Current roles2023 - Professor of Systems Genomics & Population Health, Dept of Public Health & Primary Care, University of Cambridge2023 - Director of Data Sciences (Clinical), Baker Heart & Diabetes Institute2022 - Theme Lead, Data Science and Population Health, NIHR Cambridge Biomedical Research Centre 2020 - Munz Chair of Cardiovascular Prediction & Prevention, Baker Heart & Diabetes Institute2018 - Director, Cambridge Baker Systems Genomics Initiative
Previous2021 - 2023 Director of Research, Dept of Public Health & Primary Care, University of Cambridge2018 - 2021 Turing Fellow, The Alan Turing Institute2018 - 2021 Principal Researcher, Dept of Public Health & Primary Care, University of Cambridge2017 - 2019 Principal Research Fellow, Baker Heart & Diabetes Institute2014 - 2018 NHMRC RD Wright Fellow2014 - 2018 National Heart Foundation Future Leader Fellow2015 - 2017 Co-Founder / Deputy Director, Centre for Systems Genomics, University of Melbourne2012 - 2017 Senior Research Fellow - Principal Research Fellow (Associate Professor), University of Melbourne2010 - 2014 NHMRC Peter Doherty Fellow2010 - 2012 Postdoctoral Fellow, Walter and Eliza Hall Institute of Medical Research2005 - 2010 Researcher / Genome Analyst, Wellcome Trust Sanger Institute
Education2010 PhD Computational Genomics, Leiden University / Wellcome Trust Sanger Institute Mentors: Leena Peltonen & Gertjan van Ommen Thesis: Analysis & algorithms in human disease genomics2005 MSc Biochemistry & Molecular Biology, University of California Los Angeles2004 BSc Biochemistry, University of Washington2004 BSc Economics, University of Washington
Mike grew up in the Seattle area before beginning undergraduate study in 1999 at the University of Washington, where he graduated with BSc's in biochemistry and economics. As a 19 year-old, Mike began analyzing data from the draft Human Genome Project, spending several years doing research in gene finding and protein structure prediction. He continued studying protein structure as a graduate student at UCLA, but returned to genomics in 2005 when he moved to the Wellcome Trust Sanger Institute (Cambridge, UK). While at Sanger, Mike completed his PhD with Prof Leena Peltonen and Prof Gert-Jan van Ommen and was heavily involved in the analytics for the first wave of genome-wide association studies as well as large-scale studies integrating multi-omic data. After a postdoc at the Walter and Eliza Hall Institute (Melbourne, AU), he was recruited to the faculty at the University of Melbourne in 2012 where he built a research program in systems genomics with a focus on clinical and public health applications. In 2017, Mike was recruited to the Baker Institute and the University of Cambridge to set up a lab spanning Australia and the UK that focuses on core areas of systems genomics, including polygenic risk scores, integrated analysis of multi-omics data and development of analytic tools.
John-Luis Moretti (Administration Officer, Baker Institute)
After completing a Bachelor of Science at Monash University, John-Luis completed a Masters in Biomedical Science research with Geoff Head at the Baker Institute and Roger Evans at Monash University. Since then he has worked at Monash University as a teaching assistant and at the Baker Institute as a surgical assistant. He is currently at the Baker Institute working with the Laboratory Operations team and as an Administration Officer for the Systems Genomics, and Computational and Clinical Informatics labs.
Dr Chief Ben-Eghan (University of Cambridge)
Chief joined the Inouye lab as a post-doctoral research associate in statistical genetics. He received his MSc in Biotechnology from the University of Greenwich and worked with the H3Africa Chronic Kidney Disease research node (Ghana) investigating APOL1 nephropathy in continental African populations. He was a PhD student at the McGill University, Department of Human Genetics, under the supervision of Prof. Mark Lathrop and Prof. Audrey Grant. His doctoral work focused on analysing complex traits with a focus on enhancing GWAS discovery through diverse population inquiry in large multi-ethnic cohorts. While there, he worked on adapting the accountability for reasonableness framework in a genomic context, to help address the ethical and statistical challenges in designing more inclusive studies to promote equity in data use. He also worked on developing a multi-ancestry, multi-phenotype fine-mapping framework for the asthma chr17q12-21 locus. His current work focusses on developing polygenic risk scores for cardiometabolic diseases (and related traits) and testing their portability across diverse populations, aimed towards minimising health disparities in underrepresented populations.
