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http://www.fda.gov/ScienceResearch/BioinformaticsTools/Arraytrack/default.htm

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on May 23,2023. Software tool developed for ArrayTrack that takes a list of genes and identifies terms in Gene Ontology associated with those genes. GOFFA provides tools to view/access the following: GO term hierarchy, full listing of GO terms annotated with the genes associated with a given term, Fisher's exact test p-value providing the probability of identifying that many genes for a given term by chance alone, and relative enrichment factor (E-value) giving the enrichment of a GO term for genes in the submitted list relative to the frequency of genes assigned to that term from the full set of GOFFA annotated genes for a particular species.

Proper citation: Gene Ontology For Functional Analysis (GOFFA) (RRID:SCR_006484) Copy   

•   Source: SciCrunch Registry

http://unite.ut.ee/index.php

A fungal rDNA internal transcribed spacer (ITS) sequence database (although additional genes and genetic markers are also welcome) to facilitate identification of environmental samples of fungal DNA. Additional important features include user annotation of INSD sequences to add metadata on, e.g., locality, habitat, soil, climate, and interacting taxa. The user can furthermore annotate INSD sequences with additional species identifications that will appear in the results of any analyses done. UNITE focuses on high-quality ITS sequences generated from fruiting bodies collected and identified by experts and deposited in public herbaria. In addition, it also holds all fungal ITS sequences in the International Nucleotide Sequence Databases (INSD: NCBI, EMBL, DDBJ). Both sets of sequences may be used in any analyses carried out. UNITE is accompanied by a project management system called PlutoF, where users can store field data, document the sequencing lab procedures, manage sequences, and make analyses. PlutoF intends to make it possible for taxonomists, ecologists, and biogeographers to use a common platform for data storage, handling, and analyses, with the intent of facilitating an integration of these disciplines. A user can have an unlimited number of projects but still make analyses across any project data available to him.

Proper citation: UNITE (RRID:SCR_006518) Copy   

•   Source: SciCrunch Registry

http://rdp.cme.msu.edu

A database which provides ribosome related data services to the scientific community, including online data analysis, rRNA derived phylogenetic trees, and aligned and annotated rRNA sequences. It specifically contains information on quality-controlled, aligned and annotated bacterial and archaean 16S rRNA sequences, fungal 28S rRNA sequences, and a suite of analysis tools for the scientific community. Most of the RDP tools are now available as open source packages for users to incorporate in their local workflow.

Proper citation: Ribosomal Database Project (RRID:SCR_006633) Copy   

•   Source: SciCrunch Registry

http://ligand-expo.rutgers.edu/

An integrated data resource for finding chemical and structural information about small molecules bound to proteins and nucleic acids within the structure entries of the Protein Data Bank. Tools are provided to search the PDB dictionary for chemical components, to identify structure entries containing particular small molecules, and to download the 3D structures of the small molecule components in the PDB entry. A sketch tool is also provided for building new chemical definitions from reported PDB chemical components.

Proper citation: Ligand Expo (RRID:SCR_006636) Copy   

•   Source: SciCrunch Registry

http://www.ebi.ac.uk/ontology-lookup/

Interactive and programmatic interfaces to query, browse and navigate an increasing number of biomedical ontologies and controlled vocabularies. It provides a web service interface to query multiple ontologies from a single location with a unified output format. It can integrate any ontology available in the Open Biomedical Ontology (OBO) format. The database can be queried to obtain information on a single term or to browse a complete ontology using AJAX. Auto-completion provides a user-friendly search mechanism. An AJAX-based ontology viewer is available to browse a complete ontology or subsets of it. A weekly MySQL database export file can be downloaded from the EBI public FTP directory.

