Dawn Field

Publications of Dawn Field

• Predicting bacterial community assemblages using an artificial neural network approach.

  Authors: Peter E Larsen, Dawn Field, Jack A Gilbert

  Nature methods. 04/2012;

  Understanding the interactions between the Earth's microbiome and the physical, chemical and biological environment is a fundamental goal of microbial ecology. We describe a bioclimatic modelingUnderstanding the interactions between the Earth's microbiome and the physical, chemical and biological environment is a fundamental goal of microbial ecology. We describe a bioclimatic modeling approach that leverages artificial neural networks to predict microbial community structure as a function of environmental parameters and microbial interactions. This method was better at predicting observed community structure than were any of several single-species models that do not incorporate biotic interactions. The model was used to interpolate and extrapolate community structure over time with an average Bray-Curtis similarity of 89.7. Additionally, community structure was extrapolated geographically to create the first microbial map derived from single-point observations. This method can be generalized to the many microbial ecosystems for which detailed taxonomic data are currently being generated, providing an observation-based modeling technique for predicting microbial taxonomic structure in ecological studies.

• Cloud BioLinux: pre-configured and on-demand bioinformatics computing for the genomics community.

  Authors: Konstantinos Krampis, Tim Booth, Brad Chapman, Bela Tiwari, Mesude Bicak, Dawn Field, Karen Nelson

  BMC bioinformatics. 03/2012; 13(1):42.

  ABSTRACT: BACKGROUND: A steep drop in the cost of next-generation sequencing during recent years has made the technology affordable to the majority of researchers, but downstream bioinformaticABSTRACT: BACKGROUND: A steep drop in the cost of next-generation sequencing during recent years has made the technology affordable to the majority of researchers, but downstream bioinformatic analysis still poses a resource bottleneck for smaller laboratories and institutes that do not have access to substantial computational resources. Sequencing instruments are typically bundled with only the minimal processing and storage capacity required for data capture during sequencing runs. Given the scale of sequence datasets, scientific value cannot be obtained from acquiring a sequencer unless it is accompanied by an equal investment in informatics infrastructure. RESULTS: Cloud BioLinux is a publicly accessible Virtual Machine (VM) that enables scientists to quickly provision on-demand infrastructures for high-performance bioinformatics computing using cloud platforms. Users have instant access to a range of pre-configured command line and graphical software applications, including a full-featured desktop interface, documentation and over 135 bioinformatics packages for applications including sequence alignment, clustering, assembly, display, editing, and phylogeny. Each tool's functionality is fully described in the documentation directly accessible from the graphical interface of the VM. Besides the Amazon EC2 cloud, we have started instances of Cloud BioLinux on a private Eucalyptus cloud installed at the J. Craig Venter Institute, and demonstrated access to the bioinformatic tools interface through a remote connection to EC2 instances from a local desktop computer. Documentation for using Cloud BioLinux on EC2 is available from our project website, while a Eucalyptus cloud image and VirtualBox Appliance is also publicly available for download and use by researchers with access to private clouds. CONCLUSIONS: CloudBioLinux provides a platform for developing bioinformatics infrastructures on the cloud. An automated and configurable process builds Virtual Machines, allowing the development of highly customized versions from a shared code base. This shared community toolkit enables application specific analysis platforms on the cloud by minimizing the effort required to prepare and maintain them.

• Toward interoperable bioscience data.

  Authors: Susanna-Assunta Sansone, Philippe Rocca-Serra, Dawn Field, Eamonn Maguire, Chris Taylor, Oliver Hofmann, Hong Fang, Steffen Neumann, Weida Tong, Linda Amaral-Zettler [......] Dorothy Reilly, Magali Roux, Caroline E Shamu, Catherine A Shang, Christoph Steinbeck, Anne Trefethen, Bryn Williams-Jones, Katherine Wolstencroft, Ioannis Xenarios, Winston Hide

  Nature genetics. 02/2012; 44(2):121-6.

  To make full use of research data, the bioscience community needs to adopt technologies and reward mechanisms that support interoperability and promote the growth of an open 'data commoning' culture.To make full use of research data, the bioscience community needs to adopt technologies and reward mechanisms that support interoperability and promote the growth of an open 'data commoning' culture. Here we describe the prerequisites for data commoning and present an established and growing ecosystem of solutions using the shared 'Investigation-Study-Assay' framework to support that vision.

