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SciCrunch Registry is a curated repository of scientific resources, with a focus on biomedical resources, including tools, databases, and core facilities - visit SciCrunch to register your resource.

(last updated: Sep 3, 2019)

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Resource NameResource TypeDescriptionKeywordsResource IDProper CitationParent OrganizationRelated ConditionFunding AgencyRelationReferenceWebsite StatusAlternate IDsAlternate URLsOld URLs
ImpactStoryResource, software resource, source code, service resource, production service resourceA web application which provides altmetrics to help researchers measure and share the impacts of their research outputs. After making a profile, scientists can track which of their publications are most popular through number of citations, frequency of PDF downloads, etc. Information from research outputs such as journal articles, blog posts, datasets, and software contribute to a user's impact, which is viewable in their profile.altmetrics, metric, citeulike, crossref, scienceseeker, scopus, slideshare, topsy, twitter, vimeo, wordpress.com, plos, youtubeSCR_002632(ImpactStory, RRID:SCR_002632)Alfred P. Sloan Foundation, NSF, Open Society Foundationrelated to: PubMed, GitHub, FigShare, Dryad, Wikipedia, Mendeley, used by: Publons, listed by: FORCE11, Connected Researchers, PLOS Article-Level MetricsLast checked downnlx_156056
PAMGOResource, ontology, data or information resource, controlled vocabularyTHIS RESOURCE IS NO LONGER IN SERVICE, documented on June 10, 2016. A consortium that created universal descriptors to describe functionally similar gene products and their attributes across all organisms. In 2004, the PAMGO interest group joined the GO consortium to extend the GO to include terms describing various processes related to microbe-host interactions. The organization uses a controlled vocabulary to set a process in place to describe plant associated microbes and their interactions with their plant-hosts. These higher order terms can describe gene products of all types of symbionts (e.g. parasites, commensals, and mutualists), including prokaryotes and eukaryotes that associate with plant or animal hosts. This initiative is a multi-institutional collaborative effort to pool information and research in: the bacteria Dickeya dadantii, Pseudomonas syringae pv tomato and Agrobacterium tumefaciens, the fungus Magnaporthe grisea, the oomycetes Phytophthora sojae and Phytophthora ramorum, and the nematode Meloidogyne hapla.ontology, plant ontology, microbe-host, controlled vocabulary, symbiosis, parasite, mutualist, commensalSCR_000022(PAMGO, RRID:SCR_000022)Virginia Polytechnic Institute and State University; Virginia; USA NSFaffiliated with: Cornell University, New York, USA, North Carolina State University, North Carolina, USA, University of Wisconsin-Madison, Wisconsin, USA, Virginia Bioinformatics InstituteLast checked downnlx_92278
LONI Visualization ToolResource, data visualization software, software application, data processing software, software resourceA versatile 1D, 2D and 3D data viewer geared for cross-platform visualization of stereotactic brain data. It is a 3-D viewer that allows volumetric data display and manipulation of axial, sagittal and coronal views. It reads Analyze, Raw-binary and NetCDF volumetric data, as well as, Multi-Contour Files (MCF), LWO/LWS surfaces, atlas hierarchical brain-region labelings ( Brain Trees). It is a portable Java-based software, which only requires a Java interpreter and a 64 MB of RAM memory to run on any computer architecture. LONI_Viz allows the user to interactively overlay and browse through several data volumes, zoom in and out in the axial, sagittal and coronal views, and reports the intensities and the stereo-tactic voxel and world coordinates of the data. Expert users can use LONI_Viz to delineate structures of interest, e.g., sulcal curves, on the 3 cardinal projections of the data. These curves then may be use to reconstruct surfaces representing the topological boundaries of cortical and sub-cortical regions of interest. The 3D features of the package include a SurfaceViewer and a full real-time VolumeRenderer. These allow the user to view the relative positions of different anatomical or functional regions which are not co-planar in any of