Dr Emma Bonglack (University of Cambridge)
Emmanuela completed her PhD with Micah Luftig at Duke University, developing a novel targeted therapeutic strategy to treat lymphomas caused by EBV related viruses, which often have limited options for treatment in the clinic. As a Schmidt Science Fellow in Mike Inouye’s lab, she is crossing disciplines to integrate multi-omics and advanced statistical methods to study the role of iron-deficiency anemia in cardiometabolic diseases, in ancestrally diverse global populations. Emmanuela’s interest in global health developed during her PhD and as a result of her growing up in Cameroon, where the negative impacts of poor health infrastructure and limited resources could be seen all around. Given the growing burden of chronic diseases and the high prevalence of iron deficiency in LMICs like Cameroon, Emmanuela hopes her research will advance our understanding of the unique factors that drive chronic/cardiometabolic diseases in diverse but underrepresented regions/populations.
Dr Carles Foguet (University of Cambridge)
Carles received his bachelor's degree in Biochemistry from the University of Barcelona, where he developed an interest in Systems Biology. To pursue this interest, he enrolled in the Biohealth Computing Erasmus Mundus master program, enabling him to take courses in bioinformatics at the University of Turin and to develop new modelling tools at the Joseph Fourier University. Next, he pursued a Ph.D. in Biotechnology at the University of Barcelona. During his Ph.D., he developed new approaches to model metabolism at a genome-scale by integrating multiple layers of omics data and an algorithm to integrate transcriptomics with stable isotope-resolved metabolomics and contributed to the PhenoMeNal project. He joined the Cambridge node of the Inouye lab in April 2021, where he works on the analysis of genomic and multi-omic datasets across HDRUK.
Dr Xilin Jiang (University of Cambridge)
I am a statistical geneticist working on the genetic architecture of complex diseases and its implications in clinical practice. Specifically, my research focuses on constructing risk factors using many variables that each have a small effect on diseases. The variables include genotype data, proteomic data, gene expression data and hospitalisation data (EHR). I like to think of disease as a stochastic process and disease risk on the “liability” scale. In statistical terminology, my research involves Bayesian inference for high dimensional data, longitudinal analysis and causal inference. I got my DPhil in Genomic Medicine and Statistics from Oxford University, funded by a Rhodes Scholarship and a Wellcome Trust studentship. I delivered the scholar address (name for a student speech delivered at the scholarship graduating ceremony) for the Rhodes scholar class of 2017. At the beginning of Pandemic, I worked as a consultant to the Gates Foundation and China CDC. Before my DPhil I worked on neural imaging modelling, analysing both structure and functional MRI data. I received my BSc from Fudan University.
Dr Joanna Kaplanis (Wellcome Sanger Institute / University of Cambridge)
Joanna grew up in London before moving to the US in 2008 where she received her BA in Applied Mathematics and MSc in Biostatistics from Harvard University. During this time she was introduced to human genetics while working as a research assistant in Yaniv Erlich's lab where she analysed large social media generated family trees to understand the genetic architecture of longevity. Following this, she moved back to the UK in 2015 to undertake her PhD at the Wellcome Sanger Institute with Matt Hurles where she focussed on understanding the rates and patterns of germline mutation as well as their role in rare developmental disorders. In 2021 she started her post-doc jointly with Gosia Trynka and Mike Inouye where her project is focussed on integrating functional genomics data and polygenic scores to identify disease relevant cell types.
