How to cite this record: FAIRsharing.org: PO; Plant Ontology; DOI: https://doi.org/10.25504/FAIRsharing.3ngg40; Last edited: Feb. 22, 2018, 2:06 p.m.; Last accessed: Mar 24 2018 7:43 a.m.
No XSD schemas defined
Conditions of UseApplies to: Data use
Finding our way through phenotypes
Deans AR,Lewis SE,Huala E,Anzaldo SS,Ashburner M,Balhoff JP,Blackburn DC,Blake JA,Burleigh JG,Chanet B,Cooper LD,Courtot M,Csosz S,Cui H,Dahdul W,Das S,Dececchi TA,Dettai A,Diogo R,Druzinsky RE,Dumontier M,Franz NM,Friedrich F,Gkoutos GV,Haendel M,Harmon LJ,Hayamizu TF,He Y,Hines HM,Ibrahim N,Jackson LM,Jaiswal P,James-Zorn C,Kohler S,Lecointre G,Lapp H,Lawrence CJ,Le Novere N,Lundberg JG,Macklin J,Mast AR,Midford PE,Miko I,Mungall CJ,Oellrich A,Osumi-Sutherland D,Parkinson H,Ramirez MJ,Richter S,Robinson PN,Ruttenberg A,Schulz KS,Segerdell E,Seltmann KC,Sharkey MJ,Smith AD,Smith B,Specht CD,Squires RB,Thacker RW,Thessen A,Fernandez-Triana J,Vihinen M,Vize PD,Vogt L,Wall CE,Walls RL,Westerfeld M,Wharton RA,Wirkner CS,Woolley JB,Yoder MJ,Zorn AM,Mabee P
PLoS Biol 2015
The plant ontology as a tool for comparative plant anatomy and genomic analyses.
Cooper L,Walls RL,Elser J,Gandolfo MA,Stevenson DW,Smith B,Preece J,Athreya B,Mungall CJ,Rensing S,Hiss M,Lang D,Reski R,Berardini TZ,Li D,Huala E,Schaeffer M,Menda N,Arnaud E,Shrestha R,Yamazaki Y,Jaiswal P
Plant Cell Physiol 2012
No guidelines defined
Models and Formats
No syntax standards defined
The MetaCrop resource contains information on the major metabolic pathways mainly in crops of agricultural and economic importance. The database includes manually curated information on reactions and the kinetic data associated with these reactions. Ontology terms are used and publication identification available to ease mining the data.
The Arabidopsis Information Resource
The Arabidopsis Information Resource (TAIR) maintains a database of genetic and molecular biology data for the model higher plant Arabidopsis thaliana.
Golm Metabolome Database
The Golm Metabolome Database (GMD) provides gas chromatography (GC) mass spectrometry (MS) reference spectra, reference metabolite profiles and tools for one of the most widespread routine technologies applied to the large scale screening and discovery of novel metabolic biomarkers.
Nottingham Arabidopsis Stock Centre Seeds Database
The Nottingham Arabidopsis Stock Centre (NASC) provides seed and information resources to the International Arabidopsis Genome Programme and the wider research community.
Gramene, a comparative mapping resource for grains
Gramene's purpose is to provide added value to data sets available within the public sector, which will facilitate researchers' ability to understand the grass genomes and take advantage of genomic sequence known in one species for identifying and understanding corresponding genes, pathways and phenotypes in other grass species.
Maize Genetics and Genomics Database
MaizeGDB is the maize research community's central repository for genetics and genomics information.
The Oryzabase is a comprehensive rice science database established in 2000 by rice researcher's committee in Japan. The Oryzabase consists of five parts, (1) genetic resource stock information, (2) gene dictionary, (3) chromosome maps, (4) mutant images, and (5) fundamental knowledge of rice science.
Genome Database for Rosaceae
The Genome Database for Rosaceae (GDR) is a curated and integrated web-based relational database providing centralized access to Rosaceae genomics and genetics data and analysis tools to facilitate cross-species utilization of data.
Manually Curated Database of Rice Proteins
‘Manually Curated Database of Rice Proteins’ (MCDRP) is a unique manually curated database based on published experimental data. Currently, the database has data for over 1800 rice proteins curated from > 4000 different experiments of over 400 research articles. Since every aspect of the experiment such as gene name, plant type, tissue and developmental stage has been digitized, experimental data can be rapidly accessed and integrated.
Genetic and Genomic Information System
GnpIS is a multispecies integrative information system dedicated to plant and fungi pests. It bridges genetic and genomic data, allowing researchers access to both genetic information (e.g. genetic maps, quantitative trait loci, association genetics, markers, polymorphisms, germplasms, phenotypes and genotypes) and genomic data (e.g. genomic sequences, physical maps, genome annotation and expression data) for species of agronomical interest. GnpIS is used by both large international projects and plant science departments at the French National Institute for Agricultural Research. It is regularly improved and released several times per year. GnpIS is accessible through a web portal and allows to browse different types of data either independently through dedicated interfaces or simultaneously using a quick search ('google like search') or advanced search (Biomart, Galaxy, Intermine) tools.
A resource providing data on bioentities and their associated ontology terms for Plant Biology. The database provides access to ontology-based annotations of genes, phenotypes and germplasms from about 90 plant species. A number of internal and external ontologies are used to annotate the biological data available from this resource.
Large-scale genomic data for peanut have only become available in the last few years, with the advent of low-cost sequencing technologies. To make the data accessible to researchers and to integrate across diverse types of data, the International Peanut Genomics Consortium funded the development of PeanutBase. This database provides access to genetic maps and markers, locations of quantitative trait loci (QTLs), genome sequences, gene locations and sequences, gene families and correspondences with genes in other species, and descriptions of traits and growth characteristics. It also provides tools for exploration and analysis, including sequence of genomic and genic sequences, and keyword searches of genes, gene families, and QTL studies. These resources should facilitate breeding advancements in peanut, helping improve crop productivity and there are a variety of resources for peanut research around the web, ranging from tools for basic plant biology to information for growers and various sectors of the peanut industry to resources for plant breeders.
The Open Biological and Biomedical Ontology (OBO) Foundry is a collective of ontology developers that are committed to collaboration and adherence to shared principles. The mission of the OBO Foundry is to develop a family of interoperable ontologies that are both logically well-formed and scientifically accurate. To achieve this, OBO Foundry participants voluntarily adhere to and contribute to the development of an evolving set of principles including open use, collaborative development, non-overlapping and strictly-scoped content, and common syntax and relations, based on ontology models that work well, such as the Gene Ontology (GO). The OBO Foundry is overseen by an Operations Committee with Editorial, Technical and Outreach working groups.
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