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https://plantcyc.org/content/plantcyc-15.2.0

Multi species reference database. Comprehensive plant biochemical pathway database, containing curated information from literature and computational analyses about genes, enzymes, compounds, reactions, and pathways involved in primary and secondary metabolism.

Proper citation: PlantCyc (RRID:SCR_002110) Copy   

•   Source: SciCrunch Registry

http://genome.unmc.edu/ngLOC/index.html

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 5, 2023.An n-gram-based Bayesian classifier that predicts subcellular localization of proteins both in prokaryotes and eukaryotes. The downloadable version of this software with source code is freely available for academic use under the GNU General Public License.

Proper citation: ngLOC (RRID:SCR_003150) Copy   

•   Source: SciCrunch Registry

http://gbrowse.org/

A database and interactive web site for manipulating and displaying annotations on genomes. Features include: detailed views of the genome; use of a variety of premade or personally made glyphs ; customizable order and appearance of tracks by administrators and end-users; search by annotation ID, name, or comment; support of third party annotation using GFF formats; DNA and GFF dumps; connectivity to different databases, including BioSQL and Chado; and a customizable plug-in architecture (e.g. run BLAST, find oligonucleotides, design primers, etc.). GBrowse is distributed as source code for Macintosh OS X, UNIX and Linux platforms, and as pre-packaged binaries for Windows machines. It can be installed using the standard Perl module build procedure, or automated using a network-based install script. In order to use the net installer, you will need to have Perl 5.8.6 or higher and the Apache web server installed. The wiki portion accepts data submissions.

Proper citation: GBrowse (RRID:SCR_006829) Copy   

•   Source: SciCrunch Registry

http://www.btool.org/WegoLoc

Data analysis service that predicts protein subcellular localizations of animal, fungal, plant, and human proteins based on sequence similarity and gene ontology information.

Proper citation: WegoLoc (RRID:SCR_001402) Copy   

•   Source: SciCrunch Registry

http://solgenomics.net/

A clade oriented, community curated database containing genomic, genetic, phenotypic and taxonomic information for plant genomes. Genomic information is presented in a comparative format and tied to important plant model species such as Arabidopsis. SGN provides tools such as: BLAST searches, the SolCyc biochemical pathways database, a CAPS experiment designer, an intron detection tool, an advanced Alignment Analyzer, and a browser for phylogenetic trees. The SGN code and database are developed as an open source project, and is based on database schemas developed by the GMOD project and SGN-specific extensions.

Proper citation: SGN (RRID:SCR_004933) Copy   

•   Source: SciCrunch Registry

http://www.ala.org.au/

Online repository of information about Australian plants, animals, and fungi. Development started in 2006. The Commonwealth Scientific and Industrial Research Organisation is organisation significantly involved in development of ALA.

Proper citation: Atlas of Living Australia (RRID:SCR_006467) Copy   

•   Source: SciCrunch Registry

http://www.croptrust.org/main/

Not yet vetted by NIF curator

Proper citation: Israel Plant Gene Bank (RRID:SCR_008718) Copy   

•   Source: SciCrunch Registry

http://www.nordgen.org/index.php/en/content/view/full/467

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on May 18,2023.

Proper citation: Nordic Genetic Resource Centre (Plants) (RRID:SCR_010529) Copy   

•   Source: SciCrunch Registry

http://www.accdc.com/

Comprehensive lists of plant and animal species, with a rarity rank and legal status for each. It has has over 635,000 geo-located records of species occurrences and over 40,000 records of extremely rare to uncommon species in the Atlantic region, including New Brunswick, Nova Scotia, Prince Edward Island, Newfoundland, and Labrador. The Atlantic CDC also maintains biological and other types of data in a variety of linked databases. The CDC welcomes inquiries from those who would like to contribute data about plant or animal species at risk or rare communities in Atlantic Canada. Its mission is to assemble and provide objective and understandable data and expertise about species and ecological communities of conservation concern, including those at risk, and undertake field biological inventories to support decision-making, research, and education in Atlantic Canada. The Atlantic CDC develops species location data, known as element occurrence records. Occurrence precision (accuracy) ranges from quite precise (within meters) to less precise (within counties) but most commonly it is within 1 5 km. Element occurrence (EO) refers to one or more locations considered important to the continued existence of a species or ecological community. For species, over 30 types of data: taxonomy, biology, etc. are typically examined when identifying EOs. An EO is generally the habitat occupied by a local population. However, occurrence varies among species and some species have more than one type of occurrence (e.g., breeding and winter occurrences). Breeding colonies, breeding ponds, denning sites, and hibernacula are general examples of different types of animal EOs. For an ecological community, an EO may be the area containing a patch of that community type.

