Advisory Board and Editors Statistics
Xing Li
Dr. Xing Li is an Assistant Professor and Associate Consultant in the Division of Biomedical Statistics and Informatics, Department of Health Science Research at Mayo Clinic - voted the best hospital by U.S. News & World Report. Dr. Li completed his PhD in Bioinformatics from The University of Michigan at Ann Arbor, Michigan, USA. Dr. Li also holds a Masters Degree in Biochemistry and Molecular Biology and Bachelors Degree in Microbiology. Dr. Li’s research interests focus on machine learning, bioinformatics, and statistical data mining in large scale data in biomedical research, such as next generation sequencing data (whole genome sequencing, RNA-seq, microarray data), in the file. He has published more than 20 peer-reviewed papers in reputable journals and book chapters in the fields of Bioinformatics and Biostatistics, cancer research, cardiovascular disease, embryonic stem cell (ESC) and induced pluripotent stem cell (iPSC) research, and human genomics, genetics and development, and Microbiology. Dr. Li’s publications have been highlighted as Journal Cover Stories, Journal Featured Articles, Highlights Section Papers, Must Read by Faculty 1000, and ESC & iPSC News, etc. Dr. Li has been developing data analysis tools, such as RCircle and PCA3d, etc. Dr. Li is also a member of American Association for Cancer Research (AACR), International Society for Computational Biology (ISCB), American Statistics Association (ASA) and American Heart Association (AHA).
Gerton Lunter
My group is interested in investigating the processes of evolution and biology using computational methods. We apply machine learning methods (HMMs, Bayesian statistics, particle filters, deep learning) to large data sets to study for example human demographic history or non-coding functional elements in the genome.
Weiqi Luo
With a B.Sc. in Mathematics and Applied Mathematics from the University of Shantou, China (2003), a M.Sc. in Data Analysis, Network and Nonlinear Dynamical System from the University of York, UK (2004), and a Ph.D. in Statistics from the University of Leeds, UK (2008), Dr. Luo has gained extensive knowledge& experience in applied mathematics and statistics, computer simulations & forecasting, dynamic system and high-dimensional data analysis, to study disease dispersal and mitigation on a multinational scale. He has worked several years as biostatistician at The Food and Environmental Research Agency (UK) before beginning research in Florida (2011) as collaborated research scholar in NCSU and visiting scientist USDA. He played a key role in a wide range of multidisciplinary projects including, but not limited to, risk-based survey of HLB/ACP in FL, CA, TX and AZ, Plum Pox Virus (PPV) survey in NY and CA, Census travel modelling, agent-based disease simulation, GIS disease mapping and Aerial image processing.
Brendan P Malone
My research focus is in using quantitative methods to precisely understand how soils function and change- spatially, and through time.
I research methods for comprehensive digital soil mapping aiming to characterize soil both in the lateral and vertical dimensions.
I research methods for quantifying (and validating) measures of uncertainty for these comprehensive soil information systems.
I investigate innovative systems for soil measurement, which includes that associated with remote and proximal and soil sensing instrumentation. I have particular interest in infrared and x-ray spectroscopy.
Fernando Mata
Dr. Fernando Mata has an academic background in Agronomy and Animal Production at the Technical University of Lisbon, Portugal, where he also completed his postgraduate studies in Applied Maths. In addition, Dr. Mata completed his postgraduate studies in Pedagogy for Higher Education at The University of the West of England, UK. The skills gained while studying Maths and Animal Science led to him becoming an Animal Welfare Epidemiologist, the topic of his Doctorate in Veterinary Sciences at Anglia Ruskin University, Cambridge.
Professionally, he began his career as a dairy farmer and later moved into academia. He has lecturing experiences both in Portugal (Polytechnic Institute of Portalegre) and in the UK (University of the West of England, Newcastle University, Greenwich University and Wrexham Glyndwr University).
Currently, Dr. Mata is fully focused on research at the Centre for Research and Development in Agrifood Systems and Sustainability in the Polytechnic Institute of Viana do Castelo Portugal. Fernando has Fellowship of the Higher Education Academy, is a Registered animal Scientist with the British Society of Animal Science and is a Certified Biologist with the Royal Society of Biology. Apart from Animal Welfare Epidemiology, Fernando is interested in Animal Production, and Animal Performance in general.