Dr Martin Kelemen (University of Cambridge)
Martin received his BSc at University College London where he studied Human Genetics with a final year project focusing on genetic risk prediction and writing extensions for LDAK, supervised by the method's author Doug Speed. He then completed his PhD on the Mathematical Genomics and Medicine programme, supervised jointly by Carl Anderson at the Wellcome Trust Sanger Institute and by Chris Wallace at the University of Cambridge. Martin's PhD project was centred on finding evidence for epistasis using deep learning methods and improving the accuracy of polygenic risk scores by exploiting shared genetic effects between related diseases. He joined the unit as a postdoc to lead a project on building a risk model for abdominal aortic aneurysm that integrates polygenic scores and conventional risk factors. His current research focuses on exploring the effect of the environment and genetic variation on the transferability of polygenic risk scores across ancestries, working jointly with Mike and Prof Adam Butterworth (Public Health and Primary Care). In his free time Martin enjoys life drawing and listening to trashy Italo disco hits from the 80's.
Dr Loïc Lannelongue (University of Cambridge)
Loïc is now a postdoctoral research associate in biomedical data science. Previously, he was as a PhD student in the MRC Doctoral Programme (Inouye Lab) at the University of Cambridge studying both green computing and protein-protein interaction networks. Before that, he was trained in Paris at Lycée Saint-Louis and ENSAE ParisTech where he earned a BSc and a french Diplôme d’ingénieur (MSc) studying mainly mathematics and statistics, but also a bit of theoretical physics and economics. Then he completed an MSc in Statistics and Machine Learning at the University of Oxford in 2018. His Master’s thesis focused on developing a Bayesian tree-based algorithm to predict the length of hospital stays for patients.
Dr Yang Liu (University of Cambridge)
Yang was born and raised in Shandong, China and moved to the U.S. during high school. She received her Bachelors of Science in Biomedical Engineering with a concentration on electronic & computer engineering from Georgia Institute of Technology, Atlanta, USA. Then she completed her Master of Bioinformatics at the University of Queensland, Brisbane, Australia, where she developed an interest in genomic risk prediction of complex human diseases. At Melbourne University, she studied for her PhD in the Inouye Lab using machine learning for prediction and classification of diseases based on genotype and phenotype data. She has continued her studies as a postdoc in the lab at the Cambridge node.
Dr Douglas Loesch (AstraZeneca / University of Cambridge)
Doug grew up near Philadelphia in the US. He worked as an educator for 8 years with a focus on students with special needs. He then pursued a research career at the University of Maryland (Baltimore), earning a PhD in human genetics and epidemiology under the guidance of Prof Timothy O’Connor. His research has primarily focused on Parkinson disease in South America and has participated in several collaborative initiatives that sought to improve diversity in genomics research. He is now a postdoctoral fellow at the Centre for Genomics Research at AstraZeneca and a visiting research at the Cambridge University. His interests include exploring how genomics can inform clinical care and what we can do to address issues pertaining to equity in biomedical research, especially with regards statistical genetics.
Dr Guillaume Méric (Group Leader, Baker Institute)
Read more about me here. My research interests are broad and revolve around the ecology and evolution of environmental and pathogenic bacteria in relation to their human or animal hosts. I study different levels of these host-pathogen/host-bacterial interactions, mainly with a microbial population biology angle: how the ecology and environment can impact on bacterial and microbial population evolution, how pathogens emerge from background asymptomatic carried populations, and how microbes jump and transmit between various hosts. For example, I try to understand the impact of host factors (ecology, physiology or immunity) on the evolution and adaptation of the bacterial species they carry. In the Inouye Lab, I'm working on pathogen and antimicrobial resistance gene detection from shotgun metagenomics data and how these relate to host phenotypes (human genetics, metabolomics, incident disease etc). I collaborate closely with Kathryn Holt's lab at the Bio21 Institute.
Dr Myo Naung (Baker Institute)
Myo Naung has recently finished PhD training from The Walter Eliza Hall of Medical Institute (WEHI), Australia. His PhD research focused on understanding immune escape polymorphisms in Plasmodium falciparum vaccine candidate antigens using both genomics and serological approaches from longitudinal children cohorts of Papua New Guinea. Myo's research interests revolve around understanding the ecology and evolution of infectious agents and their interaction with human or animal hosts. He has spent several years in the US and UK for his undergraduate and master's degrees. As a researcher, Myo has experience in both wet-lab and dry-lab research and has used a combination of these techniques to study infectious agents, including long-read nanopore sequencing, and multiplexed serological assays.
