People

Principal Investigator

Professor Michael Inouye    email (cambridge) | email (baker) | twitter @minouye271  |   @mikeinouye.bsky.social

Biography

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.

Disclosures

Trustee of the Public Health Genomics (PHG) Foundation. Scientific Advisory Board of Open Targets. Research collaborations with AstraZeneca, Nightingale Health, and Pfizer.

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 Malathi Dona    (Baker Institute)

Malathi received her PhD in Statistics at La Trobe University, Melbourne. During her PhD studies, she developed novel statistical methods to analyse large-scale omics data incorporating known biological pathways and network information to discover disease-associated genes. In 2019, Malathi joined the Cardiac Cellular Systems Lab at the Baker Heart and Diabetes Institute as a research fellow to apply her skills in cardio vascular research. Her research focused on the development of advanced bioinformatics pipelines tailored for the study of intercellular communication networks within complex tissues such as the heart, aorta, and liver to better understand cellular changes that contribute to the disease development. In 2024, Malathi transitioned to the Inouye Lab, taking on the role of a Domain Bioinformatician. In this capacity, she utilizes her proficiency in single-cell transcriptomics integrating with genomics to gain a deeper understanding of cardio vascular disease development.

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.

Laurent Gil   (Wellcome Sanger Institute / University of Cambridge)

Laurent studied Biology and Bioinformatics in Bordeaux (France) where he obtained a Masters degree in Bioinformatics. After few years working at the University of Bordeaux as Software developer, he moved to Cambridge (UK) to join the Ensembl Project (Variation team) at EMBL-EBI to work on many aspects of this project: data import, data storage, databases, web interface, tools, training. In addition he was working on the Locus Reference Genomic (LRG) Project. In 2019, he joined HDR-UK to work on the PGS Catalog Project as software developer and then started to work on OmicsPred in 2023.

Matt Gillman   (University of Cambridge)

Matt is our Green Algorithms Software Engineer Lead. Matt originally graduated with a BSc (Hons) in Physics with Astrophysics from the University of Leeds, but a few years later took a "conversion" MSc in Computer Science from the University of Hertfordshire. He also has an MSc in Advanced Computer Science (with Distinction) from the University of Essex. A lifelong learner, he has, additionally, a Graduate Certificate in Theology and a Postgraduate Certificate in Theology, both from the University of Chester by distance learning. He has spent most of his career in software development, and has worked in a wide range of employers: Nortel Networks (then a global telecomms firm), the UK Home Office, the Wellcome Sanger Institute, a number of London universities, an SME and even his own little company (now defunct). Over the years he has used C/C++, Perl, Python, Java, Matlab and Stata in various projects.

Dr William Ho   (Baker Institute)

William grew up immersed in the vibrancy of Hong Kong, where his passion for medical and agricultural biology took root. Pursuing this passion, he moved to Germany for his PhD and solidified his expertise in Molecular Biotechnology (BSc First Class Honours; MPhil distinction). There, he met with Prof. Detlef Weigel, an international pioneer in the plant-pan genomics researches, whom inspired him to develop strong interest in bioinformatics and genomics. After obtaining his PhD (magna cum laude) from the Max Planck Institute for Developmental Biology, William decided to begin his post-doctorate in Australia as a hybrid researcher between wet- and dry-lab. With over 20 years of experience in the field, William is proficient in next-generation sequencing and omics data analyses, contributing significant insights into functional, cellular and population genomics, epigenomics, and multi-omics integration in transcriptomics and metabolomics. William has honed his skills in various academic, commercial and institutional settings, including CSIRO, Metabolomics Australia, Melbourne Integrative Genomics, Walter and Eliza Hall Institute, and Peter MacCallum Cancer Center in Australia. Currently, William is making strides as a Domain Bioinformatician at the System Genomics Center of Inouye Lab in Melbourne. His current research interest is focused on epidemiology and precision medicine from the multi-omics perspectives.

Dr Xilin Jiang   (Group Leader, 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 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   (Senior Research Associate and Group Leader, 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 Pearl Liu   (University of Cambridge)

Pearl is currently a postdoctoral research associate at Inouye Lab, co-supervised by Dr Xilin Jiang. Pearl obtained a Bachelor’s degree in Applied Mathematics and Statistics at Johns Hopkins University, with a second major in Molecular and Cellular Biology, where she developed an interest in the intersection of statistics and biomedical sciences. She then obtained a PhD in Biostatistics at University of Washington, supervised by Professor Michael Wu, where she developed statistical methods for the association analyses of microbiome data using kernel-based and multivariate approaches. After completing her PhD studies, Pearl worked as a healthcare consultant at Analysis Group, gaining experiences in health economics and outcomes research (HEOR) using routine healthcare data. At Inouye Lab, Pearl is interested in leveraging omics and healthcare data to better understand the risk of health outcomes, e.g., through construction of risk prediction models. In addition, in collaboration with the NHS Genomic Laboratory Hub, Pearl will implement and validate the utility of polygenic risk scores in routine clinical settings.

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 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 Hasanga Manikpurage   (University of Cambridge)

Hasanga completed a bachelor's degree in Life Sciences (2014-2016) and a master's degree in Cell Biology, Physiology and Pathologies (2016-2018) at Université Paris Cité (previously known as Paris VII Diderot). With his training, Hasanga was predestined for a career as an experimental biologist. During his Masters in the laboratory of Dr Xavier Norel, he studied the involvement of prostaglandins in the regulation of vascular tone in human coronary arteries, particularly in the context of coronary artery disease. In 2018, Hasanga decided to leave France and move to Quebec (Canada) to start a PhD programme, this time using only in silico methodologies. He joined Dr. Sébastien Thériault's team and was co-directed by Dr. Benoit Arsenault. During his thesis, Hasanga focused mainly on the genetic determinants of coronary heart disease and various cardiovascular risk factors in order to develop polygenic risk scores. His thesis support the value of these genetic scores in quantifying the heritable risk of coronary artery disease, not necessarily captured by conventional clinical scores. The use of polygenic risk scores will enable identifying individuals at high genetic risk of complexe diseases. However, further efforts are needed to eventually use them clinically in the general population and to improve their predictive performances. By joining the Cambridge node of the Inouye Lab, Hasanga hopes to continue his efforts to address these challenges.

