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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
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
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
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
https://www.genevestigator.com/gv/
A high performance search engine for gene expression that integrates thousands of manually curated public microarray and RNAseq experiments and nicely visualizes gene expression across different biological contexts (diseases, drugs, tissues, cancers, genotypes, etc.). There are two basic analysis approaches: # for a gene of interest, identify which conditions affect its expression. # for condition(s) of interest, identify which genes are specifically expressed in this/these conditions. Genevestigator builds on the deep integration of data, both at the level of data normalization and on the level of sample annotations. This deep integration allows scientists to ask new types of questions that cannot be addressed using conventional tools.
Proper citation: Genevestigator (RRID:SCR_002358) Copy
Open source database of curated, non-redundant set of profiles derived from published collections of experimentally defined transcription factor binding sites for multicellular eukaryotes. Consists of open data access, non-redundancy and quality. JASPAR CORE is smaller set that is non-redundant and curated. Collection of transcription factor DNA-binding preferences, modeled as matrices. These can be converted into Position Weight Matrices (PWMs or PSSMs), used for scanning genomic sequences. Web interface for browsing, searching and subset selection, online sequence analysis utility and suite of programming tools for genome-wide and comparative genomic analysis of regulatory regions. New functions include clustering of matrix models by similarity, generation of random matrices by sampling from selected sets of existing models and a language-independent Web Service applications programming interface for matrix retrieval.
Proper citation: JASPAR (RRID:SCR_003030) Copy
An open web-accessible resource for gene functional annotations in the plant sciences to facilitate improvement, consolidation and visualization of gene annotations across several plant species. It is based on the MapMan ontology, organized in the form of a hierarchical tree of biological concepts, which describe gene functions. Currently, genes of the model species Arabidopsis, potato, tomato, rice, and tobacco are included. The main features are (i) dynamic and interactive gene product annotation through various curation options; (ii) consolidation of gene annotations for different plant species through the integration of orthologue group information; (iii) traceability of gene ontology changes and annotations; (iv) integration of external knowledge about genes from different public resources; and (v) providing gathered information to high-throughput analysis tools via dynamically generated export files. All of the GoMapMan functionalities are openly available, with the restriction on the curation functions, which require prior registration to ensure traceability of the implemented changes.
Proper citation: GoMapMan (RRID:SCR_005060) Copy
Not yet vetted by NIF curator
Proper citation: Global Crop Diversity Trust (RRID:SCR_010658) Copy
http://jci-bioinfo.cn/iLoc-Plant
Data analysis service for predicting subcellular localization of plant proteins with single and multiple sites.
Proper citation: iLoc-Plant (RRID:SCR_011973) Copy
http://gpcr.biocomp.unibo.it/bacello/
A predictor for the subcellular localization of proteins in eukaryotes that is based on a decision tree of several support vector machines (SVMs). It classifies up to four localizations for Fungi and Metazoan proteins and five localizations for Plant ones. BaCelLo's predictions are balanced among different classes and all the localizations are considered as equiprobable.
Proper citation: BaCelLo (RRID:SCR_011965) Copy
http://www.csbio.sjtu.edu.cn/bioinf/Cell-PLoc/
A package of web-servers for predicting subcellular localization of proteins in different organisms.
Proper citation: Cell-PLoc (RRID:SCR_011966) Copy
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
http://www.regjeringen.no/en/dep/lmd/campain/svalbard-global-seed-vault.html?id=462220
Secure seed bank on the Norwegian island of Spitsbergen in remote Arctic Svalbard archipelago to preserve wide variety of plant seeds that are duplicate samples, or "spare" copies, of seeds held in gene banks worldwide. The seed vault is attempt to ensure against loss of seeds in other genebanks during large-scale regional or global crises.
Proper citation: Svalbard Global Seed Vault (RRID:SCR_010706) Copy
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