Dr Elodie Persyn (University of Cambridge)
Dr Elodie Persyn studied agricultural engineering in Rennes (France) and obtained a Masters degree in Cellular and Molecular Biology and in Applied Statistics. She did a PhD in Nantes (France) with Richard Redon, Christian Dina and Lise Bellanger on rare variant association studies. She developed research interests in genetic epidemiology and population genetics with the comparison of statistical methods and the application to complex traits. After her PhD, she moved to the UK to join Cathryn Lewis’ team in King’s College London as a post-doctoral researcher. In collaboration with Hugh Markus from the University of Cambridge, she studied the genetics of brain imaging biomarkers of small vessel disease through the analysis of UK Biobank data. Currently, in the Inouye Lab, she is investigating the integration of multi-omics data from the INTERVAL study (https://www.intervalstudy.org.uk/).
Dr Scott Ritchie (Senior Research Associate, University of Cambridge)
Scott grew up in Melbourne before spending several years in the UK and US. He returned to Melbourne to begin undergraduate study at the University of Melbourne in 2008 graduating with a Bachelor in Computer Science in 2010. During his undergraduate he became interested in machine learning and data analysis, and was introduced to Bioinformatics in his final year. This led him to continue with postgraduate study at the University of Melbourne in Bioinformatics, graduating with distinction with an MSc in 2012. During this time he joined the Inouye Lab where he was introduced to systems biology, exploring different methods for constructing gene co-expression networks. In 2017, he completed his PhD also in the Inouye Lab. His current research interests include network analysis, gene expression data, and data visualisation.
Dr Woei Yuh Saw (Baker Institute)
Woei Yuh completed her PhD at the National University of Singapore (NUS) in Jan 2019. As part of her PhD, she focused on mapping the degree of natural variation amongst Asian populations, using different biological molecular states which include genomics (for instance, whole genome SNPs data, pharmacogenomics variants, and HLA typing alleles), transcriptomics, and lipidomics. During her PhD, she also worked at the NUS StatGen (Statistical Genetics) Laboratory. She is now a Research Officer in the System Genomics laboratory at Baker Heart and Diabetes Institute. Her main research interest is looking at multi-omics integration together with clinical, diet and environmental data, which she hopes to be able to derive biological insights from the multi-omics and infer links with diseases.
Dr Manika Singh (Baker Institute)
Manika received her B.Sc. degree in Genetics, Biochemistry, and Zoology from Bangalore University and her M.Sc. degree in Bioinformatics from Sikkim Manipal University, India. She received a Bioinformatics National Certification (BINC) fellowship from the department of Biotechnology (DBT), India, and joined as a junior research fellow at the Institute of Bioinformatics, Bangalore. During this time, she learned the analysis of next-generation sequencing datasets and worked on various genomics and proteomics projects. Next, she received a CSIRO data61 scholarship to pursue a Ph.D. at the Queensland University of Technology, Brisbane. During her Ph.D., she developed a novel pipeline for isoform-level multi-omics integration in a mouse model of behaviour. In 2022, she joined the Inouye lab to work on the analysis of genomics and muti-omics datasets.
Dr Ruidong Xiang (Baker Institute)
Ruidong has broad research interests related to statistical genomics. He has worked with genomic and phenotypic data from plants, animals and humans. He uses functional and evolutionary information to improve genome-wide mapping and prediction of complex traits. He has extensive experience in analysing pleiotropy (variants affecting >1 traits) and molecular phenotypes such as mapping gene expression eQTL, RNA splicing sQTL and metabolomic mQTL. His past work includes the development of the Functional-And-Evolutionary Trait Heritability (FAETH) score to rank genome-wide sequence variants and using Bayesian genome-wide fine-mapping to select core markers to customise a biology-informed SNP chip. More recently, he has developed new methods/analysis framework to link omics data and complex traits (scholar page). At the Inouye Lab, he will develop and/or apply advanced statistical methods to understand the link between multi-omics and human diseases.