Proper citation: Ontology Lookup Service (RRID:SCR_006596) Copy   

•   Source: SciCrunch Registry

http://www.informatics.jax.org/mgihome/GXD/gxdgen.shtml

A unified resource that combines text-based and 3D graphical methods to store, display, and analyze mouse developmental gene expression information. The Mouse Gene Expression Information Resource resource will integrate the following components: * Gene Expression Database (GXD) - Integrates different types of expression data and provides links to many other resources to place the data into the larger biological and analytical context. * Anatomy Database - Provides the standard nomenclature for developmental anatomy. * 3D Atlas / Graphical Gene Expression Database - Provides a high-resolution digital representation of mouse anatomy reconstructed from serial sections of single embryos at each representative developmental stage enabling 3D graphical display and analysis of in situ expression data.

Proper citation: Mouse Genome Informatics: The Mouse Gene Expression Information Resource Project (RRID:SCR_006630) Copy   

•   Source: SciCrunch Registry

http://www.autoimmunitycenters.org/

Nine centers that conduct clinical trials and basic research on new immune-based therapies for autoimmune diseases. This program enhances interactions between scientists and clinicians in order to accelerate the translation of research findings into medical applications. By promoting better coordination and communication, and enabling limited resources to be pooled, ACEs is one of NIAID''''s primary vehicles for both expanding our knowledge and improving our ability to effectively prevent and treat autoimmune diseases. This coordinated approach incorporates key recommendations of the NIH Autoimmune Diseases Research Plan and will ensure progress in identifying new and highly effective therapies for autoimmune diseases. ACEs is advancing the search for effective treatments through: * Diverse Autoimmunity Expertise Medical researchers at ACEs include rheumatologists, neurologists, gastroenterologists, and endocrinologists who are among the elite in their respective fields. * Strong Mechanistic Foundation ACEs augment each clinical trial with extensive basic studies designed to enhance understanding of the mechanisms responsible for tolerance initiation, maintenance, or loss, including the role of cytokines, regulatory T cells, and accessory cells, to name a few. * Streamlined Patient Recruitment The cooperative nature of ACEs helps scientists recruit patients from distinct geographical areas. The rigorous clinical and basic science approach of ACEs helps maintain a high level of treatment and analysis, enabling informative comparisons between patient groups.

Proper citation: Autoimmunity Centers of Excellence (RRID:SCR_006510) Copy   

•   Source: SciCrunch Registry

http://www.doi.org/

A system for identifying content objects in the digital environment. DOI names are assigned to any entity for use on digital networks. They are used to provide current information, including where they (or information about them) can be found on the Internet. Information about a digital object may change over time, including where to find it, but its DOI name will not change. The DOI System provides a framework for persistent identification, managing intellectual content, managing metadata, linking customers with content suppliers, facilitating electronic commerce, and enabling automated management of media. DOI names can be used for any form of management of any data, whether commercial or non-commercial. The DOI System is an ISO International Standard. Using DOI names as identifiers makes managing intellectual property in a networked environment much easier and more convenient, and allows the construction of automated services and transactions.

Proper citation: DOI (RRID:SCR_006632) Copy   

•   Source: SciCrunch Registry

http://www.ebi.ac.uk/pdbe/emdb/

Repository for electron microscopy density maps of macromolecular complexes and subcellular structures at Protein Data Bank in Europe. Covers techniques, including single-particle analysis, electron tomography, and electron (2D) crystallography.

Proper citation: Electron Microscopy Data Bank at PDBe (MSD-EBI) (RRID:SCR_006506) Copy   

•   Source: SciCrunch Registry

http://www.phytozome.net/

A comparative platform for green plant genomics. Families of orthologous and paralogous genes that represent the modern descendents of ancestral gene sets are constructed at key phylogenetic nodes. These families allow easy access to clade specific orthology / paralogy relationships as well as clade specific genes and gene expansions. As of release v9.1, Phytozome provides access to forty-one sequenced and annotated green plant genomes which have been clustered into gene families at 20 evolutionarily significant nodes. Where possible, each gene has been annotated with PFAM, KOG, KEGG, and PANTHER assignments, and publicly available annotations from RefSeq, UniProt, TAIR, JGI are hyper-linked and searchable., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: Phytozome (RRID:SCR_006507) Copy   

•   Source: SciCrunch Registry

http://geothermaldata.org

Database of information resources on geothermal energy from a national network of data providers. Data are contributed by academic researchers, private sector participants, and state and federal agencies, primarily the Department of Energy. Access, view, and download data with this free and easy online search tool.

