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Nick Barton is a Professor of Evolutionary Genetics at the Institute of Science and Technology, Austria. Nick and his research group focus on the evolution of populations that are distributed through space, and that experience natural selection on many genes. Their research covers a wide range, including a long-term study of a flower colour hybrid zone in snapdragons (Antirrhinum), statistical analysis of the effects of selection on sequence variation, and theoretical work on speciation and quantitative genetics. Recent papers include analyses of “islands of divergence” in Antirrhinum, of a mouse selection experiment, and of the infinitesimal model for the inheritance of quantitative traits.
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Nick Barton is a Professor of Evolutionary Genetics at the Institute of Science and Technology, Austria. Nick and his research group focus on the evolution of populations that are distributed through space, and that experience natural selection on many genes. Their research covers a wide range, including a long-term study of a flower colour hybrid zone in snapdragons (Antirrhinum), statistical analysis of the effects of selection on sequence variation, and theoretical work on speciation and quantitative genetics. Recent papers include analyses of “islands of divergence” in Antirrhinum, of a mouse selection experiment, and of the infinitesimal model for the inheritance of quantitative traits.
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Ed Buckler is a USDA-ARS crop geneticist based at Cornell University campus.
Ed’s research focusses on developing genomic, statistical, and bioinformatic methods with applications in maize and other crops. Key questions are:
· How does genetic variation give rise to phenotypic variation?
· How can we use genetics to make agriculture more efficient and share those efficiencies globally?
· How can we reduce the impact of agriculture on the environment?
Ed’s tools and approaches have been applied to over 3000 other species – everything from human genetics, nearly every crop, and many species of ecological interest. Ed’s latest papers have been on machine learning of RNA expression and the relationship between eQTL and fitness.
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Ed Buckler is a USDA-ARS crop geneticist based at Cornell University campus.
Ed’s research focusses on developing genomic, statistical, and bioinformatic methods with applications in maize and other crops. Key questions are:
· How does genetic variation give rise to phenotypic variation?
· How can we use genetics to make agriculture more efficient and share those efficiencies globally?
· How can we reduce the impact of agriculture on the environment?
Ed’s tools and approaches have been applied to over 3000 other species – everything from human genetics, nearly every crop, and many species of ecological interest. Ed’s latest papers have been on machine learning of RNA expression and the relationship between eQTL and fitness.
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Anne Charmantier is an evolutionary ecologist interested in between-individual variation of life-history, morphological, and behavioural traits in natural populations. She holds a senior CNRS position (eq. Prof) in the Centre d’Ecologie Fonctionnelle et Evolutive (CNRS, UMR 5175, Montpellier, France). Her main research interests are focused on understanding the mechanisms involved in the evolution of adaptive traits, especially in a context of climate change and urbanisation. Since 2007 she has been managing a blue tit/great tit project dating back from 1976, which offers unique opportunity to study adaptation in heterogeneous and rapidly changing environments. In 2014, she published the OUP book ‘Quantitative Genetics in the Wild’ with Profs. Dany Garant and Loeske Kruuk.
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Anne Charmantier is an evolutionary ecologist interested in between-individual variation of life-history, morphological, and behavioural traits in natural populations. She holds a senior CNRS position (eq. Prof) in the Centre d’Ecologie Fonctionnelle et Evolutive (CNRS, UMR 5175, Montpellier, France). Her main research interests are focused on understanding the mechanisms involved in the evolution of adaptive traits, especially in a context of climate change and urbanisation. Since 2007 she has been managing a blue tit/great tit project dating back from 1976, which offers unique opportunity to study adaptation in heterogeneous and rapidly changing environments. In 2014, she published the OUP book ‘Quantitative Genetics in the Wild’ with Profs. Dany Garant and Loeske Kruuk.
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Over the past ten years, Dr. Susanne Dreisigacker has been leading the Wheat Molecular Breeding Laboratory at the International Wheat and Maize Improvement Center (CIMMYT) in Mexico. Dr. Dreisigacker’s main interest is to bring promising genomics tools into use in the CIMMYT Global Wheat Program. Her lab conducts genetics studies on key biotic (foliar diseases), abiotic (yield and yield stability) and quality factors that limit the production and value of wheat especially in the developing world. She provides the Global Wheat Program access to state-of-the-art molecular technologies and together with the CIMMYTs wheat breeders she applies marker-assisted selection strategies such as MAS, MABC and genomic selection targeting to accelerate genetic gains in bread and durum wheat. Dr. Dreisigacker’s research team collaborates with scientists around the world, including teams in India, China, Middle East, UK, USA, Germany, and South Africa. She trains and supervises students coming from local universities or internationally through CIMMYT’s intensive wheat training program.