Proper citation: Atlantic Canada Conservation Data Centre (RRID:SCR_006061) Copy   

•   Source: SciCrunch Registry

http://organelledb.lsi.umich.edu/

Database of organelle proteins, and subcellular structures / complexes from compiled protein localization data from organisms spanning the eukaryotic kingdom. All data may be downloaded as a tab-delimited text file and new localization data (and localization images, etc) for any organism relevant to the data sets currently contained in Organelle DB is welcomed. The data sets in Organelle DB encompass 138 organisms with emphasis on the major model systems: S. cerevisiae, A. thaliana, D. melanogaster, C. elegans, M. musculus, and human proteins as well. In particular, Organelle DB is a central repository of yeast protein localization data, incorporating results from both previous and current (ongoing) large-scale studies of protein localization in Saccharomyces cerevisiae. In addition, we have manually curated several recent subcellular proteomic studies for incorporation in Organelle DB. In total, Organelle DB is a singular resource consolidating our knowledge of the protein composition of eukaryotic organelles and subcellular structures. When available, we have included terms from the Gene Ontologies: the cellular component, molecular function, and biological process fields are discussed more fully in GO. Additionally, when available, we have included fluorescent micrographs (principally of yeast cells) visualizing the described protein localization. Organelle View is a visualization tool for yeast protein localization. It is a visually engaging way for high school and undergraduate students to learn about genetics or for visually-inclined researchers to explore Organelle DB. By revealing the data through a colorful, dimensional model, we believe that different kinds of information will come to light.

Proper citation: Organelle DB (RRID:SCR_007837) Copy   

•   Source: SciCrunch Registry

http://bar.utoronto.ca/welcome.htm

Web-based tools for working with functional genomics and other data, including Gene Expression and Protein Tools, Molecular Markers and Mapping Tools, and Other Genomic Tools. Most are designed with the plant (mainly Arabidopsis) researcher in mind, but a couple of them can be useful to the wider research community, e.g. Mouse eFP Browser or BlastDigester. The associated paper for most tools is available.

Proper citation: BAR (RRID:SCR_006748) Copy   

•   Source: SciCrunch Registry

http://goblet.molgen.mpg.de/cgi-bin/goblet2008/goblet.cgi

Tool that performs annotation based on GO and pathway terms for anonymous cDNA or protein sequences. It uses the species independent GO structure and vocabulary together with a series of protein databases collected from various sites, to perform a detailed GO annotation by sequence similarity searches. The sensitivity and the reference protein sets can be selected by the user. GOblet runs automatically and is available as a public service on our web server. GOblet expects query sequences to be in FASTA-Format (with header-lines). Protein and nucleotide sequences are accepted. Total size of all sequences submitted per request should not be larger than 50kb currently. For security reasons: Larger post's will be rejected. Due to limited capacities the queries may be processed in batches depending on the server load. The output of the BLAST job is filtered automatically and the relevant hits are displayed. In addition, the respective GO-terms are shown together with the complete GO-hierarchy of parent terms., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: GOblet (RRID:SCR_006998) Copy   

•   Source: SciCrunch Registry

http://aps.unmc.edu/AP/main.php

Database and data analysis system dedicated to glossary, nomenclature, classification, information search, prediction, design, and statistics of Antimicrobial peptides and beyond. The peptide data stored in the APD were gleaned from the literature (PubMed, PDB, Google, and Swiss-Prot) manually in the past several years. Peptides will be registered into this database if: # they are from natural sources (bacteria, protozoa, fungi, plants, and animals); # their antimicrobial activities are demonstrated (MIC

Proper citation: APD (RRID:SCR_006606) Copy   

•   Source: SciCrunch Registry

http://purl.bioontology.org/ontology/CO

Ontology that includes crop-specific trait ontologies for several economically important plants like rice, wheat, maize, potato, musa, chickpea and sorghum along with other important domains for crop research such as germplasm, passport, trait measurement scales, experimental design factors etc.

