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SAMSI Offers Two New Programs for 2014–2015

1 December 2013 131 views No Comment

The Statistical and Applied Mathematical Sciences Institute (SAMSI) recently announced it will offer two new programs in 2014–2015 to integrate applied mathematicians and statisticians with other scientific disciplines to further research in bioinformatics and ecology.

One program, “Beyond Bioinformatics, Statistical, and Mathematical Challenges,” will look at the statistical and mathematical challenges arising in the analysis of genomic and related data with the goal of addressing relevant biological questions. As genomic and related data are growing more complex, novel methods need to be developed to help with data synthesis and analysis to answer previously inconceivable questions about biological processes. This program will focus on the following:

  • Statistical pre-processing of emerging high-throughput data
  • Dependence in high-dimensional data, in particular multivariate discrete counts
  • Integration of multi-omics data
  • Modeling dynamics of mixtures such as populations of cells, variants, and meta-genomics
  • Big Data and machine learning for addressing ‘omic issues

Program leaders for the program include Alexander Alekseyenko of the NYU School of Medicine, Karin Dorman of Iowa State University, Nick Hengartner of Los Alamos National Laboratory, Susan Holmes of Stanford University, Katerina Kechris of the University of Colorado-Denver, Shili Lin of The Ohio State University, Dan Nettleton of Iowa State University, and Hongyu Zhao of Yale University.

The other SAMSI program is “Mathematical and Statistical Ecology,” which will bring together statisticians, mathematicians, and theoretical ecologists to study and develop the interactions among different approaches ecological modeling has developed. One approach is that theoretical ecologists have developed mathematical models that are analyzed using traditional tools of applied mathematics, such as partial differential equations and dynamical systems. These models are then used to look at resilience, tipping points, or other ecological properties. A second approach, typically used by statisticians and data analysts, involves sophisticated statistical tools such as Bayesian hierarchical models that are applied to large spatio-temporal datasets, but often these models are developed without the detailed consideration of nonlinear dynamics. Some of the topics that will be explored through the year include the following:

  • Critical thresholds and tipping points
  • Resilience of ecological systems, leading indicators
  • Multi-scale and multivariate statistical method
  • Climate and biodiversity
  • Implications for public policy

There is also likely to be a joint working group between the programs on landscape genomics.

Program leaders for “Mathematical and Statistical Ecology” include Philip Dixon of Iowa State University, Lou Gross of the University of Tennessee and NIMBioS, Jennifer Hoeting of Colorado State University, Mevin Hooten of Colorado State University, Lea Jenkins of Clemson University, Claire Lunch of the National Ecological Observatory Network, Ron McRoberts of the U.S. Forest Service, Jay Ver Hoef of NOAA, and Linda Young of the National Agricultural Statistics Service.

There are many opportunities for people to be involved with the SAMSI programs. Financial support is available for visiting researchers to be a resident at SAMSI for one month to one year. Several postdoctoral positions are funded for each SAMSI program. Young researchers have special opportunities to participate that typically have a one-year appointment.

Workshops and working groups give many people the opportunity to collaborate with others on research projects and to network with their peers. Dedicated workshops will allow graduate and upper-level undergraduate students to learn about the latest research and applications in the statistical and mathematical sciences. All involved researchers will get chances to broaden their interests and skill sets, participate in cutting-edge interdisciplinary projects, and make new connections. New researchers and members of under-represented groups are especially encouraged to participate.

Visit SAMSI website to find out more about either of these research programs, or to apply.

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