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

by Cambridge University

Metagenomics 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. 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.Read more at http://www.newton.ac.uk/programmes/MTG/

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Recent Episodes
  • A Bayesian approach to inferring the phylogenetic structure of microbial communities: the case of a seasonal Antarctic lake
    Mar 31, 2014 – 42:17
  • Application of Bayesian model averaging and population Monte Carlo to inference from metagenomic mixture
    Mar 31, 2014 – 30:15
  • Burrows-Wheeler Transform (BWT) based methods for assembly and haplotype analysis
    Apr 2, 2014 – 01:07:00
  • Convergence analysis of balancing principle for nonlinear Tikhonov regularization in Hilbert scales for statistical inverse problems
    Mar 31, 2014 – 30:11
  • Digging into the soil metagenome
    Mar 31, 2014 – 50:27
  • Ecological genomics from metagenomic data?
    Mar 31, 2014 – 51:50
  • Estimating within-host viral genetic diversity from next-generation sequencing data
    Mar 31, 2014 – 43:07
  • Inferring genotype-phenotype relationships from (meta-)genomes
    Jun 2, 2014 – 54:03
  • Inferring Mixed Viral Populations
    Mar 31, 2014 – 32:04
  • Lessons learned from operating a big metagenomics resource
    Apr 2, 2014 – 58:23
  • Linking taxa to function through contig clustering of microbial metagenomes
    Mar 31, 2014 – 43:54
  • Metagenome, metatranscriptome and single cell genome sequencing of biogas-producing microbial communities from production-scale biogas plants
    Mar 31, 2014 – 30:06
  • Metagenomic assembly and characterisation of viral signatures with MetaCortex
    Mar 31, 2014 – 34:27
  • Microbiome, Metagenomics and High-dimensional Compositional Data Analysis
    Mar 31, 2014 – 55:52
  • Mission impossible: metagenomic assembly
    Mar 31, 2014 – 58:45
  • Modelling macroecological patterns: Neutral theory and beyond
    Apr 14, 2014 – 33:21
  • New bioinformatic resources for taxonomic assignment of metagenomic NGS data: BioMaS, ITSoneDB and SARMA
    Mar 31, 2014 – 30:03
  • NGS Sequence Assembly for Metagenomic Data
    Mar 31, 2014 – 44:54
  • Predictability and unpredictability in the dynamics of nutrient-cycling microbial ecosystems
    Mar 31, 2014 – 37:34
  • Quikr: Rapid Bacterial Community Reconstruction Via Compressive Sensing
    Mar 31, 2014 – 34:02
  • Reasonable names and reasonable terms for Bacteria and Archaea
    Apr 2, 2014 – 56:58
  • Species identification from medical metagenomic sequence data
    Mar 31, 2014 – 29:09
  • Statistical Machine Learning for Modeling Early Respiratory Microbiota Composition
    Mar 31, 2014 – 36:57
  • The living layer: the microbial interface between superior organisms and the environment as revealed by metagenomics
    Mar 31, 2014 – 44:25
  • TIPP: Taxon Identification and Phylogenetic Profiling
    Mar 28, 2014 – 38:31
  • Understanding Biology from the Sequence Data of Uncultured Organisms
    Mar 31, 2014 – 54:32
  • Using metatranscriptomics to make global predictions: The impact of temperature on marine phytoplankton resource allocation and metabolism
    Mar 31, 2014 – 37:58
  • Waste Not, Want Not: Why Rarefying Microbiome Data is not an optimal normalization procedure
    Mar 31, 2014 – 57:14
  • Webserver-supported storage of metagenomic datasets using MEGANv5
    Mar 31, 2014 – 21:59
  • Why mixture modelling?
    Apr 10, 2014 – 01:28:00
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