• A second special issue of Standards In Genomic Sciences from the Genomic Standards Consortium.

  Authors: Dawn Field, Renzo Kottmann, Norman Morrison, Peter Sterk

  Standards in genomic sciences. 11/2011; 5(2):194.

• The Western English Channel contains a persistent microbial seed bank.

  Authors: J Gregory Caporaso, Konrad Paszkiewicz, Dawn Field, Rob Knight, Jack A Gilbert

  The ISME journal. 11/2011;

  Robust seasonal dynamics in microbial community composition have previously been observed in the English Channel L4 marine observatory. These could be explained either by seasonal changes in the taxaRobust seasonal dynamics in microbial community composition have previously been observed in the English Channel L4 marine observatory. These could be explained either by seasonal changes in the taxa present at the L4 site, or by the continuous modulation of abundance of taxa within a persistent microbial community. To test these competing hypotheses, deep sequencing of 16S rRNA from one randomly selected time point to a depth of 10 729 927 reads was compared with an existing taxonomic survey data covering 6 years. When compared against the 6-year survey of 72 shallow sequenced time points, the deep sequenced time point maintained 95.4% of the combined shallow OTUs. Additionally, on average, 99.75%±0.06 (mean±s.d.) of the operational taxonomic units found in each shallow sequenced sample were also found in the single deep sequenced sample. This suggests that the vast majority of taxa identified in this ecosystem are always present, but just in different proportions that are predictable. Thus observed changes in community composition are actually variations in the relative abundance of taxa, not, as was previously believed, demonstrating extinction and recolonization of taxa in the ecosystem through time.

• Defining seasonal marine microbial community dynamics.

  Authors: Jack A Gilbert, Joshua A Steele, J Gregory Caporaso, Lars Steinbrück, Jens Reeder, Ben Temperton, Susan Huse, Alice C McHardy, Rob Knight, Ian Joint, Paul Somerfield, Jed A Fuhrman, Dawn Field

  The ISME journal. 08/2011; 6(2):298-308.

  Here we describe, the longest microbial time-series analyzed to date using high-resolution 16S rRNA tag pyrosequencing of samples taken monthly over 6 years at a temperate marine coastal site offHere we describe, the longest microbial time-series analyzed to date using high-resolution 16S rRNA tag pyrosequencing of samples taken monthly over 6 years at a temperate marine coastal site off Plymouth, UK. Data treatment effected the estimation of community richness over a 6-year period, whereby 8794 operational taxonomic units (OTUs) were identified using single-linkage preclustering and 21 130 OTUs were identified by denoising the data. The Alphaproteobacteria were the most abundant Class, and the most frequently recorded OTUs were members of the Rickettsiales (SAR 11) and Rhodobacteriales. This near-surface ocean bacterial community showed strong repeatable seasonal patterns, which were defined by winter peaks in diversity across all years. Environmental variables explained far more variation in seasonally predictable bacteria than did data on protists or metazoan biomass. Change in day length alone explains >65% of the variance in community diversity. The results suggested that seasonal changes in environmental variables are more important than trophic interactions. Interestingly, microbial association network analysis showed that correlations in abundance were stronger within bacterial taxa rather than between bacteria and eukaryotes, or between bacteria and environmental variables.

• The Genomic Standards Consortium.

  Authors: Dawn Field, Linda Amaral-Zettler, Guy Cochrane, James R Cole, Peter Dawyndt, George M Garrity, Jack Gilbert, Frank Oliver Glöckner, Lynette Hirschman, Ilene Karsch-Mizrachi [......] Nikos Kyrpides, Folker Meyer, Inigo San Gil, Susanna-Assunta Sansone, Lynn M Schriml, Peter Sterk, Tatiana Tatusova, David W Ussery, Owen White, John Wooley

  PLoS biology. 06/2011; 9(6):e1001088.

