Modelling time-varying gene regulatory processes with probabilistic graphical models
Dr Dirk Husmeier, Biomathematics and Statistics Scotland, UK
Abstract
Dirk Husmeier graduated in Physics (Dipl.-Phys.) at the University of Bochum (Germany) in 1991, and received both his M.Sc. (Information Processing and Neural Networks) and Ph.D. (Applied Mathematics and Neural Computation) degrees from King’s College London in 1994 and 1997, respectively. After working as a postdoctoral research fellow in the Electrical Engineering Department of Imperial College London from 1997 to 1999, he joined Biomathematics and Statistics Scotland (BioSS) as a research scientist in October 1999. Since 2006, Dr Husmeier has been leading the statistical bioinformatics research theme at BioSS
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Dr Dirk Husmeier, Biomathematics and Statistics Scotland, UK
Dr Dirk Husmeier, Biomathematics and Statistics Scotland, UK
Dirk Husmeier graduated in Physics (Dipl.-Phys.) at the University of Bochum (Germany) in 1991, and received both his M.Sc. (Information Processing and Neural Networks) and Ph.D. (Applied Mathematics and Neural Computation) degrees from King’s College London in 1994 and 1997, respectively. After working as a postdoctoral research fellow in the Electrical Engineering Department of Imperial College London from 1997 to 1999, he joined Biomathematics and Statistics Scotland (BioSS) as a research scientist in October 1999. Since 2006, Dr Husmeier has been leading the statistical bioinformatics research theme at BioSS.
Sparse modelling and inference of dynamic genetic networks
Professor Ernst Wit, Groningen University, The Netherlands
Abstract
Professor Wit is the Chair of Statistics and Probability at the Johann Bernoulli Institute at the University of Groningen since 2008. Before this he held positions at the University of Glasgow and Lancaster University. He obtained his PhD in Philosophy in 1997 from the Pennsylvania State University and a PhD in Statistics in 2000 from the University of Chicago. His research interest focus modelling of structured data, in particular with applications in genomics. He is the author of the book "Statistics for Microarrays" (Wiley 2004) and is currently working on a manuscript on statistical modelling of genetic networks. Recurrent themes in this work are high-dimensional data, sparse and structured models and complex model selection. Ernst Wit is a scientific advisory board member of The Genome Analysis Centre in Norwich.
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Professor Ernst Wit, Groningen University, The Netherlands
Professor Ernst Wit, Groningen University, The Netherlands
Professor Wit is the Chair of Statistics and Probability at the Johann Bernoulli Institute at the University of Groningen since 2008. Before this he held positions at the University of Glasgow and Lancaster University. He obtained his PhD in Philosophy in 1997 from the Pennsylvania State University and a PhD in Statistics in 2000 from the University of Chicago. His research interest focus modelling of structured data, in particular with applications in genomics. He is the author of the book "Statistics for Microarrays" (Wiley 2004) and is currently working on a manuscript on statistical modelling of genetic networks. Recurrent themes in this work are high-dimensional data, sparse and structured models and complex model selection. Ernst Wit is a scientific advisory board member of The Genome Analysis Centre in Norwich.
Gene and QTL networks
Dr Lauren McIntyre, University of Florida, USA
Abstract
Lauren McIntyre received her PhD in 1996 from North Carolina State University under the direction of Dr. Bruce Weir. Her PhD focused on testing Hardy-Weinberg Equilibrium. At Duke University Medical School she developed methods for mapping multigenic binary traits. In 1999, with a move to Purdue University, Dr. McIntyre developed an interest in the genotype to phenotype map. The emergence of new technologies for measuring gene expression, and the increasing availability of sequence data have provided motivation for her work on analytical approaches to modeling gene expression networks, and relating them to phenotypes. In 2006 Dr McIntyre moved to the University of Florida to join a campus wide Genetics Institute. She works on a wide variety of organisms, and remains interested in the fundamental question of the role of genetic variation.
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Dr Lauren McIntyre, University of Florida, USA
Dr Lauren McIntyre, University of Florida, USA
Lauren McIntyre received her PhD in 1996 from North Carolina State University under the direction of Dr. Bruce Weir. Her PhD focused on testing Hardy-Weinberg Equilibrium. At Duke University Medical School she developed methods for mapping multigenic binary traits. In 1999, with a move to Purdue University, Dr. McIntyre developed an interest in the genotype to phenotype map. The emergence of new technologies for measuring gene expression, and the increasing availability of sequence data have provided motivation for her work on analytical approaches to modeling gene expression networks, and relating them to phenotypes. In 2006 Dr McIntyre moved to the University of Florida to join a campus wide Genetics Institute. She works on a wide variety of organisms, and remains interested in the fundamental question of the role of genetic variation.
High-dimensional QTL mapping in Arabidopsis
Professor Rebecca Doerge, Purdue University, USA
Abstract
Professor Rebecca Doerge joined Purdue University in 1995. She holds a joint appointment between the Colleges of Agriculture (Department of Agronomy) and Science (Department of Statistics). Professor Doerge's research program is focused on Statistical Bioinformatics, a component of bioinformatics that brings together many scientific disciplines into one arena to ask, answer, and disseminate biologically interesting information in the quest to understand the ultimate function of DNA and epigenomic associations for each and every genome. Rebecca has published over 100 scientific articles, published one book, and graduated over 17 Ph.D. students. She is an elected a Fellow of the American Statistical Association, a Fellow of the American Association for the Advancement of Science (AAAS), the Director of the Statistical Bioinformatics Center, and is currently the Head of the Department of Statistics, Purdue University.
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Professor Rebecca Doerge, Purdue University, USA
Professor Rebecca Doerge, Purdue University, USA
Professor Rebecca Doerge joined Purdue University in 1995. She holds a joint appointment between the Colleges of Agriculture (Department of Agronomy) and Science (Department of Statistics). Professor Doerge's research program is focused on Statistical Bioinformatics, a component of bioinformatics that brings together many scientific disciplines into one arena to ask, answer, and disseminate biologically interesting information in the quest to understand the ultimate function of DNA and epigenomic associations for each and every genome. Rebecca has published over 100 scientific articles, published one book, and graduated over 17 Ph.D. students. She is an elected a Fellow of the American Statistical Association, a Fellow of the American Association for the Advancement of Science (AAAS), the Director of the Statistical Bioinformatics Center, and is currently the Head of the Department of Statistics, Purdue University.