the axial, sagittal or coronal 2D projection planes. The interactive part of LONI_Viz features a region drawing module used for manual delineation of regions of interest. A series of 2D contours describing the boundary of a region in projection planes (axial, sagittal or coronal) could be used to reconstruct the surface-representation of the 3D outer shell of the region. The latter could then be resliced in directions complementary to the drawing-direction and these complementary contours could be loaded in all tree cardinal views. In addition the surface object could be displayed using the SurfaceViewer. A pre-loading data crop and sub-sampling module allows the user to load and view practically data of any size. This is especially important when viewing cryotome, histological or stained data-sets which may reach 1GB (109 bytes) in size. The user could overlay several pre-registered volumes, change intensity colors and ranges and the inter-volume opacities to visually inspect similarities and differences between the different subjects/modalities. Several image-processing aids provide histogram plotting, image-smoothing, etc. Specific Features: * Region description DataBase * Moleculo-genetic database * Brain anatomical data viewer * BrainMapper tool * Surface (LightWave objects/scenes) and Volume rendering tools * Interactive Contour Drawing tool Implementation Issues: * Applet vs. Application - the software is available as both an applet and a standalone application. The former could be used to browse data from within the LONI database, however, it imposes restrictions on file-size, Internet connection and network-bandwidth and client/server file access. The later requires a local install and configuration of the LONI_Viz software * Extendable object-oriented code (Java), computer architecture independent * Complete online software documentation is available at http://www.loni.ucla.edu/LONI_Viz and a Java-Class documentation is available at http://www.loni.ucla.edu/~dinov/LONI_Vis.dir/doc/LONI_Viz_Java_Docs.htmlbrain, atlas, visualization, gene mapping, atlas application, magnetic resonance, surface analysisSCR_000765(LONI Visualization Tool, RRID:SCR_000765)Laboratory of Neuro Imaging AgingNCRR, NIA, NIMH, NLM, NSFlisted by: NeuroImaging Tools and Resources Collaboratory (NITRC), BiositemapsPMID:16598642Last checked downnif-0000-23313http://www.nitrc.org/projects/incf_loni-vizhttp://www.loni.ucla.edu/Software/LOVE
Genes to Cognition - Biological ResourcesResource, biomaterial supply resource, material resource, organism supplierBiological resources, including gene-targeting vectors, ES cell lines, antibodies, and transgenic mice, generated for its phenotyping pipeline as part of the Genes to Cognition research program are freely-available to interested researchers. Available Transgenic Mouse Lines: *Hras1 (H-ras) knockout,C57BL/6J *Dlg4 (PSD-95) knockout,129S5 *Dlg4 (PSD-95) knockout,C57BL/6J *Dlg3 (SAP102) knockout with hprt mutation,129S5 *Dlg3 (SAP102) knockout (wild-type for hprt,C57BL/6J *Syngap1 (SynGAP) knockout (from 8.24 clone), C57BL/6J *Dlg4 (PSD-95) guanylate kinase domain deletion, C57BL/6J *Ptk2 (FAK) knockout,C57BL/6Jtransgenic, mutant mouse strain, c57bl/6j, 129s5, transgenic mouse line, vector, es cell line, transgenic mouseSCR_001675(Genes to Cognition - Biological Resources, RRID:SCR_001675)University of Edinburgh; Scotland; United Kingdom BBSRC, EPSRC, European Union, Framework Programme, Gatsby Charitable Foundation, Human Frontiers Science Programme, MRC, NSF, Wellcome Trustlisted by: One Mind Biospecimen Bank ListingLast checked downnif-0000-10163http://www.genes2cognition.org/mice_resources/http://www.genes2cognition.org/resources.html
National Center for Earth-Surface DynamicsResource, service resource, data or information resource, data repository, storage service resource, databaseField, laboratory, and model data related to earth-surface dynamics created or compiled by NCED-funded scientists. NCED is a Science and Technology Center developed to predict the coupled dynamics and co-evolution of landscapes and their ecosystems in order to transform management and restoration of the Earth-surface environment.landscape, ecosystem, data setSCR_002195(National Center for Earth-Surface Dynamics, RRID:SCR_002195)University of Minnesota Twin Cities; Minnesota; USA NSFlisted by: CINERGILast checked downnlx_154715
