Our research is focused on the discovery and characterization of novel bacterial, archaeal and eukaryotic microbes and viruses in environmental sequence data. We use multi-omics (metagenomics, metatranscriptomics, single cell genomics and phylogenomics) and machine learning to identify new divergent lineages and expand the Tree of Life. We then investigate the coding potential to find novel functions that may impact microbiome structure and biogeochemical cycles.
Research Team
Research Areas
Software
A read simulation tool for generating synthetic sequencing data from genomic sequences
A clustering tool for phylogenetic distance matrix analysis and genome grouping
A predictive tool for microbial symbionts in environmental sequence data, including microbial phenotype along the symbiosis continuum
A specialized tool for identifying, extracting, and assembling rRNA genes from environmental sequence data
A comprehensive tool for giant virus taxonomy and quality assessment that assigns taxonomy to putative giant virus contigs or MAGs, and estimates genome completeness and contamination.
A computational pipeline enabling fast and easy construction of phylogenetic trees from user-provided genomes and phylogenetic markers.