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Over the past ten years, Dr. Susanne Dreisigacker has been leading the Wheat Molecular Breeding Laboratory at the International Wheat and Maize Improvement Center (CIMMYT) in Mexico. Dr. Dreisigacker’s main interest is to bring promising genomics tools into use in the CIMMYT Global Wheat Program. Her lab conducts genetics studies on key biotic (foliar diseases), abiotic (yield and yield stability) and quality factors that limit the production and value of wheat especially in the developing world. She provides the Global Wheat Program access to state-of-the-art molecular technologies and together with the CIMMYTs wheat breeders she applies marker-assisted selection strategies such as MAS, MABC and genomic selection targeting to accelerate genetic gains in bread and durum wheat. Dr. Dreisigacker’s research team collaborates with scientists around the world, including teams in India, China, Middle East, UK, USA, Germany, and South Africa. She trains and supervises students coming from local universities or internationally through CIMMYT’s intensive wheat training program.
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Dr. Yaniv Erlich is the Chief Science Officer of MyHeritage.com and an Associate Professor of Computer Science and Computational Biology at Columbia University (leave of absence). Prior to these positions, he was a Fellow at the Whitehead Institute, MIT. Dr. Erlich received his bachelor’s degree from Tel-Aviv University, Israel (2006) and a PhD from the Watson School of Biological Sciences at Cold Spring Harbor Laboratory (2010). Dr. Erlich’s research interests are computational human genetics. Dr. Erlich is a TEDMED speaker (2018), the recipient of DARPA’s Young Faculty Award (2017), the Burroughs Wellcome Career Award (2013), Harold M. Weintraub award (2010), the IEEE/ACM-CS HPC award (2008), and he was selected as one of 2010 Tomorrow’s PIs team of Genome Technology. He is currently working on statistical genetics at scale using direct to consumer genomics.
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Dr. Yaniv Erlich is the Chief Science Officer of MyHeritage.com and an Associate Professor of Computer Science and Computational Biology at Columbia University (leave of absence). Prior to these positions, he was a Fellow at the Whitehead Institute, MIT. Dr. Erlich received his bachelor’s degree from Tel-Aviv University, Israel (2006) and a PhD from the Watson School of Biological Sciences at Cold Spring Harbor Laboratory (2010). Dr. Erlich’s research interests are computational human genetics. Dr. Erlich is a TEDMED speaker (2018), the recipient of DARPA’s Young Faculty Award (2017), the Burroughs Wellcome Career Award (2013), Harold M. Weintraub award (2010), the IEEE/ACM-CS HPC award (2008), and he was selected as one of 2010 Tomorrow’s PIs team of Genome Technology. He is currently working on statistical genetics at scale using direct to consumer genomics.
Daniel is a Group Leader at the Wellcome Sanger Institute. The long-term goal of Daniel’s group is to understand the molecular and cellular consequences of genetic changes in gene regulatory regions. His research combines statistical genetics with high-throughput experimental techniques in human cells to address these questions. Much of the group’s recent research has been focussed on using human induced pluripotent stem cells (hIPSCs) and cells derived from hIPSCs as model systems to map and characterise human noncoding genetic changes.
Daniel is a Group Leader at the Wellcome Sanger Institute. The long-term goal of Daniel’s group is to understand the molecular and cellular consequences of genetic changes in gene regulatory regions. His research combines statistical genetics with high-throughput experimental techniques in human cells to address these questions. Much of the group’s recent research has been focussed on using human induced pluripotent stem cells (hIPSCs) and cells derived from hIPSCs as model systems to map and characterise human noncoding genetic changes.
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Lucia Galvão de Albuquerque is Professor of Animal Breeding and Genetics at the Department of Animal Science at São Paulo State University and a researcher of the National Council for Scientific and Technological Development (CNPq). She has experience in beef cattle breeding, working closely with the beef industry in Brazil. Lately, she has been leading research projects, based in complete DNA and RNA sequences, with the objective of developing technologies to increase biologic knowledge and to promote genetic improvement of quality, efficiency and sustainability of Nellore beef cattle production.
