Isaac Newton Institute for Mathematical Sciences

Mathematical, Statistical and Computational Aspects of the New Science of Metagenomics

24 Mar-17 Apr 2014

Organisers: Wally Gilks (Leeds), Daniel Huson (Tübingen), Elisa Loza (Rothamsted Research), Simon Tavaré (Cambridge), Gabriel Valiente (Technical University of Catalonia) and Tandy Warnow (Texas at Austin)

Scientific Advisory Committee: Vincent Moulton (East Anglia), Mihai Pop (Maryland)

Programme Theme

MTG programme identifier: colours that can be found in communities of bacteria in the geyser pools in Yellowstone National ParkMetagenomics is the study of the total genomic content of microbial communities. In metagenomic studies, DNA material is sampled collectively from the microorganisms that populate the environment of interest (e.g. agricultural soil, ocean water, or the human gut). The extracted DNA sequences are subsequently used to profile the environment and its biodiversity, its dominant microbial classes or biological functions, and whether and how this profile differs from those of other environments.

The impact of metagenomics in our understanding of the natural world has been, and will continue to be, revolutionary and profound. Insights derived from metagenomic studies have become increasingly relevant in areas as diverse as human health, bioenergy, environmental sciences and paleontology.

This research programme will bring together leading expertise in the multiple disciplines involved in metagenomics including mathematics, computer science, probability and statistics, biomedical research and biology.

The brief of the programme will be to explore the major current analytical and computational open problems in metagenomics, and to identify opportunities for application and development of theory and methods, with an emphasis on synergy between disciplines.

Particular themes will include:

  • Community profiling and comparative metagenomics
  • Assembly of metagenomic data in the context of evolving NGS platforms
  • Community structure and dynamics: beyond taxonomic and functional characterisation
  • Analysis of microbial community transcriptomes, proteomes and metabolomes

These themes provide a rich source of mathematical problems in areas such as probability and statistics theory, dynamic programming, combinatorics and graph theory.