Abstract: Microbiome research is rapidly transitioning into Data Science. The unprecedented volume of microbiome data being generated pose significant challenges with respect to standards and management strategies, but also bear great new opportunities that can fuel discovery. Computational analysis of microbiome samples involving previously uncultured organisms, is currently advancing our understanding of the structure and function of entire microbial communities and expanding our knowledge of genetic and functional diversity of individual micro-organisms. I will describe some of our computational approaches and will emphasize the value of data processing integration in enabling the exploration of large metagenomic datasets and the discovery of novelty. I will present current approaches and will discuss a few science vignettes in the exploration of microbial, viral, and functional diversity.

Bio: Dr. Kyrpides joined the DOE Joint Genome Institute in 2004 to lead the Genome Biology Program and the development of the comparative analysis platforms for microbial genomes and metagenomes (IMG). He became the Metagenomics Program head in 2010 and has the combined Microbial Genomes and Metagenomes Program since 2011. Prior to joining the DOE Joint Genome Institute, Dr. Kyrpides led the development of the genome analysis and Bioinformatics core at Integrated Genomics Inc. in Chicago, IL. He did his postdoctoral studies with Carl Woese at the University of Illinois at Urbana-Champaign and at Argonne National Laboratory. Dr. Kyrpides’ research focus on Microbiome Research with an emphasis on Microbiome Data Science. His group is developing novel methods for enabling large-scale comparative analysis, as well as mining and visualization of big data.

Abstract: Microbiome research is rapidly transitioning into Data Science. The unprecedented volume of microbiome data being generated pose significant challenges with respect to standards and management strategies, but also bear great new opportunities that can fuel discovery. Computational analysis of microbiome samples involving previously uncultured organisms, is currently advancing our understanding of the structure and function of entire microbial communities and expanding our knowledge of genetic and functional diversity of individual micro-organisms. I will describe some of our computational approaches and will emphasize the value of data processing integration in enabling the exploration of large metagenomic datasets and the discovery of novelty. I will present current approaches and will discuss a few science vignettes in the exploration of microbial, viral, and functional diversity.

Bio: Dr. Kyrpides joined the DOE Joint Genome Institute in 2004 to lead the Genome Biology Program and the development of the comparative analysis platforms for microbial genomes and metagenomes (IMG). He became the Metagenomics Program head in 2010 and has the combined Microbial Genomes and Metagenomes Program since 2011. Prior to joining the DOE Joint Genome Institute, Dr. Kyrpides led the development of the genome analysis and Bioinformatics core at Integrated Genomics Inc. in Chicago, IL. He did his postdoctoral studies with Carl Woese at the University of Illinois at Urbana-Champaign and at Argonne National Laboratory. Dr. Kyrpides’ research focus on Microbiome Research with an emphasis on Microbiome Data Science. His group is developing novel methods for enabling large-scale comparative analysis, as well as mining and visualization of big data.