Proper citation: National Geothermal Data System (RRID:SCR_006545) Copy   

•   Source: SciCrunch Registry

http://grants.nih.gov/grants/oer.htm

OER serves as a vital interface between the NIH and the biomedical research community by guiding investigators through the process of attaining grants funding and helping them understand and navigate through federal policies and procedures. OER supports extramural research by providing policy and guidance to the 24 NIH Institutes and Centers that award grants. Extramural grants account for approximately 84 percent of NIH''s 29 billion budget. These are awarded to investigators throughout the U.S. and abroad. Approximately 10 percent of the NIH budget supports NIH intramural investigators, NIH staff who conduct research.

Proper citation: Office of Extramural Research NIH (RRID:SCR_006547) Copy   

•   Source: SciCrunch Registry

https://repository.niddk.nih.gov/home/

NIDDK Central Repositories are two separate contract funded components that work together to store data and samples from significant, NIDDK funded studies. First component is Biorepository that gathers, stores, and distributes biological samples from studies. Biorepository works with investigators in new and ongoing studies as realtime storage facility for archival samples.Second component is Data Repository that gathers, stores and distributes incremental or finished datasets from NIDDK funded studies Data Repository helps active data coordinating centers prepare databases and incremental datasets for archiving and for carrying out restricted queries of stored databases. Data Repository serves as Data Coordinating Center and website manager for NIDDK Central Repositories website.

Proper citation: NIDDK Central Repository (RRID:SCR_006542) Copy   

•   Source: SciCrunch Registry

http://rice.plantbiology.msu.edu/

Database and resource that provides sequence and annotation data for the rice genome. This website provides genome sequence from the Nipponbare subspecies of rice and annotation of the 12 rice chromosomes. All structural and functional annotation is viewable through our Rice Genome Browser which currently supports 75 tracks of annotation. Enhanced data access is available through web interfaces, FTP downloads and a Data Extractor tool developed in order to support discrete dataset downloads. Rice is a model species for the monocotyledonous plants and the cereals which are the greatest source of food for the world''s population. While rice genome sequence is available through multiple sequencing projects, high quality, uniform annotation is required in order for genome sequence data to be fully utilized by researchers. The existence of a common gene set and uniform annotation allows researchers within the rice community to work from a common resource so that their results can be more easily interpreted by other scientists. The objective of this project has always been to provide high quality annotation for the rice genome. They generated, refined and updated gene models for the estimated 40,000-60,000 total rice genes, provided standardized annotation for each model, linked each model to functional annotation including expression data, gene ontologies, and tagged lines. They have provided a resource to extend the annotation of the rice genome to other plant species by providing comparative alignments to other plant species. Analysis/Tools are available including: BLAST, Locus Name Search, Functional Term Search, Protein Domain Search, Anatomy Expression Viewer, Highly Expressed Genes

Proper citation: Rice Genome Annotation (RRID:SCR_006663) Copy   

•   Source: SciCrunch Registry

http://projectreporter.nih.gov/project_info_description.cfm?aid=8661937&icde=19363283&ddparam=&ddvalue=&ddsub=&cr=1&csb=default&cs=ASC

