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January 2017
  • 27 Jan 17
    Speaker: Professor Jean-Philippe Vert, Mines ParisTech, France Title: Machine learning for patient stratification from genomic data Abstract: As the cost and throughput of genomic technologies reach a point where DNA sequencing is close to becoming a routine exam at the clinics, there is a lot of hope that treatments of diseases like cancer can dramatically improve by a digital revolution in medicine, where smart algorithms a...
  • 26 Jan 17
    Speaker: Junhyong Kin, Department of Computer & Information Science, University of Pennsylvania Title: Geometric Embeddings of Biological Data
  • 16 Jan 17
    Speaker: Cedric Archambeau, Amazon Title: Introduction to Machine Learning
  • 06 Jan 17
    Speaker: Dr Niall Cardin, Google Mountain View Talk title: Topics in “Data Science” at Google. Niall will introduce statistics/data-science at Google and give a description of how they do experiments. He will then talk about some specific interesting cases, such as long term user behavior changes, and also talk about methods for cases where they can’t run experiments.
December 2016
  • 15 Dec 16
    Speaker: Professor Eric Kolaczyk, Department of Mathematics and Statistics, Boston University Title: Network-based Statistical Models and Methods for Identification of Cellular Mechanisms of Action Abstract: Identifying biological mechanisms of action (e.g. genes, functional elements, or biological pathways) that control disease states, drug response, and altered cellular function is a multifaceted problem involving a dynamic...
  • 02 Dec 16
    Speaker: Professor Richard Durbin, Wellcome Trust Sanger Institute, Cambridge Title: Inferring population history from whole genome sequences Abstract: Genome sequences carry genetic information to make an organism, but they are also products of evolution and as such carry information about the genetic history of individuals and species. In recent years analysis of genome sequence data has told us much about the origins of hu...
October 2016
  • 14 Oct 16
    Speaker: Professor Matthew Stephens, Department of Human Genetics, University of Chicago Title: “Come join the multiple testing party!” Abstract: Multiple testing is often described as a “burden”. My goal is to convince you that multiple testing is better viewed as an opportunity, and that instead of laboring under this burden you should be looking for ways to exploit this opportunity. I invite you to ...
  • 06 Oct 16
    Stein’s method is a powerful and elegant probabilistic tool for deriving distributional approximations in probability theory. It has found numerous applications in fields as varied as statistical inference, random graph theory, computational biology and machine learning. This workshop will focus on recent theoretical developments to the method as well as applications to problems from probability and statistics. Abstracts Andreas Anastasiou (London School of Economics)...
September 2016
  • 16 Sep 16
    Speaker: Professor Susan Holmes, Stanford University Title: Statistical Challenges posed by the Human Microbiome Abstract: We propose a new statistical workflow for the analyses of bacterial strains in longitudinal data analyses of data from the Human Microbiome. This includes using hierarchical mixtures for abundance modeling, hierarchical testing strategies and the propagation of uncertainty through the analyses to the ordi...
  • 12 Sep - 14 Sep 16
    Organisers: Jonathan Marchini, University of Oxford, UK; Simon Myers, University of Oxford, UK; Jotun Hein, University of Oxford, UK; Peter Ralph, University of South California, USA The 2nd Probabilistic Modeling in Genomics Conference (ProbGen16), was held at the Department of Statistics, University of Oxford, UK. The conference covered probabilistic models, algorithms, and statistical methods across a broad range of applications in genetics and genomics. We invite...