Research in the Kyrpides group focuses on Microbiome Data Science. This includes the understanding of structure and function of various microorganisms and microbial communities and the elucidation of the evolutionary dynamics that shape the microbial genomes. To accomplish that members of the group are developing novel methods for enabling large-scale comparative analysis, as well as mining and visualization of big data.
Current big data projects in the group include the sequencing and comparative analysis of thousands of archaeal and bacterial type strains (GEBA-type strains project), uncovering Earth’s Virome, the delineation of host-virus interactions, and the discovery of novel protein families from microbiome data.
|Nikos Kyrpides, PI||David Paez-Espino,
More about Nikos.
|David’s research is focused on the discovery of novel viral genomes and the exploration of host-virus interactions looking through all available microbiome data.||
George’s research is focusing on the development of novel approaches to enable comparative analysis and visualization of big data.
- Ovchinnikov S. et al. (2017) Protein structure determination using metagenome sequence data. Science 355(6322):294-298
- Paez-Espino D. et al. (2017) IMG/VR: a database of cultured and uncultured DNA Viruses and retroviruses. Nucleic Acids Res. 45(D1):D457-D465.
- Mukherjee S. et al. (2017) Genomes OnLine Database (GOLD) v.6: data updates and feature enhancements. Nucleic Acids Res. 45(D1):D446-D456.
- Hadjithomas M et al. (2017) IMG-ABC: new features for bacterial secondary metabolism analysis and targeted biosynthetic gene cluster discovery in thousands of microbial genomes. Nucleic Acids Res. 45(D1):D560-D565.
- Chen IA et al. (2017) IMG/M: integrated genome and metagenome comparative data analysis system. Nucleic Acids Res. 45(D1):D507-D516
- Paez-Espino, D. et al. (2016) Uncovering Earth’s virome. Nature 536:425-30
- Kyrpides NC. et al. (2016) Microbiome Data Science: Understanding Our Microbial Planet. Trends Microbiol. 24(6):425-7.
- Eloe-Fadrosh EA, et al. (2016) Metagenomics uncovers gaps in amplicon-based detection of microbial diversity. Nat Microbiol. 15032
- Eloe-Fadrosh EA, et al. (2016) Global metagenomic survey reveals a new bacterial candidate phylum in geothermal springs. Nat Commun. 7:10476
- Oulas A. et al. (2016) Metagenomic investigation of the geologically unique Hellenic Volcanic Arc reveals a distinctive ecosystem with unexpected physiology. Environ Microbiol. 18(4):1122-36.
- Varghese NJ, et al. (2015) Microbial species delineation using whole genome sequences. Nucleic Acids Res. 43(14):6761-71
- Tennessen K, et al. (2015) ProDeGe: a computational protocol for fully automated decontamination of genomes. ISME J. 10(1):269-72
- Seshadri R, et al. (2105) Discovery of Novel Plant Interaction Determinants from the Genomes of 163 Root Nodule Bacteria. Sci Rep. 5:16825
- Kyrpides NC et al. (2014) Genomic Encyclopedia of Bacteria and Archaea: Sequencing a Myriad of Type Strains. PLoS Biology 12(8):e1001920
- Ivanova N. et al. (2014) Stop Codon Reassignments in the Wild. Science 344(6186):909-13
- Mavromatis K et al. (2012) The fast changing landscape of sequencing technologies and their impact on microbial genome assemblies and annotation. PLoS One. 7(12):e48837.
- Markowitz VM. et al. (2012) IMG/M-HMP: A Metagenome Comparative Analysis System for the Human Microbiome Project. PLoS One. 7(7):e40151
- Pati A et al. (2010) GenePRIMP: A GENE PRediction IMprovement Pipeline for Prokaryotic genomes. Nature Methods. 2010; 7: 455-7.
- Kyrpides, NC. (2009) Fifteen Years of Microbial Genomics: Meeting the Challenges and Fulfilling the Dream. Nature Biotechnology 27, 627 -632
- Mavromatis K et al. (2007) Use of simulated data sets to evaluate the fidelity of metagenomic processing methods. Nature Methods. 4: 495-500.