VS-LiteResource, software resourceA simple, efficient, process-based forward model of tree-ring growth, requires as inputs only latitude and monthly temperature and precipitation.model, mathematical model, tree ring, dendrochronology, tree ring width, tree, ring, ring growth modelSCR_002431(VS-Lite, RRID:SCR_002431)World Data Center for Paleoclimatology NOAA, NSFlisted by: CINERGILast checked downSciRes_000128
Genes to Cognition DatabaseResource, data or information resource, databaseDatabase of protein complexes, protocols, mouse lines, and other research products generated from the Genes to Cognition project, a project focused on understanding molecular complexes involved in synaptic transmission in the brain.allele, gene list, mouse line, human disease, phenotyping, plasticity, behavior, proteonomics, brain, cognition, cognition disorder, learning, memory, neuroscience, experimental protocol, synapse proteomics, synapseSCR_002735(Genes to Cognition Database, RRID:SCR_002735)BBSRC, EPSRC, European Union, Framework Programme, Gatsby Charitable Foundation, Human Frontiers Science Programme, MRC, NSF, Wellcome TrustLast checked downnif-0000-02864http://www.genes2cognition.org/cgi-bin/SearchView
SumsDBResource, data analysis service, database, analysis service resource, production service resource, service resource, storage service resource, atlas, image repository, data repository, data or information resourceTHIS RESOURCE IS NO LONGER IN SERVICE, documented on May 11, 2016. Repository of brain-mapping data (surfaces and volumes; structural and functional data) derived from studies including fMRI and MRI from many laboratories, providing convenient access to a growing body of neuroimaging and related data. WebCaret is an online visualization tool for viewing SumsDB datasets. SumsDB includes: * data on cerebral cortex and cerebellar cortex * individual subject data and population data mapped to atlases * data from FreeSurfer and other brainmapping software besides Caret SumsDB provides multiple levels of data access and security: * Free (public) access (e.g., for data associated with published studies) * Data access restricted to collaborators in different laboratories * Owner-only access for work in progress Data can be downloaded from SumsDB as individual files or as bundles archived for offline visualization and analysis in Caret WebCaret provides online Caret-style visualization while circumventing software and data downloads. It is a server-side application running on a linux cluster at Washington University. WebCaret "scenes" facilitate rapid visualization of complex combinations of data Bi-directional links between online publications and WebCaret/SumsDB provide: * Links from figures in online journal article to corresponding scenes in WebCaret * Links from metadata in WebCaret directly to relevant online publications and figuressegmentation, volume, neuroimaging, brain, fmri, stereotaxic foci, stereotaxic coordinate, brain-mapping, foci, structural mri, mri, cerebral cortex, cerebellar cortex, afni brik, analyze, atlas, nifti, registration, rendering, spatial transformation, surface analysis, surface rendering, visualization, volume rendering, brain mapping, neuroanatomySCR_002759(SumsDB, RRID:SCR_002759)Washington University School of Medicine in St. Louis; Missouri; USA Mental disease, Neurological disorder, NormalHuman Brain Project, NASA, National Partnership for Advanced Computational Infrastructure, NCI, NIMH, NLM, NSFrelated to: Computerized Anatomical Reconstruction and Editing Toolkit, Integrated Manually Extracted Annotation, used by: NIF Data Federation, listed by: Biositemaps, NeuroImaging Tools and Resources Collaboratory (NITRC), re3data.orgLast checked downnif-0000-00016http://brainvis.wustl.edu/wiki/index.php/Sums:About http://www.nitrc.org/projects/sumsdb
Mutation Annotation and Genomic InterpretationResource, analysis service resource, data analysis service, service resource, production service resourceA tool for annotating, exploring, and analyzing gene sets that may be associated with cancer.mutation, interaction, transcript, copy number aberration, networkSCR_002800(Mutation Annotation and Genomic Interpretation, RRID:SCR_002800)Brown University; Rhode Island; USA CancerBrown University; Rhode Island; USA, NIH, NSFuses: The Cancer Genome Atlas, HINT, HPRD - Human Protein Reference Database, Pfam, SMART, Conserved Domain Database, listed by: OMICtoolsLast checked downOMICS_06145
