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http://www.genscript.com/psort/wolf_psort.html

Data analysis service for protein subcellular localization prediction.

Proper citation: WoLF PSORT (RRID:SCR_002472) Copy   

•   Source: SciCrunch Registry

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://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://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://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://www.lfd.uci.edu/

Biomedical technology research center and training resource that develops novel fluorescence technologies, including instrumentation, methods and software applicable to cellular imaging and the elucidation of dynamic processes in cells. The LFD's main activities are: * Services and Resources: the LFD provides a state-of-the-art laboratory for fluorescence measurements, microscopy and spectroscopy, with technical assistance to visiting scientists. * Research and Development: the LFD designs, tests, and implements advances in the technology of hardware, software, and biomedical applications. * Training and Dissemination: the LFD disseminates knowledge of fluorescence spectroscopic principles, instrumentation, and applications to the scientific community.

Proper citation: Laboratory for Fluorescence Dynamics (RRID:SCR_001437) 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.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

https://github.com/hangelwen/miR-PREFeR

An accurate, fast, and easy-to-use plant miRNA prediction software tool using small RNA-Seq data. It utilizes expression patterns of miRNA and follows the criteria for plant microRNA annotation to accurately predict plant miRNAs from one or more small RNA-Seq data samples of the same species.

Proper citation: miR-PREFeR (RRID:SCR_003353) Copy   

•   Source: SciCrunch Registry

http://bioinformatics.psb.ugent.be/webtools/tapir/

Web server designed for prediction of plant microRNA targets.

Proper citation: TAPIR: target prediction for plant microRNAs (RRID:SCR_000237) Copy   

•   Source: SciCrunch Registry

http://www.i3crb.fr/

Project to improve data and sample exchanges and to facilitate large scale analysis of data by improving interoperability of French Biological Resources Centres (BRC or biobanks) IT systems and biological databases. The work done in this project will be linked to other national (IBiSA, ANR, R��seau des Biobanques, Club 3C-R), European (BBMRI, ELIXIR) or international project (P3G). In the preliminary phase (2009-2010) I3-CRB has developed a directory of French Biological Resource Centres / Biobanks where one may register their French BRC or perform a search across all of them. Detail by overall data or kingdom is provided as well as many filtering options. Access to biological samples is provided by the participating BRC''''s. Biological Resources Centres (BRC or biobanks) collect annotated biological samples from various sources (human, animal, plant, bacteria...). The type of samples depends on the collection and the associated thematic (DNA, proteins, cells, tissues, blood, serum, organisms...). The aims of these centers are to collect, to store, to transform and to distribute the biological samples. They constitute a vital infrastructure for life science and health research. Goals of the French Biobanks/Biological Resource Centres: * List French biobanks and their biological collections * Improve sample exchanges * Improve the international visibility of the French biological collections MeSH terms have been integrated: Domains, diseases, and location of the disease (Anatomy). Collections/species are based on NCBI Taxonomy.

Proper citation: I3-CRB: Interoperable IT Infrastructure for Biological Resources Centres / Biobanks - France (RRID:SCR_006991) Copy   

•   Source: SciCrunch Registry

http://www.brc.riken.jp/inf/en

RIKEN BRC contributes to advancement of life science research by collecting, preserving and distributing biological resources such as experimental animals, experimental plants, cultured cell lines, genetic materials (DNA), and associated bioinformatics. The RIKEN BRC develops novel bioresources to promote scientific research and new technologies to increase the value of bioresources, and also to implement effective procedures for the preservation, quality control and usage of bioresources. The RIKEN BRC is working closely with institutions in Japan and abroad.

Proper citation: RIKEN BioResource Center (RRID:SCR_003250) Copy   

•   Source: SciCrunch Registry

http://www.bnl.gov/medical/RCIBI/

Develop new scientific tools to image the movement of molecules in energy-relevant and environmentally-sensitive contexts in response to BER's call to explore the potential of radiotracer imaging in energy and environmentally-responsive contexts. Their goal is to visualize metabolic networks and regulatory systems underlying cellular communication in the living organism including plants and microbial communities. This has broad implications to DOE missions in energy and the environment and is very relevant to improvements in plant biomass for biofuel.

Proper citation: Radiotracer Chemistry Instrumentation and Biological Imaging (RRID:SCR_003258) 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://bioinfo.eie.polyu.edu.hk/mGoaSvmServer/mGOASVM.html

Data analysis service for the prediction of multi-label protein subcellular localization based on gene ontology and support vector machines. Web services are also available.

Proper citation: mGOASVM (RRID:SCR_013098) 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