Search

Your search keyword '"Christa B. Smith"' showing total 2 results
Start Over Author "Christa B. Smith" Journal scientific data
2 results on '"Christa B. Smith"'

1. Digital Microbe: a genome-informed data integration framework for team science on emerging model organisms

Author

Iva Veseli, Michelle A. DeMers, Zachary S. Cooper, Matthew S. Schechter, Samuel Miller, Laura Weber, Christa B. Smith, Lidimarie T. Rodriguez, William F. Schroer, Matthew R. McIlvin, Paloma Z. Lopez, Makoto Saito, Sonya Dyhrman, A. Murat Eren, Mary Ann Moran, and Rogier Braakman

Subjects
Science
Abstract

Abstract The remarkable pace of genomic data generation is rapidly transforming our understanding of life at the micron scale. Yet this data stream also creates challenges for team science. A single microbe can have multiple versions of genome architecture, functional gene annotations, and gene identifiers; additionally, the lack of mechanisms for collating and preserving advances in this knowledge raises barriers to community coalescence around shared datasets. “Digital Microbes” are frameworks for interoperable and reproducible collaborative science through open source, community-curated data packages built on a (pan)genomic foundation. Housed within an integrative software environment, Digital Microbes ensure real-time alignment of research efforts for collaborative teams and facilitate novel scientific insights as new layers of data are added. Here we describe two Digital Microbes: 1) the heterotrophic marine bacterium Ruegeria pomeroyi DSS-3 with > 100 transcriptomic datasets from lab and field studies, and 2) the pangenome of the cosmopolitan marine heterotroph Alteromonas containing 339 genomes. Examples demonstrate how an integrated framework collating public (pan)genome-informed data can generate novel and reproducible findings.

Published
2024
Full Text
View/download PDF

2. Microbial metagenomes and metatranscriptomes during a coastal phytoplankton bloom

Author

Marcel Huntemann, Alex Copeland, Courtney M. Thomas, I. Min A. Chen, Neha Varghese, Bryce Foster, Supratim Mukherjee, Simon Roux, Mary Ann Moran, Brian Foster, Nikos C. Kyrpides, Alicia Clum, Kaitlin Esson, Brent Nowinski, Krishnaveni Palaniappan, Tijana Glavina del Rio, Ronald P. Kiene, Chris Daum, Christina M. Preston, Christa B. Smith, Christopher A. Scholin, T. B. K. Reddy, William B. Whitman, Natalia Ivanova, James M. Birch, Roman Marin, and Emiley A. Eloe-Fadrosh

Subjects
Statistics and Probability, Data Descriptor, 010504 meteorology & atmospheric sciences, Library and Information Sciences, 01 natural sciences, Algal bloom, 18S ribosomal RNA, California, Education, Microbial ecology, 03 medical and health sciences, Element cycles, Phytoplankton, Genetics, Sequencing, 14. Life underwater, lcsh:Science, 030304 developmental biology, 0105 earth and related environmental sciences, 0303 health sciences, biology, Bacteria, Ecology, fungi, Dinoflagellate, Amplicon, Eutrophication, biology.organism_classification, Archaea, Computer Science Applications, 13. Climate action, Metagenomics, Dinoflagellida, Metagenome, lcsh:Q, Statistics, Probability and Uncertainty, Bloom, Transcriptome, Bay, Information Systems
Abstract

Metagenomic and metatranscriptomic time-series data covering a 52-day period in the fall of 2016 provide an inventory of bacterial and archaeal community genes, transcripts, and taxonomy during an intense dinoflagellate bloom in Monterey Bay, CA, USA. The dataset comprises 84 metagenomes (0.8 terabases), 82 metatranscriptomes (1.1 terabases), and 88 16S rRNA amplicon libraries from samples collected on 41 dates. The dataset also includes 88 18S rRNA amplicon libraries, characterizing the taxonomy of the eukaryotic community during the bloom. Accompanying the sequence data are chemical and biological measurements associated with each sample. These datasets will facilitate studies of the structure and function of marine bacterial communities during episodic phytoplankton blooms., Design Type(s)transcription profiling design • sequence assembly objective • biodiversity assessment objectiveMeasurement Type(s)transcription profiling assay • marine metagenome • microbial communityTechnology Type(s)RNA sequencing • DNA sequencing • amplicon sequencingFactor Type(s)assay protocol • temporal_instantSample Characteristic(s)marine metagenome • Monterey Bay • ocean biome Machine-accessible metadata file describing the reported data (ISA-Tab format)

Published
2019

Catalog

Books, media, physical & digital resources
See catalog results