Fungal Genome InitiativeResource, data set, data or information resourceProduces and analyzes sequence data from fungal organisms that are important to medicine, agriculture and industry. The FGI is a partnership between the Broad Institute and the wider fungal research community, with the selection of target genomes governed by a steering committee of fungal scientists. Organisms are selected for sequencing as part of a cohesive strategy that considers the value of data from each organism, given their role in basic research, health, agriculture and industry, as well as their value in comparative genomics.sequence, fungi, gene annotation, genomeSCR_003169(Fungal Genome Initiative, RRID:SCR_003169)Broad Institute NHGRI, NIAID, NSF, USDAlisted by: 3DVCLast checked downnif-0000-30591
Hymenoptera Anatomy OntologyResource, ontology, data or information resource, controlled vocabularyA structured controlled vocabulary of the anatomy of the Hymenoptera (bees, wasps, sawflies and ants)owl, anatomy, organismalSCR_003340(Hymenoptera Anatomy Ontology, RRID:SCR_003340)NSFlisted by: BioPortal, OBOLast checked downnlx_157435http://purl.bioontology.org/ontology/HAO, http://purl.obolibrary.org/obo/hao.owl
Datasharing.netResource, topical portal, portal, data or information resourceThe U.S. National Institutes of Health Final NIH Statement on Sharing Research Data (NIH-OD-03-032) is now in effect. It specifies that all high-direct-cost NIH grant applications include plans for sharing of research data. To support and encourage collegial, enabling, and rewarding data sharing for neuroscience and beyond, the Laboratory of Neuroinformatics at Weill Medical College of Cornell University has established this site. A source of, and portal to, tools and proposals supporting the informed exchange of neuroscience data.data management, neuroinformatics, data sharingSCR_003312(Datasharing.net, RRID:SCR_003312)Weill Cornell Medical College; New York; USA Human Brain Project, NIMH, NINDS, NSFLast checked downnif-0000-00061
PIRSFResource, narrative resource, database, standard specification, data or information resourceA SuperFamily classification system, with rules for functional site and protein name, to facilitate the sensible propagation and standardization of protein annotation and the systematic detection of annotation errors. The PIRSF concept is being used as a guiding principle to provide comprehensive and non-overlapping clustering of UniProtKB sequences into a hierarchical order to reflect their evolutionary relationships. The PIRSF classification system is based on whole proteins rather than on the component domains; therefore, it allows annotation of generic biochemical and specific biological functions, as well as classification of proteins without well-defined domains. There are different PIRSF classification levels. The primary level is the homeomorphic family, whose members are both homologous (evolved from a common ancestor) and homeomorphic (sharing full-length sequence similarity and a common domain architecture). At a lower level are the subfamilies which are clusters representing functional specialization and/or domain architecture variation within the family. Above the homeomorphic level there may be parent superfamilies that connect distantly related families and orphan proteins based on common domains. Because proteins can belong to more than one domain superfamily, the PIRSF structure is formally a network. The FTP site provides free download for PIRSF.protein annotation, classification, protein, superfamily, functional site, protein nameSCR_003352(PIRSF, RRID:SCR_003352)PIR NHGRI, NSFrelated to: UniProtKB, listed by: OMICtoolsReferences (2)Last checked downnif-0000-03294, OMICS_01697http://pir.georgetown.edu/pirsf/
