29 research outputs found
Annotation of gene product function from high-throughput studies using the Gene Ontology.
High-throughput studies constitute an essential and valued source of information for researchers. However, high-throughput experimental workflows are often complex, with multiple data sets that may contain large numbers of false positives. The representation of high-throughput data in the Gene Ontology (GO) therefore presents a challenging annotation problem, when the overarching goal of GO curation is to provide the most precise view of a gene's role in biology. To address this, representatives from annotation teams within the GO Consortium reviewed high-throughput data annotation practices. We present an annotation framework for high-throughput studies that will facilitate good standards in GO curation and, through the use of new high-throughput evidence codes, increase the visibility of these annotations to the research community
The Plant Ontology Database: a community resource for plant structure and developmental stages controlled vocabulary and annotations
The Plant Ontology Consortium (POC, http://www.plantontology.org) is a collaborative effort among model plant genome databases and plant researchers that aims to create, maintain and facilitate the use of a controlled vocabulary (ontology) for plants. The ontology allows users to ascribe attributes of plant structure (anatomy and morphology) and developmental stages to data types, such as genes and phenotypes, to provide a semantic framework to make meaningful cross-species and database comparisons. The POC builds upon groundbreaking work by the Gene Ontology Consortium (GOC) by adopting and extending the GOC's principles, existing software and database structure. Over the past year, POC has added hundreds of ontology terms to associate with thousands of genes and gene products from Arabidopsis, rice and maize, which are available through a newly updated web-based browser (http://www.plantontology.org/amigo/go.cgi) for viewing, searching and querying. The Consortium has also implemented new functionalities to facilitate the application of PO in genomic research and updated the website to keep the contents current. In this report, we present a brief description of resources available from the website, changes to the interfaces, data updates, community activities and future enhancement
Plant Ontology (PO): a Controlled Vocabulary of Plant Structures and Growth Stages
The Plant Ontology Consortium (POC) (www.plantontology.org) is a collaborative
effort among several plant databases and experts in plant systematics, botany
and genomics. A primary goal of the POC is to develop simple yet robust
and extensible controlled vocabularies that accurately reflect the biology of plant
structures and developmental stages. These provide a network of vocabularies linked
by relationships (ontology) to facilitate queries that cut across datasets within
a database or between multiple databases. The current version of the ontology
integrates diverse vocabularies used to describe Arabidopsis, maize and rice (Oryza
sp.) anatomy, morphology and growth stages. Using the ontology browser, over 3500
gene annotations from three species-specific databases, The Arabidopsis Information
Resource (TAIR) for Arabidopsis, Gramene for rice and MaizeGDB for maize, can
now be queried and retrieved
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Whole-Plant Growth Stage Ontology for Angiosperms and Its Application in Plant Biology
Plant growth stages are identified as distinct morphological landmarks in a continuous developmental process. The terms
describing these developmental stages record the morphological appearance of the plant at a specific point in its life cycle. The
widely differing morphology of plant species consequently gave rise to heterogeneous vocabularies describing growth and
development. Each species or family specific community developed distinct terminologies for describing whole-plant growth
stages. This semantic heterogeneity made it impossible to use growth stage description contained within plant biology
databases to make meaningful computational comparisons. The Plant Ontology Consortium (http://www.plantontology.org)
was founded to develop standard ontologies describing plant anatomical as well as growth and developmental stages that can
be used for annotation of gene expression patterns and phenotypes of all flowering plants. In this article, we describe the
development of a generic whole-plant growth stage ontology that describes the spatiotemporal stages of plant growth as a set
of landmark events that progress from germination to senescence. This ontology represents a synthesis and integration of
terms and concepts from a variety of species-specific vocabularies previously used for describing phenotypes and genomic
information. It provides a common platform for annotating gene function and gene expression in relation to the developmental
trajectory of a plant described at the organismal level. As proof of concept the Plant Ontology Consortium used the plant
ontology growth stage ontology to annotate genes and phenotypes in plants with initial emphasis on those represented in The
Arabidopsis Information Resource, Gramene database, and MaizeGDB.This is the publisher’s final pdf. The published article is copyrighted by the American Society of Plant Biologists and can be found at: http://www.plantphysiol.org/
