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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

http://webdocs.cs.ualberta.ca/~bioinfo/PA/Sub/

Web server specialized to predict the subcellular localization of proteins using established machine learning techniques.

Proper citation: Proteome Analyst Specialized Subcellular Localization Server (RRID:SCR_003143) 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://bis.zju.edu.cn/pnatdb/

Natural Antisense Transcripts (NATs), a kind of regulatory RNAs, occur prevalently in plant genomes and play significant roles in physiological and/or pathological processes. PlantNATsDB (Plant Natural Antisense Transcripts DataBase) is a platform for annotating and discovering NATs by integrating various data sources involving approximately 2 million NAT pairs in 69 plant species. PlantNATsDB also provides an integrative, interactive and information-rich web graphical interface to display multidimensional data, and facilitate plant research community and the discovery of functional NATs. GO annotation and high-throughput small RNA sequencing data currently available were integrated to investigate the biological function of NATs. A ''''Gene Set Analysis'''' module based on GO annotation was designed to dig out the statistical significantly overrepresented GO categories from the specific NAT network. PlantNATsDB is currently the most comprehensive resource of NATs in the plant kingdom, which can serve as a reference database to investigate the regulatory function of NATs.

Proper citation: PlantNATsDB - Plant Natural Antisense Transcripts DataBase (RRID:SCR_013278) 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.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.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.croptrust.org/main/

Not yet vetted by NIF curator

Proper citation: Israel Plant Gene Bank (RRID:SCR_008718) 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://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://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.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://www.gramene.org

Curated, open-source, integrated data resource for comparative functional genomics in crops and model plant species to facilitate the study of cross-species comparisons using information generated from projects supported by public funds. It currently hosts annotated whole genomes in over two dozen plant species and partial assemblies for almost a dozen wild rice species in the Ensembl browser, genetic and physical maps with genes, ESTs and QTLs locations, genetic diversity data sets, structure-function analysis of proteins, plant pathways databases (BioCyc and Plant Reactome platforms), and descriptions of phenotypic traits and mutations. The web-based displays for phenotypes include the Genes and Quantitative Trait Loci (QTL) modules. Sequence based relationships are displayed in the Genomes module using the genome browser adapted from Ensembl, in the Maps module using the comparative map viewer (CMap) from GMOD, and in the Proteins module displays. BLAST is used to search for similar sequences. Literature supporting all the above data is organized in the Literature database. In addition, Gramene now hosts a variety of web services including a Distributed Annotation Server (DAS), BLAST and a public MySQL database. Twice a year, Gramene releases a major build of the database and makes interim releases to correct errors or to make important updates to software and/or data. Additionally you can access Gramene through an FTP site.

Proper citation: Gramene (RRID:SCR_002829) 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://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://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://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://www.ariadnegenomics.com/products/databases/resnet/

Databases that represent sets of pre-compiled information on biological relationships and associations, interactions and facts which have been extracted from the biomedical literature using Ariadne's MedScan technology. ResNet databases store information harvested from the entire PubMed in a formal structure that allows searching, retrieval and updating by Pathway Studio user. ResNet is seamlessly installed when Pathway Studio is installed. There are several available ResNet databases: *ResNet Mammalian Database includes data for Human, Rat, and Mouse *ResNet Plant Database has data on Arabidopsis, Rice and several other plants. Features of ResNet: *All extracted relations have linked access to the original article or abstract *Synonyms and homologs are included to maintain gene identity and to obviate redundancy in search results *Users can update ResNet as often as required using the MedScan technology built into all Ariadne products *Updates are made available by Ariadne every quarter To purchase Pathway Studio software with ResNet database, for information, or to schedule a web demonstration, call our sales department at (240) 453-6272, or (866) 340-5040 (toll free)., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: RESNET (RRID:SCR_002121) Copy   

•   Source: SciCrunch Registry

http://www.ncbi.nlm.nih.gov/mapview/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 4, 2023. Database that provides special browsing capabilities for a subset of organisms in Entrez Genomes. Map Viewer allows users to view and search an organism's complete genome, display chromosome maps, and zoom into progressively greater levels of detail, down to the sequence data for a region of interest. If multiple maps are available for a chromosome, it displays them aligned to each other based on shared marker and gene names, and, for the sequence maps, based on a common sequence coordinate system.

Proper citation: MapViewer (RRID:SCR_003092) Copy   

•   Source: SciCrunch Registry