ASAP: the Alternative Splicing Annotation ProjectResource, data or information resource, databaseTHIS RESOURCE IS NO LONGER IN SERVICE, documented on 8/12/13. Database to access and mine alternative splicing information coming from genomics and proteomics based on genome-wide analyses of alternative splicing in human (30 793 alternative splice relationships found) from detailed alignment of expressed sequences onto the genomic sequence. ASAP provides precise gene exon-intron structure, alternative splicing, tissue specificity of alternative splice forms, and protein isoform sequences resulting from alternative splicing. They developed an automated method for discovering human tissue-specific regulation of alternative splicing through a genome-wide analysis of expressed sequence tags (ESTs), which involves classifying human EST libraries according to tissue categories and Bayesian statistical analysis. They use the UniGene clusters of human Expressed Sequence Tags (ESTs) to identify splices. The UniGene EST's are clustered so that a single cluster roughly corresponds to a gene (or at least a part of a gene). A single EST represents a portion of a processed (already spliced) mRNA. A given cluster contains many ESTs, each representing an outcome of a series of splicing events. The ESTs in UniGene contain the different mRNA isoforms transcribed from an alternatively spliced gene. They are not predicting alternative splicing, but locating it based on EST analysis. The discovered splices are further analyzed to determine alternative splicing events. They have identified 6201 alternative splice relationships in human genes, through a genome-wide analysis of expressed sequence tags (ESTs). Starting with 2.1 million human mRNA and EST sequences, they mapped expressed sequences onto the draft human genome sequence and only accepted splices that obeyed the standard splice site consensus. After constructing a tissue list of 46 human tissues with 2 million human ESTs, they generated a database of novel human alternative splices that is four times larger than our previous report, and used Bayesian statistics to compare the relative abundance of every pair of alternative splices in these tissues. Using several statistical criteria for tissue specificity, they have identified 667 tissue-specific alternative splicing relationships and analyzed their distribution in human tissues. They have validated our results by comparison with independent studies. This genome-wide analysis of tissue specificity of alternative splicing will provide a useful resource to study the tissue-specific functions of transcripts and the association of tissue-specific variants with human diseases.gene, genome, human, isoform, mechanism, metazoa, molecular, mrna, nucleus, process, protein, sequence, splice, tissue specificity, transcription, transcript, alternate splicing, microarray, alternative splicing, biological process, alternatively spliced isoform, contig, cancer, imageSCR_003415(ASAP: the Alternative Splicing Annotation Project, RRID:SCR_003415)University of California at Los Angeles; California; USA DOE, NSFrelated to: Alternative Splicing Annotation Project II Database, listed by: BiositemapsPMID:12519958Last checked downnif-0000-33105
bioPIXIEResource, analysis service resource, data analysis service, service resource, production service resourcebioPIXIE is a general system for discovery of biological networks through integration of diverse genome-wide functional data. This novel system for biological data integration and visualization, allows you to discover interaction networks and pathways in which your gene(s) (e.g. BNI1, YFL039C) of interest participate. The system is based on a Bayesian algorithm for identification of biological networks based on integrated diverse genomic data. To start using bioPIXIE, enter your genes of interest into the search box. You can use ORF names or aliases. If you enter multiple genes, they can be separated by commas or returns. Press ''submit''. bioPIXIE uses a probabilistic Bayesian algorithm to identify genes that are most likely to be in the same pathway/functional neighborhood as your genes of interest. It then displays biological network for the resulting genes as a graph. The nodes in the graph are genes (clicking on each node will bring up SGD page for that gene) and edges are interactions (clicking on each edge will show evidence used to predict this interaction). Most likely, the first results to load on the results page will be a list of significant Gene Ontology terms. This list is calculated for the genes in the biological network created by the bioPIXIE algorithm. If a gene ontology term appears on this list with a low p-value, it is statistically significantly overrepresented in this biological network. As you move the mouse over genes in the network, interactions involving these genes are highlighted. If you click on any of the highlighted interactions graph, evidence pop-up window will appear. The Evidence pop-up lists all evidence for this interaction, with links to the papers that produced this evidence - clicking these links will bring up the relevant source citation(s) in PubMed. You may need to download the Adobe Scalable Vector Graphic (SVG) plugin to utilize the visualization tool (you will be prompted if you need it).prediction, bayesian network, probabilistic, interaction, networkSCR_004182(bioPIXIE, RRID:SCR_004182)Princeton University; New Jersey; USA NHGRI, NIGMS, NSFPMID:16420673Last checked downnlx_20893