Tin Oreskovic   (University of Oxford / University of Cambridge)

Starting in late 2024, I will work on applying machine learning methods to multi-omic data from the Mexico City Prospective Study as part of HDR UK’s Molecules to Health Records driver programme, working as a member of the study’s team at Oxford’s Population Health Department and the Inouye Lab. I am currently completing my PhD at the University of Oxford. The aims of my PhD project were to assess the possible causal relations between body composition traits and a wide range of diseases and to identify potential novel drug targets for fat mass using proteomics data. My PhD is supported by Oxford Population Health and the Ad Futura Foundation. Before my PhD, I worked as a data scientist at IBM’s Chief Analytics Office in New York, as a researcher at an IBM Research group studying the opioid epidemic in the USA, and as a co-lead of a Data Science for Social Good project aiming to improve MMR Vaccination rates in Croatia. In addition to my PhD, I have contributed to other research projects, including, for instance, a project assessing the re-purposing potential of GLP1R agonists for alcohol use disorders using cis Mendelian randomization and a pragmatic non-inferiority trial of smoking cessation therapies. I received my MSc in data science from Columbia University and my BAs in economics and philosophy from Brown University. Before moving abroad for my undergraduate studies, I lived in Croatia.

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 and Group Leader, 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.

Siyuan Chen   (University of Cambridge)

Siyuan grew up in Shanghai, China, and completed his BSc in Biological Sciences at Fudan University in 2020, where he developed an interest in genomics and bioinformatics. After graduation, he joined the Computational Biology and Quantitative Genetics program at the Harvard School of Public Health. Siyuan completed his Master’s thesis in Prof. Isaac Kohane’s lab, focusing on genetic analysis among cancer exceptional responders. He reported that polygenic risk scores for autoimmune diseases are significantly different in cancer exceptional responders compared to typical cancer patients. He then worked as a computational biology research associate at the Shanghai AI Laboratory for around two years, gaining experience in several scRNA projects before becoming a PhD student at Inouye Lab. His current research aims to develop a methodological framework to link cellular characteristics from scRNA datasets to GWAS results.

Benedetta Felici   (University of Cambridge)

Benedetta grew up in Italy, where she completed her Bachelor's degree in Philosophy, International Studies, and Economics, with a Minor in Computer and Data Science at the University of Venice. During an exchange at the University College of Groningen, she developed a strong interest in applying statistics to real-world problems. For this reason, she then pursued a Master's degree in Statistical Sciences, curriculum in Health and Population Analytics, at the University of Bologna, with an exchange period at Ludwig Maximilian University in Munich. It was during this time that her passion for statistical genomics emerged; her Master's thesis explored the genetic bases of cardiovascular diseases, using linkage disequilibrium score regression and Mendelian randomization. Now a PhD candidate at Inouye Lab, her current research focuses on integrating multi-omics and imaging data through deep learning, to better understand the aetiology of cardiovascular diseases.

Zongtai (Michael) Wu   (University of Cambridge)

Michael grew up in Shanghai before moving to the UK during high school. He went on to earn a BA in Natural Sciences from the University of Cambridge, where he developed a foundation in interdisciplinary scientific research. Driven by a passion for computational biology, he completed an MPhil project at the Milner Institute in Cambridge, where he worked on applying machine learning and protein network analysis on metagenomic data to improve the diagnosis of ventilator-associated pneumonia and patient outcomes in critically ill children. Currently, Michael is a PhD candidate in Biomedical Data Science at Inouye Lab, funded by Health Data Research UK. His research focuses on identifying causal mediators between genetics and cardiometabolic diseases, and examining the causal relationships between molecular traits.

Millie Zhou   (University of Cambridge)

Millie grew up in California where she completed her undergraduate studies from University of California, Davis with a double major in psychology and sociology. During this time, she worked as a clinical research assistant and helped conduct psychological assessments of at-risk children who experienced maltreatment. This foundation sparked a broad intellectual curiosity that expanded into the implications of data and technology on health. Millie later pursued a master’s degree in software engineering at Harvard University, where her research utilised computational genomics to elucidate the genetic basis of neuropsychiatric disorders. After securing industry funding, she went to the University of Oxford for a master’s degree in medical statistics, where her research explored the causal relationship between amyotrophic lateral sclerosis and lung cancer using genetics and Mendelian randomisation. Millie is now working towards her PhD in biomedical data science at the Inouye Lab under the supervision of Mike Inouye and Angela Wood, funded by the Baker Heart and Diabetes Institute and HDRUK. Her research aims to leverage computational and statistical methods to elucidate the intricate relationships between genetics and diseases.

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.

Wenjun Chen  (University of Cambridge)

Wenjun Chen, originally from Shanghai, China, graduated with a Bachelor's degree in Applied Mathematics from Xi'an Jiaotong-Liverpool University. His research interests grew in the intersection of statistics, artificial intelligence, and biomedical science. Currently, he is pursuing an MPhil in Population Health Data Science at the University of Cambridge (supervised by Yang Liu), with his dissertation focusing on risk prediction of obesity-related traits and diseases.

Martin Hong  (University of Cambridge)