Recommended from our members
The Plant Ontology Database: a community resource for plant structure and developmental stages controlled vocabulary and annotations
The Plant Ontology Consortium (POC, http://www.plantontology.org) is a collaborative effort
among model plant genome databases and plant
researchers that aims to create, maintain and
facilitate the use of a controlled vocabulary
(ontology) for plants. The ontology allows users to
ascribe attributes of plant structure (anatomy and
morphology) and developmental stages to data
types, such as genes and phenotypes, to provide a
semantic framework to make meaningful cross-species
and database comparisons. The POC builds
upon groundbreaking work by the Gene Ontology
Consortium (GOC) by adopting and extending the
GOC’s principles, existing software and database
structure. Over the past year, POC has added
hundreds of ontology terms to associate with
thousands of genes and gene products from
Arabidopsis, rice and maize, which are available
through a newly updated web-based browser
(http://www.plantontology.org/amigo/go.cgi) for
viewing, searching and querying. The Consortium
has also implemented new functionalities to facilitate
the application of PO in genomic research and
updated the website to keep the contents current. In this report, we present a brief description of
resources available from the website, changes to
the interfaces, data updates, community activities
and future enhancement.This is the publisher’s final pdf. The published article is copyrighted by the author(s) and published by Oxford University Press. The published article can be found at: http://nar.oxfordjournals.org/
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The Plant Structure Ontology, a Unified Vocabulary of Anatomy and Morphology of a Flowering Plant
Formal description of plant phenotypes and standardized annotation of gene expression and protein localization data require
uniform terminology that accurately describes plant anatomy and morphology. This facilitates cross species comparative
studies and quantitative comparison of phenotypes and expression patterns. A major drawback is variable terminology that is
used to describe plant anatomy and morphology in publications and genomic databases for different species. The same terms
are sometimes applied to different plant structures in different taxonomic groups. Conversely, similar structures are named by
their species-specific terms. To address this problem, we created the Plant Structure Ontology (PSO), the first generic
ontological representation of anatomy and morphology of a flowering plant. The PSO is intended for a broad plant research
community, including bench scientists, curators in genomic databases, and bioinformaticians. The initial releases of the PSO
integrated existing ontologies for Arabidopsis (Arabidopsis thaliana), maize (Zea mays), and rice (Oryza sativa); more recent
versions of the ontology encompass terms relevant to Fabaceae, Solanaceae, additional cereal crops, and poplar (Populus spp.).
Databases such as The Arabidopsis Information Resource, Nottingham Arabidopsis Stock Centre, Gramene, MaizeGDB, and
SOL Genomics Network are using the PSO to describe expression patterns of genes and phenotypes of mutants and natural
variants and are regularly contributing new annotations to the Plant Ontology database. The PSO is also used in specialized
public databases, such as BRENDA, GENEVESTIGATOR, NASCArrays, and others. Over 10,000 gene annotations and phenotype
descriptions from participating databases can be queried and retrieved using the Plant Ontology browser. The PSO, as well
as contributed gene associations, can be obtained at www.plantontology.org.This is the publisher’s final pdf. The published article is copyrighted by the American Society of Plant Biologists and can be found at: http://www.plantphysiol.org/
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AgBioData consortium recommendations for sustainable genomics and genetics databases for agriculture
The future of agricultural research depends on data. The sheer volume of agricultural biological data being produced today makes excellent data management essential. Governmental agencies, publishers and science funders require datamanagement plans for publicly funded research. Furthermore, the value of data increases exponentially when they are properly stored, described, integrated and shared, so that they can be easily utilized in future analyses. AgBioData (https://www.agbiodata.org) is a consortium of people working at agricultural biological databases, data archives and knowledgbases who strive to identify common issues in database development, curation and management, with the goal of creating database products that are more Findable, Accessible, Interoperable and Reusable. We strive to promote authentic, detailed, accurate and explicit communication between all parties involved in scientific data. As a step toward this goal, we present the current state of biocuration, ontologies, metadata and persistence, database platforms, programmatic (machine) access to data, communication and sustainability with regard to data curation. Each section describes challenges and opportunities for these topics, along with recommendations and best practices