Yogo Data Management SystemResource, software resource, software toolkit, software application, source codeA set of software tools created to rapidly build scientific data-management applications. These applications will enhance the process of data annotation, analysis, and web publication. The system provides a set of easy-to-use software tools for data sharing by the scientific community. It enables researchers to build their own custom-designed data management systems. The problem of scientific data management rests on several challenges. These include flexible data storage, a way to share the stored data, tools to curate the data, and history of the data to show provenance. The Yogo Framework gives you the ability to build scientific data management applications that address all of these challenges. The Yogo software is being developed as part of the NeuroSys project. All tools created as part of the Yogo Data Management Framework are open source and released under an OSI approved license.SCR_004239(Yogo Data Management System, RRID:SCR_004239)Montana State University EPSCoR Program, Lumina Foundation, Montana State University; Montana; USA, NIMH, NSF, The Michael J. Fox Foundation for Parkinsons ResearchLast checked downnlx_25179
Catalog of FishesResource, narrative resource, data or information resource, bibliography, book, databaseThe Catalog of Fishes is the authoritative reference for taxonomic fish names, featuring a searchable on-line database. The Catalog of Fishes covers more than 53,000 species and subspecies, over 10,000 genera and subgenera, and includes in excess of 16,000 bibliographic references. The Catalog of Fishes consists of three hardbound volumes of 900-1000 pages each, along with a CD-ROM. The online database is updated about every 8 weeks and is now about twice the size of the published version. It is one of the oldest and most complete databases for any large animal group. References are over 30,000. Valid species are over 30,000. This work is an essential reference for taxonomists, scientific historians, and for any specialist dealing with fishes. Entries for species, for example, consist of species/subspecies name, genus, author, date, publication, pages, figures, type locality, location of type specimen(s), current status (with references), family/subfamily, and important publication, taxonomic, or nomenclatural notes. Nearly all original descriptions have been examined, and much effort has gone into determining the location of type specimens. The Genera are updated from Eschmeyer''s 1990 Genera of Recent Fishes. Both genera and species are listed in a classification using recent taxonomic schemes. Also included are a lengthy list of museum acronyms, an interpretation of the International Code of Zoological Nomenclature, and Opinions of the International Commission involving fishes.genus, species, reference, publicationSCR_004408(Catalog of Fishes, RRID:SCR_004408)California Academy of Sciences Alfred P. Sloan Foundation, NSFrelated to: Teleost Taxonomy Ontology, Phenoscape KnowledgebaseLast checked downnlx_41737