  A vast and rich body of information has grown up as a result of the world's enthusiasm for 'omics technologies. Finding ways to describe and make available this information that maximise itsA vast and rich body of information has grown up as a result of the world's enthusiasm for 'omics technologies. Finding ways to describe and make available this information that maximise its usefulness has become a major effort across the 'omics world. At the heart of this effort is the Genomic Standards Consortium (GSC), an open-membership organization that drives community-based standardization activities, Here we provide a short history of the GSC, provide an overview of its range of current activities, and make a call for the scientific community to join forces to improve the quality and quantity of contextual information about our public collections of genomes, metagenomes, and marker gene sequences.

• Minimum information about a marker gene sequence (MIMARKS) and minimum information about any (x) sequence (MIxS) specifications.

  Authors: Pelin Yilmaz, Renzo Kottmann, Dawn Field, Rob Knight, James R Cole, Linda Amaral-Zettler, Jack A Gilbert, Ilene Karsch-Mizrachi, Anjanette Johnston, Guy Cochrane [......] James M Tiedje, Doyle V Ward, George M Weinstock, Doug Wendel, Owen White, Andrew Whiteley, Andreas Wilke, Jennifer R Wortman, Tanya Yatsunenko, Frank Oliver Glöckner

  Nature biotechnology. 05/2011; 29(5):415-20.

  Here we present a standard developed by the Genomic Standards Consortium (GSC) for reporting marker gene sequences--the minimum information about a marker gene sequence (MIMARKS). We also introduce aHere we present a standard developed by the Genomic Standards Consortium (GSC) for reporting marker gene sequences--the minimum information about a marker gene sequence (MIMARKS). We also introduce a system for describing the environment from which a biological sample originates. The 'environmental packages' apply to any genome sequence of known origin and can be used in combination with MIMARKS and other GSC checklists. Finally, to establish a unified standard for describing sequence data and to provide a single point of entry for the scientific community to access and learn about GSC checklists, we present the minimum information about any (x) sequence (MIxS). Adoption of MIxS will enhance our ability to analyze natural genetic diversity documented by massive DNA sequencing efforts from myriad ecosystems in our ever-changing biosphere.

• Enriching public descriptions of marine phages using the Genomic Standards Consortium MIGS standard.

  Authors: Melissa Beth Duhaime, Renzo Kottmann, Dawn Field, Frank Oliver Glöckner

  Standards in genomic sciences. 04/2011; 4(2):271-85.

  In any sequencing project, the possible depth of comparative analysis is determined largely by the amount and quality of the accompanying contextual data. The structure, content, and storage of thisIn any sequencing project, the possible depth of comparative analysis is determined largely by the amount and quality of the accompanying contextual data. The structure, content, and storage of this contextual data should be standardized to ensure consistent coverage of all sequenced entities and facilitate comparisons. The Genomic Standards Consortium (GSC) has developed the "Minimum Information about Genome/Metagenome Sequences (MIGS/MIMS)" checklist for the description of genomes and here we annotate all 30 publicly available marine bacteriophage sequences to the MIGS standard. These annotations build on existing International Nucleotide Sequence Database Collaboration (INSDC) records, and confirm, as expected that current submissions lack most MIGS fields. MIGS fields were manually curated from the literature and placed in XML format as specified by the Genomic Contextual Data Markup Language (GCDML). These "machine-readable" reports were then analyzed to highlight patterns describing this collection of genomes. Completed reports are provided in GCDML. This work represents one step towards the annotation of our complete collection of genome sequences and shows the utility of capturing richer metadata along with raw sequences.

• Data shopping in an open marketplace: Introducing the Ontogrator web application for marking up data using ontologies and browsing using facets.

  Authors: Norman Morrison, David Hancock, Lynette Hirschman, Peter Dawyndt, Bert Verslyppe, Nikos Kyrpides, Renzo Kottmann, Pelin Yilmaz, Frank Oliver Glöckner, Jeff Grethe, Tim Booth, Peter Sterk, Goran Nenadic, Dawn Field

  Standards in genomic sciences. 04/2011; 4(2):286-92.