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Lucia Galvão de Albuquerque is Professor of Animal Breeding and Genetics at the Department of Animal Science at São Paulo State University and a researcher of the National Council for Scientific and Technological Development (CNPq). She has experience in beef cattle breeding, working closely with the beef industry in Brazil. Lately, she has been leading research projects, based in complete DNA and RNA sequences, with the objective of developing technologies to increase biologic knowledge and to promote genetic improvement of quality, efficiency and sustainability of Nellore beef cattle production.
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Jarrod is an evolutionary biologist based in the Institute for Evolutionary Biology at the University of Edinburgh. He is interested in understanding how natural and kin selection operate in wild systems, and how the genetic basis of traits determines how they evolve in response to selection. His lab combines theoretical work and statistical development with empirical work primarily on wild populations of bird. Current QG projects in the lab are 1) the importance of indirect genetic effects (parent-offspring, siblings) for the evolution of growth traits and the relationship between indirect genetic models and kin selection models 2) the role of phenotypic plasticity versus genetic differentiation in response to spatially and temporally fluctuating environments 3) the relative importance of mutation versus selection in determining levels of quantitative genetic variation and 4) theory and statistical methods for dealing with genetic and environmental skew. In addition to these biological questions he is interested in general statistical methods for hierarchical models, particularly MCMC methods for non-Gaussian data.
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Jarrod is an evolutionary biologist based in the Institute for Evolutionary Biology at the University of Edinburgh. He is interested in understanding how natural and kin selection operate in wild systems, and how the genetic basis of traits determines how they evolve in response to selection. His lab combines theoretical work and statistical development with empirical work primarily on wild populations of bird. Current QG projects in the lab are 1) the importance of indirect genetic effects (parent-offspring, siblings) for the evolution of growth traits and the relationship between indirect genetic models and kin selection models 2) the role of phenotypic plasticity versus genetic differentiation in response to spatially and temporally fluctuating environments 3) the relative importance of mutation versus selection in determining levels of quantitative genetic variation and 4) theory and statistical methods for dealing with genetic and environmental skew. In addition to these biological questions he is interested in general statistical methods for hierarchical models, particularly MCMC methods for non-Gaussian data.
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Rachel Hawken currently leads a team at Cobb-Vantress developing genetic tools to maintain a competitive product for the broiler breeding industry. To achieve this goal her team explores genomic and statistical genetic approaches, and engages innovative technologies and collaborative research. Rachel received her Ph.D. at The University of Melbourne, School of Veterinary Science. She moved to Minnesota to complete Postdoctoral Fellow and Research Fellow positions at the School of Veterinary Science at the University of Minnesota. Rachel then returned to Australia to join the Commonwealth Science and Industrial Research Organization (CSIRO) as a Senior Research scientist, before being recruited to Cobb in Arkansas. Rachel is now the Senior Director for Genetics (Genomics and Quantitative Genetics) at Cobb. The focus of Rachel’s early academic career was the development and testing of genomic tools to enable the selection of superior breeding stock for the swine, sheep, dairy and beef industries. Since joining Cobb, Rachel has implemented such genomic tools for the genetic improvement of the Cobb broiler. In addition, she has had the privilege of designing and implementing logistic and sampling systems needed to engage genomic technologies. Rachel is also responsible for the statistical analyses of large broiler performance data sets produced by Cobb to achieve genetic improvement.
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Rachel Hawken currently leads a team at Cobb-Vantress developing genetic tools to maintain a competitive product for the broiler breeding industry. To achieve this goal her team explores genomic and statistical genetic approaches, and engages innovative technologies and collaborative research. Rachel received her Ph.D. at The University of Melbourne, School of Veterinary Science. She moved to Minnesota to complete Postdoctoral Fellow and Research Fellow positions at the School of Veterinary Science at the University of Minnesota. Rachel then returned to Australia to join the Commonwealth Science and Industrial Research Organization (CSIRO) as a Senior Research scientist, before being recruited to Cobb in Arkansas. Rachel is now the Senior Director for Genetics (Genomics and Quantitative Genetics) at Cobb. The focus of Rachel’s early academic career was the development and testing of genomic tools to enable the selection of superior breeding stock for the swine, sheep, dairy and beef industries. Since joining Cobb, Rachel has implemented such genomic tools for the genetic improvement of the Cobb broiler. In addition, she has had the privilege of designing and implementing logistic and sampling systems needed to engage genomic technologies. Rachel is also responsible for the statistical analyses of large broiler performance data sets produced by Cobb to achieve genetic improvement.