AFTOLResource, data repository, biospecimen repository, data set, service resource, storage service resource, data or information resource, material storage repositoryTo enhance the understanding of the evolution of the Kingdom Fungi, 1500+ species were sampled for eight gene loci across all major fungal clades, plus a subset of taxa for a suite of morphological and ultrastructural characters with resulting data: AFTOL Molecular Database (generated by WASABI - Web Accessible Sequence Analysis for Biological Inference), Blast search the AFTOL Database (generated by WASABI), AFTOL primers (generated by WASABI), AFTOL primers by species (generated by WASABI), AFTOL alignments, and the AFTOL Structural and Biochemical Database. Users may submit samples to the AFTOL project. AFTOL is a collaboration centered around four universities in the United States: Duke University (Francois Lutzoni and Rytas Vilgalys), Clark University (David Hibbett), Oregon State University (Joey Spatafora), and University of Minnesota (David McLaughlin). Participants throughout the world have donated vouchers, taxon samples, and gene sequences. The aim of the project is to reconstruct the fungal tree of life using all available data for eight loci (nuclear ribosomal DNA: LSU, SSU, ITS (including 5.8s, ITS1 and ITS2); RNA polymerase II: RPB1, RPB2; elongation factor 1-alpha; mitochondrial SSU rDNA, and mitochondrial ATP synthase protein subunit 6). A further objective of this study is to summarize and integrate current knowledge regarding fungal subcellular features within this new phylogenetic framework. The name of the bioinformatic package developed for AFTOL is WASABI which provides an efficient communication platform to facilitate the collection and dissemination of molecular data to (and from) the laboratories and participants. All molecular data can be viewed, downloaded, verified, and corrected by the participants of AFTOL. A central goal of the WASABI interface is to establish an automated analysis framework that includes basecalling of newly generated chromatograms, contig assembly, quality verification of sequences (including a local BLAST), sequence alignment, and congruence test. Gene sequences that pass all tests and are finally verified by their authors will undergo automated phylogenetic analysis on a regular schedule. Although all steps are initially carried out noninteractively, the users can verify and correct the results at any step and thus initiate the reanalysis of dependent data.cytology, morphology, phylogeny, ultrastructure, primer, alignment, blast, sequence, taxonomy, structure, biochemical, subcellular, organism-related portal, data analysis service, culture, sporocarp, dna, pcr product, molecular, molecule, gene sequenceSCR_004650(AFTOL, RRID:SCR_004650)Oregon State University; Oregon; USA NSFReferences (2)Last checked downnlx_64804
PGNResource, data analysis service, production service resource, analysis service resource, database, data set, service resource, storage service resource, data repository, data or information resourceResource for the storage, retrieval and annotation of plant ESTs, with a focus on comparative genomics. PGN comprises an analysis pipeline and a website, and presently contains mainly data from the Floral Genome Project. However, it accepts submission from other sources. All data in PGN is directly derived from chromatograms and all original and intermediate data are stored in the database. The current datasets on PGN come from the floral genome project and includes the following species: Acorus americanus, Amborella trichopoda, Asparagus officinalis, Cucumis sativus, Eschscholzia californica, Eschscholzia californica, Illicium parviflorum, Ipomopsis aggregata, Liriodendron tulipifera, Mesembryanthemum crystallinum, Mimulus guttatus, Nuphar advena, Papaver somniferum, Persea americana, Prymnesium parvum, Ribes americanum, Saruma henryi, Stenogyne rugosa, Vaccinium corymbosa, Welwitschia mirabilis, Yucca filamentosa, Zamia fischeri. For functional annotation, blast is used to compare find the best match of each unigene sequence to in the Genbank NR database, and the in complete coding sequences from Arabidopsis. These annotations are stored in the database and serve as the primary source of annotation. The annotation framework will be extended to Gene Ontology annotations in the future.expressed sequence tag, genomics, functional annotation, blast, sequencing, chromatogramSCR_004559(PGN, RRID:SCR_004559)Cornell University; New York; USA NSFLast checked downnlx_55223
NBCResource, analysis service resource, data analysis service, service resource, production service resourceWebserver for taxonomic classification of metagenomic reads.metagenome, genome, virus, taxonomy, next-generation sequencing, taxonomic classification, classificationSCR_004772(NBC, RRID:SCR_004772)Drexel University; Pennsylvania; USA DOE, NSFlisted by: OMICtoolsReferences (2)Last checked downOMICS_01458
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