Proper citation: Crop Ontology (RRID:SCR_010299) Copy   

•   Source: SciCrunch Registry

http://purl.bioontology.org/ontology/PAE

THIS RESOURCES IS NO LONGER IN SERVICE, documented on April 23, 2014. REPLACED BY: Plant Ontology (PO). A controlled vocabulary of plant morphological and anatomical structures representing organs, tissues, cell types, and their biological relationships based on spatial and developmental organization. Note that this has been subsumed into the PO. This file is created by filtering plant_ontology_assert.obo to contain only terms from the plant anatomical entity branch of the PO. For more information, please see: http://palea.cgrb.oregonstate.edu/viewsvn/Poc/tags/live/

Proper citation: Plant Anatomy (RRID:SCR_010408) Copy   

•   Source: SciCrunch Registry

http://www.cropscience.bayer.com/

Crop science company with products in crop protection and nonagricultural pest control. It also has activities in seeds and plant traits. (Adapted from Wikipedia)

Proper citation: Bayer CropScience (RRID:SCR_010498) Copy   

•   Source: SciCrunch Registry

http://www3a.biotec.or.th/c-mii/

A software tool for plant miRNA and target identification. C-mii pipelines are based on combined steps and criteria from previous studies and also incorporated with several tools such as standalone BLAST and UNAFold and pre-installed databases including miRBase, UniProt, and Rfam. C-mii provides following distinguished features. First, it comes with graphical user interfaces of well-defined pipelines for both miRNA and target identifications with reliable results. Second, it provides a set of filters allowing users to reduce the number of results corresponding to the recently proposed constraints in plant miRNA and target biogenesis. Third, it extends the standard computational steps of miRNA target identification with miRNA-target folding module and GO annotation. Fourth, it supplies the bird eye views of the identification results with info-graphics and grouping information. Fifth, it provides helper functions for database update and auto-recovery to ease system usage and maintenance. Finally, it supports the multi-project and multi-thread management to improve the computational speed.

Proper citation: C-mii (RRID:SCR_010839) Copy   

•   Source: SciCrunch Registry

http://pmted.agrinome.org/

A Plant MicroRNA Target Expression Database to study the microRNA (miRNA) functions by inferring their target gene expression profiles among the large amount of existing microarray data. You may also predict your miRNA targets and retrieve their microarray expression data.

Proper citation: PMTED (RRID:SCR_010854) Copy   

•   Source: SciCrunch Registry

http://plntfdb.bio.uni-potsdam.de

Public database arising from efforts to identify and catalogue all plant genes involved in transcriptional control.Integrative plant transcription factor database that provides web interface to access large sets of transcription factors of several plant species, currently encompassing Arabidopsis thaliana (thale cress), Populus trichocarpa (poplar), Oryza sativa (rice), Chlamydomonas reinhardtii and Ostreococcus tauri. Provides access point to its daughter databases of species-centered representation of transcription factors (OstreoTFDB, ChlamyTFDB, ArabTFDB, PoplarTFDB and RiceTFDB). Information including protein sequences, coding regions, genomic sequences, expressed sequence tags, domain architecture and scientific literature is provided for each family.

Proper citation: PlnTFDB (RRID:SCR_010899) Copy   

•   Source: SciCrunch Registry

http://ahd.cbi.pku.edu.cn

Database providing a systematic and comprehensive view of morphological phenotypes regulated by plant hormones, as well as regulatory genes participating in numerous plant hormone responses. By integrating the data from mutant studies, transgenic analysis and gene ontology annotation, genes related to the stimulus of eight plant hormones were identified, including abscisic acid, auxin, brassinosteroid, cytokinin, ethylene, gibberellin, jasmonic acid and salicylic acid. Another pronounced characteristics of this database is that a phenotype ontology was developed to precisely describe all kinds of morphological processes regulated by plant hormones with standardized vocabularies. To increase the coverage of phytohormone related genes, the database has been updated from AHD to AHD2.0 adding and integrating several pronounced features: (1) added 291 newly published Arabidopsis hormone related genes as well as corrected information (e.g. the arguable ABA receptors) based on the recent 2-year literature; (2) integrated orthologues of sequenced plants in OrthoMCLDB into each gene in the database; (3) integrated predicted miRNA splicing site in each gene in the database; (4) provided genetic relationship of these phytohormone related genes mining from literature, which represents the first effort to construct a relatively comprehensive and complex network of hormone related genes as shown in the home page of our database; (5) In convenience to in-time bioinformatics analysis, they also provided links to a powerful online analysis platform Weblab that they have recently developed, which will allow users to readily perform various sequence analysis with these phytohormone related genes retrieved from AHD2.0; (6) provided links to other protein databases as well as more expression profiling information that would facilitate users for a more systematic analysis related to phytohormone research. Please help to improve the database with your contributions.

Proper citation: Arabidopsis Hormone Database (RRID:SCR_001792) Copy   

•   Source: SciCrunch Registry