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David is an evolutionary geneticist based at Florida State University who studies the relationship between the genomic, genetic and functional underpinnings of life and the process of adaptation at the phenotypic level. His lab uses the appendages of Drosophila melanogaster as a model. His current research goal is to understand how the processes of mutation and the forces that maintain quantitative genetic variation within populations are connected to long-term evolutionary trends.
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David is an evolutionary geneticist based at Florida State University who studies the relationship between the genomic, genetic and functional underpinnings of life and the process of adaptation at the phenotypic level. His lab uses the appendages of Drosophila melanogaster as a model. His current research goal is to understand how the processes of mutation and the forces that maintain quantitative genetic variation within populations are connected to long-term evolutionary trends.
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Satish Kumar is a scientist at Plant & Food Research, New Zealand. He earned his PhD degree in Genetics and Breeding from Massey University, and then worked as a scientist (Tree Improvement) at the New Zealand Forest Research Institute, Rotorua for 10 years before joining Plant & Food Research in 2009. His area of research includes breeding and genetic evaluation strategies, germplasm conservation and improvement, and genetic architecture of fruit traits. Dr Kumar led the first application of genomic selection and GWAS in apple breeding. His current research focuses on the integration of genetics and genomics technologies into breeding programmes of horticultural crops.
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Satish Kumar is a scientist at Plant & Food Research, New Zealand. He earned his PhD degree in Genetics and Breeding from Massey University, and then worked as a scientist (Tree Improvement) at the New Zealand Forest Research Institute, Rotorua for 10 years before joining Plant & Food Research in 2009. His area of research includes breeding and genetic evaluation strategies, germplasm conservation and improvement, and genetic architecture of fruit traits. Dr Kumar led the first application of genomic selection and GWAS in apple breeding. His current research focuses on the integration of genetics and genomics technologies into breeding programmes of horticultural crops.
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Michael Lynch is Director of the Biodesign Institute for Mechanisms of Evolution at Arizona State University. His research is focused on mechanisms of evolution at the gene, genomic, cellular, and phenotypic levels, with special attention being given to the roles of mutation, random genetic drift, and recombination. This work relies on the integration of theory development and computational analysis with empirical work on several model systems, including the microcrustacean Daphnia, the ciliate Paramecium, and numerous microbial species. He is well-known to us all from the text books Lynch & Walsh (1998) Genetic Analysis of Quantitative Traits and now Walsh & Lynch (2018) Evolution and Selection of Quantitative Traits, as well as from Lynch (2007) Origins of Genome Architecture. He is a member of the US National Academy of Sciences, and past president of the Genetics Society of America, Society for Molecular Biology and Evolution, and Society for the Study of Evolution.
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Michael Lynch is Director of the Biodesign Institute for Mechanisms of Evolution at Arizona State University. His research is focused on mechanisms of evolution at the gene, genomic, cellular, and phenotypic levels, with special attention being given to the roles of mutation, random genetic drift, and recombination. This work relies on the integration of theory development and computational analysis with empirical work on several model systems, including the microcrustacean Daphnia, the ciliate Paramecium, and numerous microbial species. He is well-known to us all from the text books Lynch & Walsh (1998) Genetic Analysis of Quantitative Traits and now Walsh & Lynch (2018) Evolution and Selection of Quantitative Traits, as well as from Lynch (2007) Origins of Genome Architecture. He is a member of the US National Academy of Sciences, and past president of the Genetics Society of America, Society for Molecular Biology and Evolution, and Society for the Study of Evolution.
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Peter Visscher FRS is a quantitative geneticist with research interests focussed on a better understanding of genetic variation for complex traits in human populations, including quantitative traits and disease, and on systems genomics. The first half of his research career to date was predominantly in livestock genetics (animal breeding is applied quantitative genetics), whereas the last 15 years he has contributed to methods, software and applications to quantify and dissect genetic variation in human traits.