  In the future, we hope to see an open and thriving data market in which users can find and select data from a wide range of data providers. In such an open access market, data are products that mustIn the future, we hope to see an open and thriving data market in which users can find and select data from a wide range of data providers. In such an open access market, data are products that must be packaged accordingly. Increasingly, eCommerce sellers present heterogeneous product lines to buyers using faceted browsing. Using this approach we have developed the Ontogrator platform, which allows for rapid retrieval of data in a way that would be familiar to any online shopper. Using Knowledge Organization Systems (KOS), especially ontologies, Ontogrator uses text mining to mark up data and faceted browsing to help users navigate, query and retrieve data. Ontogrator offers the potential to impact scientific research in two major ways: 1) by significantly improving the retrieval of relevant information; and 2) by significantly reducing the time required to compose standard database queries and assemble information for further research. Here we present a pilot implementation developed in collaboration with the Genomic Standards Consortium (GSC) that includes content from the StrainInfo, GOLD, CAMERA, Silva and Pubmed databases. This implementation demonstrates the power of ontogration and highlights that the usefulness of this approach is fully dependent on both the quality of data and the KOS (ontologies) used. Ideally, the use and further expansion of this collaborative system will help to surface issues associated with the underlying quality of annotation and could lead to a systematic means for accessing integrated data resources.

• The genomic standards consortium: bringing standards to life for microbial ecology.

  Authors: Pelin Yilmaz, Jack A Gilbert, Rob Knight, Linda Amaral-Zettler, Ilene Karsch-Mizrachi, Guy Cochrane, Yasukazu Nakamura, Susanna-Assunta Sansone, Frank Oliver Glöckner, Dawn Field

  The ISME journal. 04/2011; 5(10):1565-7.

• Predicted Relative Metabolomic Turnover (PRMT): determining metabolic turnover from a coastal marine metagenomic dataset.

  Authors: Peter E Larsen, Frank R Collart, Dawn Field, Folker Meyer, Kevin P Keegan, Christopher S Henry, John McGrath, John Quinn, Jack A Gilbert

  Microbial informatics and experimentation. 01/2011; 1(1):4.

  ABSTRACT: The world's oceans are home to a diverse array of microbial life whose metabolic activity helps to drive the earth's biogeochemical cycles. Metagenomic analysis has revolutionized ourABSTRACT: The world's oceans are home to a diverse array of microbial life whose metabolic activity helps to drive the earth's biogeochemical cycles. Metagenomic analysis has revolutionized our access to these communities, providing a system-scale perspective of microbial community interactions. However, while metagenome sequencing can provide useful estimates of the relative change in abundance of specific genes and taxa between environments or over time, this does not investigate the relative changes in the production or consumption of different metabolites. We propose a methodology, Predicted Relative Metabolic Turnover (PRMT) that defines and enables exploration of metabolite-space inferred from the metagenome. Our analysis of metagenomic data from a time-series study in the Western English Channel demonstrated considerable correlations between predicted relative metabolic turnover and seasonal changes in abundance of measured environmental parameters as well as with observed seasonal changes in bacterial population structure. The PRMT method was successfully applied to metagenomic data to explore the Western English Channel microbial metabalome to generate specific, biologically testable hypotheses. Generated hypotheses linked organic phosphate utilization to Gammaproteobactaria, Plantcomycetes, and Betaproteobacteria, chitin degradation to Actinomycetes, and potential small molecule biosynthesis pathways for Lentisphaerae, Chlamydiae, and Crenarchaeota. The PRMT method can be applied as a general tool for the analysis of additional metagenomic or transcriptomic datasets.

• Alive and well at 100.

  Authors: George M Garrity, Dawn Field, Nikos Kyrpides

  Standards in genomic sciences. 01/2011; 4(1):1.

• Towards BioDBcore: a community-defined information specification for biological databases.

  Authors: Pascale Gaudet, Amos Bairoch, Dawn Field, Susanna-Assunta Sansone, Chris F. Taylor, Teresa K. Attwood, Alex Bateman, Judith A. Blake, Carol J. Bult, J. Michael Cherry [......] Lorna Richardson, Philippe Rocca-Serra, Paul N. Schofield, Damian Smedley, Christopher Southan, Tin Wee Tan, Tatiana A. Tatusova, Patricia L. Whetzel, Owen White, Chisato Yamasaki

  Nucleic Acids Research. 01/2011; 39:7-10.

• Towards BioDBcore: a community-defined information specification for biological databases.