Initiative to assemble a multicenter team of expert neuroscientists to evaluate the late effects of Traumatic brain injury (TBI), including single and repetitive TBI of varying severity, and Chronic Traumatic Encephalopathy (CTE), using histological examination of postmortem bio specimens and neuroimaging tools as a foundation to develop in vivo diagnostics. As a first aim, this proposal will bring together a team of 5 accomplished neuropathologists in neurodegenerative disease to establish consensus criteria for the post-mortem diagnosis of CTE. This team will also define the stages of CTE pathology, the features that differentiate CTE from other neurodegenerations and the effects of substance abuse, and the characteristics of posttraumatic neurodegeneration after single TBI. As a second aim, this proposal will establish a national bio specimen and data bank for TBI (Understanding Neurological Injury and Traumatic Encephalopathy (UNITE) bio bank) by developing a nationwide brain donor registry and hotline to acquire high quality bio specimens and data. The UNITE bank will use strictly standardized protocols and a web-based interface to ensure that tissue and data are readily available to qualified investigators. Comprehensive retrospective clinical data including clinical symptoms, brain trauma and substance abuse history, and medical records (including common data elements) will be entered into a secure database. Behavioral/ mood dysfunction, cognitive changes, substance abuse and traumatic exposure will be correlated with quantitative assessment of the multifocal tauopathy, Ass deposition and axonal injury. As a third aim, neuroimaging signatures of the neuropathology will be determined in post-mortem tissue using high spatial resolution diffusion tensor imaging (DTI) and autoradiography using a highly selective PET ligand for tau. Quantitative assessment of axonal injury, tau, and Ass will be correlated with ex vivo DTI abnormalities and tau ligand autoradiography. Pilot neuroimaging studies of individuals at high risk for the development of CTE will also be conducted in the final 2 years of the proposal. This proposal will determine the clinical and neuroimaging correlates of CTE and posttraumatic neurodegeneration and create the groundwork for establishing their incidence and prevalence. This study will have a tremendous impact on public health of millions of Americans and greatly increase our understanding of the latent effects of brain trauma.

Proper citation: CTE and Post-traumatic Neurodegeneration: Neuropathology and Ex Vivo Imaging (RRID:SCR_006543) Copy   

•   Source: SciCrunch Registry

http://www.informatics.jax.org/expression.shtml

Community database that collects and integrates the gene expression information in MGI with a primary emphasis on endogenous gene expression during mouse development. The data in GXD are obtained from the literature, from individual laboratories, and from large-scale data providers. All data are annotated and reviewed by GXD curators. GXD stores and integrates different types of expression data (RNA in situ hybridization; Immunohistochemistry; in situ reporter (knock in); RT-PCR; Northern and Western blots; and RNase and Nuclease s1 protection assays) and makes these data freely available in formats appropriate for comprehensive analysis. There is particular emphasis on endogenous gene expression during mouse development. GXD also maintains an index of the literature examining gene expression in the embryonic mouse. It is comprehensive and up-to-date, containing all pertinent journal articles from 1993 to the present and articles from major developmental journals from 1990 to the present. GXD stores primary data from different types of expression assays and by integrating these data, as data accumulate, GXD provides increasingly complete information about the expression profiles of transcripts and proteins in different mouse strains and mutants. GXD describes expression patterns using an extensive, hierarchically-structured dictionary of anatomical terms. In this way, expression results from assays with differing spatial resolution are recorded in a standardized and integrated manner and expression patterns can be queried at different levels of detail. The records are complemented with digitized images of the original expression data. The Anatomical Dictionary for Mouse Development has been developed by our Edinburgh colleagues, as part of the joint Mouse Gene Expression Information Resource project. GXD places the gene expression data in the larger biological context by establishing and maintaining interconnections with many other resources. Integration with MGD enables a combined analysis of genotype, sequence, expression, and phenotype data. Links to PubMed, Online Mendelian Inheritance in Man (OMIM), sequence databases, and databases from other species further enhance the utility of GXD. GXD accepts both published and unpublished data.

Proper citation: Gene Expression Database (RRID:SCR_006539) Copy   

•   Source: SciCrunch Registry

http://www.chem.qmul.ac.uk/iupac/

This site is intended primarily to provide information on IUPAC nomenclature recommendations (Organic & Biochemical Nomenclature, Symbols & Terminology etc.). As the author has been primarily involved in the preparation of organic and biochemical material most work will be in that field. Other material will be provided as it becomes available, either from this site or by links to other locations.