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Peter Visscher FRS is a quantitative geneticist with research interests focussed on a better understanding of genetic variation for complex traits in human populations, including quantitative traits and disease, and on systems genomics. The first half of his research career to date was predominantly in livestock genetics (animal breeding is applied quantitative genetics), whereas the last 15 years he has contributed to methods, software and applications to quantify and dissect genetic variation in human traits.
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Jian Yang is a Professor of Statistical Genomics at the Institute for Molecular Bioscience, The University of Queensland (UQ). He received his PhD in 2008 from Zhejiang University, China, before undertaking postdoctoral research at the QIMR Berghofer Medical Research Institute in Brisbane. He joined UQ in 2012. His primary research interests are in developing novel statistical methods to better understand the genetic architecture of complex traits and diseases, to identify putative target genes, and to improve the accuracy of genomic risk prediction using high-throughput genetic and genomic data. He has led the development of QG analysis tools such as GCTA, SMR and OSCA. His recent papers have been on causal inference using GWAS summary data, and an extremely resource-efficient GWAS tool for large-scale data.
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Jian Yang is a Professor of Statistical Genomics at the Institute for Molecular Bioscience, The University of Queensland (UQ). He received his PhD in 2008 from Zhejiang University, China, before undertaking postdoctoral research at the QIMR Berghofer Medical Research Institute in Brisbane. He joined UQ in 2012. His primary research interests are in developing novel statistical methods to better understand the genetic architecture of complex traits and diseases, to identify putative target genes, and to improve the accuracy of genomic risk prediction using high-throughput genetic and genomic data. He has led the development of QG analysis tools such as GCTA, SMR and OSCA. His recent papers have been on causal inference using GWAS summary data, and an extremely resource-efficient GWAS tool for large-scale data.
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Theo Meuwissen is a Professor at the Norwegian University of Life Sciences. His work focuses on uniting quantitative genetic theory with genomics technology, revolutionizing the genetic improvement of livestock and crops.
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Theo Meuwissen is a Professor at the Norwegian University of Life Sciences. His work focuses on uniting quantitative genetic theory with genomics technology, revolutionizing the genetic improvement of livestock and crops.
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Herman (Han) Mulder is Associate Professor at Wageningen University & Research Animal Breeding and Genomics, Netherlands. His main research interests are quantitative genetics of genotype by environment interaction and genetic control of environmental variation in livestock and aquaculture. Han’s research focuses on developing statistical methods to estimate genetic variance in environmental sensitivity, either due to known environmental factors, such as temperature, or unknown factors that could be animal specific and appear as differences in within-individual variance or within-family variance. Currently, Han’s research is focused at how genetic variance in environmental variance is a measure of genetic variance in resilience when using longitudinal profiles of animals such as daily milk yield in cattle and daily feed intake in various livestock species.
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Herman (Han) Mulder is Associate Professor at Wageningen University & Research Animal Breeding and Genomics, Netherlands. His main research interests are quantitative genetics of genotype by environment interaction and genetic control of environmental variation in livestock and aquaculture. Han’s research focuses on developing statistical methods to estimate genetic variance in environmental sensitivity, either due to known environmental factors, such as temperature, or unknown factors that could be animal specific and appear as differences in within-individual variance or within-family variance. Currently, Han’s research is focused at how genetic variance in environmental variance is a measure of genetic variance in resilience when using longitudinal profiles of animals such as daily milk yield in cattle and daily feed intake in various livestock species.
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Jessica received a Bachelor of Science degree in genetics from the University of Wisconsin-Madison in 2009. During her time at Wisconsin she worked for Professor Bill Tracy’s sweetcorn breeding program where she developed a love for plant breeding. Shortly after graduation, Jessica began her PhD work at Cornell University under the direction of wheat breeder and plant breeding professor Mark Sorrells. Jessica’s PhD research focused on genomic selection for quantitative disease resistance in wheat, and it included one of the first empirical genomic selection experiments in plants. After receiving her PhD in 2014, Jessica took a position as an assistant professor at Cornell and an adjunct associate scientist at CIMMYT working on integrating genomic selection and high-throughput phenotyping to predict breeding values for yield in wheat. Jessica is now leading the quantitative genetics cluster at the international rice research institute (IRRI) where her research currently focuses on improving rice breeding efficiency and monitoring breeding program effectiveness.