  Authors: Pascale Gaudet, Amos Bairoch, Dawn Field, Susanna-Assunta Sansone, Chris Taylor, Teresa K Attwood, Alex Bateman, Judith A Blake, Carol J Bult, J Michael Cherry [......] Lorna Richardson, Philippe Rocca-Serra, Paul N Schofield, Damian Smedley, Christopher Southan, Tin Wee Tan, Tatiana Tatusova, Patricia L Whetzel, Owen White, Chisato Yamasaki

  Nucleic acids research. 01/2011; 39(Database issue):D7-10.

  The present article proposes the adoption of a community-defined, uniform, generic description of the core attributes of biological databases, BioDBCore. The goals of these attributes are to provideThe present article proposes the adoption of a community-defined, uniform, generic description of the core attributes of biological databases, BioDBCore. The goals of these attributes are to provide a general overview of the database landscape, to encourage consistency and interoperability between resources and to promote the use of semantic and syntactic standards. BioDBCore will make it easier for users to evaluate the scope and relevance of available resources. This new resource will increase the collective impact of the information present in biological databases.

• Data standards for Omics data: the basis of data sharing and reuse.

  Authors: Stephen A Chervitz, Eric W Deutsch, Dawn Field, Helen Parkinson, John Quackenbush, Phillipe Rocca-Serra, Susanna-Assunta Sansone, Christian J Stoeckert, Chris F Taylor, Ronald Taylor, Catherine A Ball

  Methods in molecular biology (Clifton, N.J.). 01/2011; 719:31-69.

  To facilitate sharing of Omics data, many groups of scientists have been working to establish the relevant data standards. The main components of data sharing standards are experiment descriptionTo facilitate sharing of Omics data, many groups of scientists have been working to establish the relevant data standards. The main components of data sharing standards are experiment description standards, data exchange standards, terminology standards, and experiment execution standards. Here we provide a survey of existing and emerging standards that are intended to assist the free and open exchange of large-format data.

• Supervised classification of microbiota mitigates mislabeling errors.

  Authors: Dan Knights, Justin Kuczynski, Omry Koren, Ruth E Ley, Dawn Field, Rob Knight, Todd Z DeSantis, Scott T Kelley

  The ISME journal. 10/2010; 5(4):570-3.

• ISA software suite: supporting standards-compliant experimental annotation and enabling curation at the community level.

  Authors: Philippe Rocca-Serra, Marco Brandizi, Eamonn Maguire, Nataliya Sklyar, Chris Taylor, Kimberly Begley, Dawn Field, Stephen Harris, Winston Hide, Oliver Hofmann, Steffen Neumann, Peter Sterk, Weida Tong, Susanna-Assunta Sansone

  Bioinformatics (Oxford, England). 09/2010; 26(18):2354-6.

  The first open source software suite for experimentalists and curators that (i) assists in the annotation and local management of experimental metadata from high-throughput studies employing one or aThe first open source software suite for experimentalists and curators that (i) assists in the annotation and local management of experimental metadata from high-throughput studies employing one or a combination of omics and other technologies; (ii) empowers users to uptake community-defined checklists and ontologies; and (iii) facilitates submission to international public repositories. Availability and Implementation: Software, documentation, case studies and implementations at http://www.isa-tools.org.

• Genomic standards consortium workshop: metagenomics, metadata and metaanalysis (m3).

  Authors: Peter Sterk, Lynette Hirschman, Dawn Field, John Wooley

  Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing. 01/2010;

  The M3 workshop has, as its primary focus, the rapidly growing area of metagenomics, including the metadata standards and the meta-analysis approaches needed to organize, process and interpretThe M3 workshop has, as its primary focus, the rapidly growing area of metagenomics, including the metadata standards and the meta-analysis approaches needed to organize, process and interpret metagenomics data. The PSB Workshop builds on the first M3 meeting, a Special Interest Group (SIG) meeting at ISMB 2009, organized by the Genomics Standards Consortium.

• Metagenomics: A foundling finds its feet.

  Authors: Jack A Gilbert, Folker Meyer, Dawn Field, Lynn M Schriml, George M Garrity

  Standards in genomic sciences. 01/2010; 3(2):212-3.