Proper citation: NC-IUPAC (RRID:SCR_006655) Copy   

•   Source: SciCrunch Registry

http://www.dpvweb.net/

DPVweb provides a central source of information about viruses, viroids and satellites of plants, fungi and protozoa. Comprehensive taxonomic information, including brief descriptions of each family and genus, and classified lists of virus sequences are provided. The database also holds detailed, curated, information for all sequences of viruses, viroids and satellites of plants, fungi and protozoa that are complete or that contain at least one complete gene. For comparative purposes, it also contains a single representative sequence of all other fully sequenced virus species with an RNA or single-stranded DNA genome. The start and end positions of each feature (gene, non-translated region and the like) have been recorded and checked for accuracy. As far as possible, nomenclature for genes and proteins are standardized within genera and families. Sequences of features (either as DNA or amino acid sequences) can be directly downloaded from the website in FASTA format. The sequence information can also be accessed via client software for PC computers (freely downloadable from the website) that enable users to make an easy selection of sequences and features of a chosen virus for further analyses. The public sequence databases contain vast amounts of data on virus genomes but accessing and comparing the data, except for relatively small sets of related viruses can be very time consuming. The procedure is made difficult because some of the sequences on these databases are incorrectly named, poorly annotated or redundant. The NCBI Reference Sequence project (1) provides a comprehensive, integrated, non-redundant set of sequences, including genomic DNA, transcript (RNA) and protein products, for major research organisms. This now includes curated information for a single sequence of each fully sequenced virus species. While this is a welcome development, it can only deal with complete sequences. An important feature of DPV is the opportunity to access genes (and other features) of multiple sequences quickly and accurately. Thus, for example, it is easy to obtain the nucleotide or amino acid sequences of all the available accessions of the coat protein gene of a given virus species or for a group of viruses. To increase its usefulness further, DPVweb also contains a single representative sequence of all other fully sequenced virus species with an RNA or single-stranded DNA (ssDNA) genome. Sponsors: This site is supported by the Association of Applied Biologists and the Zhejiang Academy of Agricultural Sciences, Hangzhou, People''s Republic of China.

Proper citation: Descriptions of Plant Viruses (RRID:SCR_006656) Copy   

•   Source: SciCrunch Registry

http://bioconductor.org/packages/bioc/html/GeneAnswers.html

GeneAnswers provide an integrated tool for given genes biological or medical interpretation. It includes statistical test of given genes and specified categories. Microarray techniques have been widely employed in genomic scale studies for more than one decade. The standard analysis of microarray data is to filter out a group of genes from thousands of probes by certain statistical criteria. These genes are usually called significantly differentially expressed genes. Recently, next generation sequencing (NGS) is gradually adopted to explore gene transcription, methylation, etc. Also a gene list can be obtained by NGS preliminary data analysis. However, this type of information is not enough to understand the potential linkage between identified genes and interested functions. The integrated functional and pathway analysis with gene expression data would be very helpful for researchers to interpret the relationship between the identified genes and proposed biological or medical functions and pathways. The GeneAnswers package provides an integrated solution for a group of genes and specified categories (biological or medical functions, such as Gene Ontology, Disease Ontology, KEGG, etc) to reveal the potential relationship between them by means of statistical methods, and make user-friendly network visualization to interpret the results. Besides the package has a function to combine gene expression profile and category analysis together by outputting concept-gene cross tables, keywords query on NCBI Entrez Gene and application of human based Disease ontology analysis of given genes from other species can help people to understand or discover potential connection between genes and functions. Sponsors: This project was supported in part by Award Number UL1RR025741 from the National Center for Research Resources.

Proper citation: GeneAnswers (RRID:SCR_006498) Copy   

•   Source: SciCrunch Registry

http://www.plantontology.org

Ontology and database that links plant anatomy, morphology and growth and development to plant genomics data.Plant Ontology Consortium develops, curates and shares controlled vocabularies (ontologies) that describe plant structures and growth and developmental stages, providing semantic framework for meaningful cross species queries across databases. PO is under active development to expand to encompass terms and annotations from all plants.

Proper citation: Plant Ontology (RRID:SCR_006494) Copy   

•   Source: SciCrunch Registry