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Jessica received a Bachelor of Science degree in genetics from the University of Wisconsin-Madison in 2009. During her time at Wisconsin she worked for Professor Bill Tracy’s sweetcorn breeding program where she developed a love for plant breeding. Shortly after graduation, Jessica began her PhD work at Cornell University under the direction of wheat breeder and plant breeding professor Mark Sorrells. Jessica’s PhD research focused on genomic selection for quantitative disease resistance in wheat, and it included one of the first empirical genomic selection experiments in plants. After receiving her PhD in 2014, Jessica took a position as an assistant professor at Cornell and an adjunct associate scientist at CIMMYT working on integrating genomic selection and high-throughput phenotyping to predict breeding values for yield in wheat. Jessica is now leading the quantitative genetics cluster at the international rice research institute (IRRI) where her research currently focuses on improving rice breeding efficiency and monitoring breeding program effectiveness.
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Matthew Stephens is Professor of Statistics and Professor of Human Genetics at the University of Chicago, and a Gordon and Betty Moore Investigator in Data Driven Discovery. He received a BA in Mathematics (1992) and Diploma in Mathematical Statistics (1994) from the University of Cambridge UK, and a D.Phil in Statistics (1997) from the University of Oxford UK. Dr Stephens is a statistician and data scientist, who has made seminal contributions to the practice and applications of statistics in genetics. His research interests include analysis of
population structure, analysis of genetic association studies (including both complex traits, and molecular phenotypes, such as gene expression and chromatin accessibility), large scale regression and multiple testing. His lab distributes several widely-used sofware packages for statistical analysis, including PHASE and fastPHASE (for haplotype inference), GEMMA (for association testing) and BIMBAM (for genotype imputation and association testing).
Dr Stephens’s Honors include the Guy Medal in Bronze by the
Royal Statistical Society in 2006, was honored as a Medallion Lecturer by the Institute for Mathematical Statistics in 2014, and inclusion in the Thomson-Reuters list of Highly Cited Researchers 2014.
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Matthew Stephens is Professor of Statistics and Professor of Human Genetics at the University of Chicago, and a Gordon and Betty Moore Investigator in Data Driven Discovery. He received a BA in Mathematics (1992) and Diploma in Mathematical Statistics (1994) from the University of Cambridge UK, and a D.Phil in Statistics (1997) from the University of Oxford UK. Dr Stephens is a statistician and data scientist, who has made seminal contributions to the practice and applications of statistics in genetics. His research interests include analysis of
population structure, analysis of genetic association studies (including both complex traits, and molecular phenotypes, such as gene expression and chromatin accessibility), large scale regression and multiple testing. His lab distributes several widely-used sofware packages for statistical analysis, including PHASE and fastPHASE (for haplotype inference), GEMMA (for association testing) and BIMBAM (for genotype imputation and association testing).
Dr Stephens’s Honors include the Guy Medal in Bronze by the
Royal Statistical Society in 2006, was honored as a Medallion Lecturer by the Institute for Mathematical Statistics in 2014, and inclusion in the Thomson-Reuters list of Highly Cited Researchers 2014.
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Dr. Barbara Stranger, PhD is an Assistant Professor in the Section of Genetic Medicine at the University of Chicago Department of Medicine. In addition, she is a Faculty Fellow in the Institute for Genomics and Systems Biology and The Center for Translational Data Science. Her lab analyzes multi-dimensional human genomics data, particularly transcriptome data and genetic variation data, in the context of human health and disease. She develops effective analytic approaches for large-scale analysis of functional genomics data, and applies systems biology methodologies to integrate data of different types to inform biology of complex traits. She is a member of the Analysis Working Group (AWG) of NIH’s Genotype-Tissue Expression (GTEx) project, and leads the Sex Differences Working Group within the GTEx AWG. Current projects in her laboratory focus on understanding mechanisms and consequences of sex differences in: 1) The human transcriptome, 2) The human proteome, 3) The genetic architecture of neuropsychiatric traits, and 4) The genetics and genomics of cancer and response to therapy. She has a longstanding interest in evolution, and also applies the tools and approaches of population and evolutionary genetics to her research areas.
