Society of Edinburgh, Cell and Molecular Biology Panel;  Chair: Cancer Research UK (CR-UK), New Investigator Panel; Cancer Research UK, Training and Career Development Board; Cancer Research UK, Science Strategy Advisory Group; Cross UK-North America Cancer Imaging Alliance – joint initiative between CR-UK, NCI-USA and Canadian Institutes of Health Research’s Institute of Cancer Research (CIHR-ICR); Wellcome Trust, Genes, Molecules and Cells Panel; Advisory/Review Boards for several European Institutions: Oslo Centre for Biotechnology, University of Basel, Department of Biomedizine, Karolinska Institute Cancer Appointments Advisory Board, FP7 ‘Molecular Oncology Pathways’ Turin Advisory Board, Marseilles Institute of Biology, France, Bristol Myers Squibb, Europe and USA; membership in several University of Edinburgh (UoE)  committees (including: Institute of Genetics and Cancer (IGC) Executive, IGC Science Translational Strategy Group (Chair), CRUK Edinburgh Centre Governance Board, College of Medicine and Veterinary Medicine (CMVM) Strategy Group,  UoE: Research Planning Group).

Margaret Frame Group website

Professor Ian Tomlinson

Prof Tomlinson is Director of the Edinburgh Cancer Research Centre (including CRUK Edinburgh Centre), and Charles and Ethel Barr Chair of Cancer Research.

Prof Tomlinson was previously Director of the Institute of Cancer and Genomic Sciences at the University of Birmingham, having worked before that at the Cancer Research UK London Research Institute, University of Oxford and the Institute of Cancer Research. His research interests lie in discovering and functionally characterising cancer driver genes, especially germline variants that predispose to cancer. He also has a longstanding interest in cancer evolution, derived from his PhD project in population genetics, with a specific interest in the relative contributions of selection and mutation to cancer growth. Ian's work focuses on colorectal cancer, but extends to several other cancer types. He is especially keen to integrate work across a variety of biomedical areas, including human patient cohorts and clinics, animal models of disease and biomathematics.

Ian Tomlinson Group website

Dr Matthias Hennig

Matthias Hennig is a Reader in Computational Neuroscience at the School of Informatics, University of Edinburgh.

Dr Hennig studied Physics at Bochum University and then obtained a PhD in Computational Neuroscience at the University of Stirling in 2005. Following postdoctoral training through a MRC Training Fellowship and a MRC Career Development Award, he was appointed lecturer at Informatics in 2012. His research interest is focussed on development, stability and processing in neuronal circuits, using computational and mathematical modelling. To enable links between theory and experimental biology, his group also develops methods and open-source tools for analysis and interpretation of large scale neural recordings, and develops and advocates open science approaches. He currently serves as the director of the Institute for Adaptive and Neural Computation in Informatics.

Matthias Henning Group website