David Meyre
David Meyre completed a PhD in quantitative plant genetics in France. Since 2001, he has been working on the elucidation of the genetic bases of obesity and type 2 diabetes. In 2004, he published the first family-based genome-wide scans for childhood and severe adult obesity. He completed the two first successful positional cloning efforts for childhood and severe adult obesity, which identified the positional candidate genes ENPP1 and PCSK1. In 2007, he contributed to the identification of the major susceptibility gene for polygenic obesity FTO. In 2009, he published the first genome-wide association study of extreme obesity in the French population and identified four novel susceptibility-loci. In 2010, he conducted the first genome-wide association meta-analysis for early-onset extreme obesity in German and French populations. In 2012, he identified the third more common form of monogenic obesity (PCSK1 partial deficiency) and demonstrated an important role of the lipid sensor GPR120 in human obesity. He also discovered the first molecular link between obesity and major depression. In 2013, he discovered a novel gene (SIM1) responsible for a syndromic Mendelian form of childhood obesity. In 2016, he discovered that physical activity can blunt the effect of the obesity predisposing gene FTO in diverse ethnic groups. He also demonstrated that genes can predict the outcomes of different types of bariatric surgery.
Dezső Módos
I am a medical doctor and a systems biologist. During my scientific carrier, I have tried to understand diseases and find novel approaches to treat them with drugs, whether it is cancer or UC. I finished the Semmelweis University Doctor of Medicine course on 2012 and then started my PhD in network biology. I was involved in developing multiple biological network databases transcription factor-target layers such as SignaLink, AutophagyRegulatory Network or the NRF2Ome. My main project was to understand signalling networks in cancer and how the different paralogues of a protein can act in the signalling network.
Since then I have been a Postdoctoral Research Associate at Cambridge University, where my main focus was how can we use networks to predict mechanisms of action of compound combinations. I used various chemical informatics techniques besides network biology such as chemical fingerprints, machine learning and gene expression-based toxicity prediction.
Currently, I am working at the Earlham Institute and Quadram Institut in Norwich researching inflammatory bowel disease and using network biology to decipher the pathogenesis of complex disorders.
I have recently moved to Imperial College, London to go through the therapeutic celling in IBD using systems biology.
Tuan V. Nguyen
Dr. Nguyen is Distinguished Professor of Predictive Medicine at the School of Biomedical Engineering, University of Technology Sydney (Australia). He also holds joint appointments as Professor, St Vincent's Clinical School, University of New South Wales (UNSW Sydney); and adjunct Professor of Epidemiology and Biostatistics at the School of Medicine, University of Notre Dame Australia.
Corey Nislow
Corey Nislow's laboratory develops and uses cutting edge tools to address this central question: how can we understand the biological commonalities in all of the life sciences; from embryonic development, to the spread of infectious diseases to better ways to treat cancer. Each of these disciplines can be explained in the context of competition, interaction and evolution. His lab studies the interface between genes and the environment using parallel genome-wide screens, high throughput cell-based assays and next generation sequencing. Most recently, he and his scientific partner, Dr. Guri Giaever, are exploring how laboratory experiments can co-opt evolutionary processes to understand drug action. He enjoys teaching all aspects of biotechnology, genomics and drug discovery. He got his PhD from the University of Colorado, worked at several Biotechnology companies and was at Stanford and University of Toronto before joining UBC in 2013. He has published 161 papers and run 19 marathons.
Joram M Posma
Lecturer in Cancer Informatics at Imperial College London and Fellow at Health Data Research (HDR) UK. Fellow of the Higher Education Academy (FHEA) and Member of the Royal Society of Chemistry (MRSC).
Zhaohui S. Qin
Dr. Qin is currently an Associate Professor in the Department of Biostatistics and Bioinformatics at Rollins School of Public Health, Emory University. He is also a faculty member at the Department of Biomedical Informatics, Emory University School of Medicine. Dr. Qin received his B.S. degree in Probability and Statistics from Peking University in 1994 and Ph.D. degree in Statistics from University of Michigan in 2000. He was a postdoctoral fellow in Dr. Jun Liu’s group in Department of Statistics at Harvard University from 2000 to 2003. He joined the Department of Biostatistics at University of Michigan in 2003. In 2010, he moved to his current position in Emory University. Dr. Qin has more than 15 years of experience in statistical modeling and statistical computing with applications in statistical genetics and genomics. Recently, his research is focused on developing Bayesian model-based methods to analyze data generated from applications of next generation sequencing technologies such as ChIP-seq, RNA-seq and resequencing. Dr. Qin also actively collaborates with biomedical scientists and clinicians on various projects that utilizing next generation sequencing technologies to study cancer genomics. Dr. Qin has published more than 100 peer-reviewed research papers covering statistics, bioinformatics, statistical genetics and computational biology. He has supervised more than 10 graduate students and postdoctoral fellows.
Mark A Robinson
Mark’s research interests are related to musculoskeletal loading, injury and impairment in the lower limbs. Of particular interest are lower limb injuries, monitoring of training loads, gait and biomechanical data analysis. He has published >70 journal articles in these areas and has >90 verified reviews. He hosted the 2022 conference of the International Society of Biomechanics in Sports in Liverpool.