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Dr. Barbara Stranger, PhD is an Assistant Professor in the Section of Genetic Medicine at the University of Chicago Department of Medicine. In addition, she is a Faculty Fellow in the Institute for Genomics and Systems Biology and The Center for Translational Data Science. Her lab analyzes multi-dimensional human genomics data, particularly transcriptome data and genetic variation data, in the context of human health and disease. She develops effective analytic approaches for large-scale analysis of functional genomics data, and applies systems biology methodologies to integrate data of different types to inform biology of complex traits. She is a member of the Analysis Working Group (AWG) of NIH’s Genotype-Tissue Expression (GTEx) project, and leads the Sex Differences Working Group within the GTEx AWG. Current projects in her laboratory focus on understanding mechanisms and consequences of sex differences in: 1) The human transcriptome, 2) The human proteome, 3) The genetic architecture of neuropsychiatric traits, and 4) The genetics and genomics of cancer and response to therapy. She has a longstanding interest in evolution, and also applies the tools and approaches of population and evolutionary genetics to her research areas.
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Shamil Sunyaev is a Professor of Computational Genomics Medicine at Harvard Medical School. He obtained a PhD in molecular biophysics from the Moscow Institute of Physics and Technology and completed his postdoctoral training in bioinformatics at the European Molecular Biology Laboratory (EMBL). The primary focus of research in his lab is genetic variation, including the biology and evolution of mutation, the effect of variation on molecular function and structure, population genetics as a lens on evolution, and the maintenance and allelic architecture of complex traits.
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Shamil Sunyaev is a Professor of Computational Genomics Medicine at Harvard Medical School. He obtained a PhD in molecular biophysics from the Moscow Institute of Physics and Technology and completed his postdoctoral training in bioinformatics at the European Molecular Biology Laboratory (EMBL). The primary focus of research in his lab is genetic variation, including the biology and evolution of mutation, the effect of variation on molecular function and structure, population genetics as a lens on evolution, and the maintenance and allelic architecture of complex traits.
Albert Tenesa studied agricultural engineering at the Polytechnic University of Valencia before undertaking an MSc in Quantitative Genetics and Genome Analysis at the University of Edinburgh, where he also completed his PhD in quantitative genetics, under the supervision of Peter Visscher and Sara Knott. After a postdoc with Professor Malcolm Dunlop working on colorectal cancer genetics, he became a group leader at the Roslin Institute and the Medical Research Council Human Genetics Unit at the University of Edinburgh. Albert’s research aims to understand how genetic variation contributes to phenotypic variation of complex traits in humans and to develop the tools that will help in transitioning from study cohorts to whole populations. You can follow his research team on twitter: @GroupTenesa.
Albert Tenesa studied agricultural engineering at the Polytechnic University of Valencia before undertaking an MSc in Quantitative Genetics and Genome Analysis at the University of Edinburgh, where he also completed his PhD in quantitative genetics, under the supervision of Peter Visscher and Sara Knott. After a postdoc with Professor Malcolm Dunlop working on colorectal cancer genetics, he became a group leader at the Roslin Institute and the Medical Research Council Human Genetics Unit at the University of Edinburgh. Albert’s research aims to understand how genetic variation contributes to phenotypic variation of complex traits in humans and to develop the tools that will help in transitioning from study cohorts to whole populations. You can follow his research team on twitter: @GroupTenesa.
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Bruce Walsh is Professor, Ecology and Evolutionary Biology at the University of Arizona. His interests are broadly in using mathematical models to explore the interface of genetics and evolution, with particular focus on the evolution and analysis of complex genetic characters. He is well known to us all from the textbooks Lynch & Walsh (1998) Genetic Analysis of Quantitative Traits and now Walsh & Lynch (2018) Evolution and Selection of Quantitative Traits. He is a prolific teacher, having taught over 80 short courses during the last decade in 24 countries. He founded the Tucson Plant Breeding Institute and was a founding instructor in the African Plant Breeding Academy. He is also an avid lepidopterist, having described over two dozen new species of Arizona moths, and has three species named after him.