Dr Yu Xu (Senior Research Associate, University of Cambridge)
Yu received his Ph.D. degree in Intelligence Systems at Trinity College Dublin, where he continued working as a research fellow till late 2018. Yu’s Ph.D. research tackled the problem of user expertise inference on social media which aimed to predict the online user’s expertise information via exploiting machine learning techniques, with a focus on the application of probabilistic graph models and multi-task learning algorithms. Prior to that, Yu earned his M.S. degree in Computer Science at Hunan University of Science and Technology, China in 2013. His M.S. research developed novel collaborative filtering and optimal path search algorithms to address the Web service recommendation problem. As a post-doctoral researcher in Inouye Lab, Yu is exploring machine learning and deep learning techniques to address genomic prediction problems including genotype/phenotype imputations, polygenic risk score predictions on human diseases, etc.
Claire Coffey (University of Cambridge)
Claire grew up in Birmingham, UK, and completed her BSc in Computer Science at the University of Birmingham. As part of this degree, she also studied at the University of British Columbia and the University of Waterloo. Wanting to apply her interest in artificial intelligence to real-world problems, Claire worked as an AI research and development consultant at a start-up where she was an inventor on 2 patents. She then completed her MPhil in Advanced Computer Science at the University of Cambridge, for which she was awarded the DeepMind Cambridge Scholarship, and her research focused on analysing the fairness of machine learning algorithms (supervised by Neil Lawrence). Claire is now working on her PhD in Health Data Science at Inouye Lab, with a studentship from Health Data Research UK, The Alan Turing Institute, and the Wellcome Trust. Her PhD research focuses on investigating, quantifying, and improving the fairness of medical risk prediction algorithms to ensure these are not discriminating against minority subgroups of society. She is supervised by Mike Inouye, Angela Wood, and Sam Lambert.
Alex Tokolyi (University of Cambridge / Wellcome Sanger Institute)
Alex grew up in Melbourne, Australia, completing undergraduate degrees at Monash University in Computer Science and Science (Microbiology and Molecular biology). During this he had the opportunity through a CSL-funded UROP internship to pursue bioinformatics research at the Australian Regenerative Medicine Institute, creating systems to explore spatial transcriptomic data. Alex then joined the lab of Kathryn Holt at the Bio21 Institute of the University of Melbourne for a year-long honours project on bacterial genomics, analysing how plasmids share genes between each other and different bacterial species. He then joined the Inouye lab to analyse the network interactions of genomic and environmental data from asthma patients, before beginning his PhD at the Sanger Institute in the University of Cambridge. Currently Alex is supervised by Emma Davenport and Mike Inouye, and looks at the variation in the human response to immune conditions such as sepsis, and the interaction of this with resident microbes.
Zhengyang Zhu (University of Cambridge)
Yang was born in China and moved to Singapore during secondary and high school. He completed his BSc in Biomedical Sciences and MSc in Epidemiology at Imperial College London. His Masters' project was to investigate renal safety profiles of HIV-1 patients after switching drug regimen in collaboration with Gilead Sciences Inc., which spurred his interest in data science in the context of infectious diseases. His current research focusses on the application of GWAS in infectious diseases, particularly infections with known comorbidities.
Peien Zhou (University of Cambridge)
Peien Zhou is a highly motivated individual with a Bachelor of Medicine in Public Health from Sun Yat-sen University and is currently pursuing a MPhil in Population Health Sciences with a focus on Health Data Science at University of Cambridge. In the Inouye Lab, he is co-supervised by Dr Yu Xu and working on development and application of genetic scores for proteomic data. He has gained experience in environmental epidemiology and chronic disease research as a research assistant at Sun Yat-sen University. Peien also has practical experience through internships and volunteering at various hospitals. He is committed to using advanced statistical and computer technologies to tackle medical problems.