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Bruce Walsh is Professor, Ecology and Evolutionary Biology at the University of Arizona. His interests are broadly in using mathematical models to explore the interface of genetics and evolution, with particular focus on the evolution and analysis of complex genetic characters. He is well known to us all from the textbooks Lynch & Walsh (1998) Genetic Analysis of Quantitative Traits and now Walsh & Lynch (2018) Evolution and Selection of Quantitative Traits. He is a prolific teacher, having taught over 80 short courses during the last decade in 24 countries. He founded the Tucson Plant Breeding Institute and was a founding instructor in the African Plant Breeding Academy. He is also an avid lepidopterist, having described over two dozen new species of Arizona moths, and has three species named after him.
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Bruce Weir is a Professor of Biostatistics at the University of Washington in Seattle. His research focuses on statistical methodology for genetic data, with an emphasis on allelic dependencies, population structure, disease associations and relationships, including applications in forensic genetics.
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Bruce Weir is a Professor of Biostatistics at the University of Washington in Seattle. His research focuses on statistical methodology for genetic data, with an emphasis on allelic dependencies, population structure, disease associations and relationships, including applications in forensic genetics.
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Dr. Eimear Kenny, PhD, is Founding Director of the Institute for Genomic Health, and Associate Professor of Medicine and Genetics at Mount Sinai. She leads research at the interface of genomics, medicine, and computer science. Her research spans a number of different fields, including population and statistical genetics; computational and machine-learning approaches for genomics; biobank- and cohort-based research on monogenic disorders and common diseases; polygenic risk for human diseases and precision medicine
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Dr. Eimear Kenny, PhD, is Founding Director of the Institute for Genomic Health, and Associate Professor of Medicine and Genetics at Mount Sinai. She leads research at the interface of genomics, medicine, and computer science. Her research spans a number of different fields, including population and statistical genetics; computational and machine-learning approaches for genomics; biobank- and cohort-based research on monogenic disorders and common diseases; polygenic risk for human diseases and precision medicine
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Steve McCarroll is Professor of Biomedical Science and Genetics at Harvard Medical School. His research program reflects the diversity of his training. He was a Ph.D. student in Cori Bargmann’s lab (genetics and neuroscience in C. elegans) at U.C. San Francisco, then a postdoc in David Altshuler’s lab (human genetics and genomics) at MGH and the Broad Institute. The focus of Steve’s research is how human genomes vary and how this variation shapes human biology. His lab has led the development of single cell droplet gene expression sequencing and is using this technology to investigate allele specific gene expression in individual cell types.
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Steve McCarroll is Professor of Biomedical Science and Genetics at Harvard Medical School. His research program reflects the diversity of his training. He was a Ph.D. student in Cori Bargmann’s lab (genetics and neuroscience in C. elegans) at U.C. San Francisco, then a postdoc in David Altshuler’s lab (human genetics and genomics) at MGH and the Broad Institute. The focus of Steve’s research is how human genomes vary and how this variation shapes human biology. His lab has led the development of single cell droplet gene expression sequencing and is using this technology to investigate allele specific gene expression in individual cell types.
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Trudy Mackay, FRS, is the Director of the Center for Human Genetics at Clemson University. Her research focuses on how multiple interacting molecular polymorphisms and environmental factors cause phenotypic variation in quantitative (complex) traits within and between populations and species. Using fruit flies (Drosophila) as a model system, she has used transposon tagging, high-resolution recombination mapping, genetic complementation tests, and whole genome transcript profiling to identify novel genes affecting morphology, lifespan, behaviors, stress resistance and human disease. She leads the Drosophila Genetic Reference Panel project that provides resources and computational approaches to integrate genotype-phenotype relationships across multiple levels of biological organization to uncover entire genetic pathways that affect variation of quantitative traits.
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Trudy Mackay, FRS, is the Director of the Center for Human Genetics at Clemson University. Her research focuses on how multiple interacting molecular polymorphisms and environmental factors cause phenotypic variation in quantitative (complex) traits within and between populations and species. Using fruit flies (Drosophila) as a model system, she has used transposon tagging, high-resolution recombination mapping, genetic complementation tests, and whole genome transcript profiling to identify novel genes affecting morphology, lifespan, behaviors, stress resistance and human disease. She leads the Drosophila Genetic Reference Panel project that provides resources and computational approaches to integrate genotype-phenotype relationships across multiple levels of biological organization to uncover entire genetic pathways that affect variation of quantitative traits.