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https://neuinfo.org/mynif/search.php?q=*&t=indexable&list=cover&nif=nlx_154697-2

A virtual database of annotations made by 50 database providers (April 2014) - and growing (see below), that map data to publication information. All NIF Data Federation sources can be part of this virtual database as long as they indicate the publications that correspond to data records. The format that NIF accepts is the PubMed Identifier, category or type of data that is being linked to, and a data record identifier. A subset of this data is passed to NCBI, as LinkOuts (links at the bottom of PubMed abstracts), however due to NCBI policies the full data records are not currently associated with PubMed records. Database providers can use this mechanism to link to other NCBI databases including gene and protein, however these are not included in the current data set at this time. (To view databases available for linking see, http://www.ncbi.nlm.nih.gov/books/NBK3807/#files.Databases_Available_for_Linking ) The categories that NIF uses have been standardized to the following types: * Resource: Registry * Resource: Software * Reagent: Plasmid * Reagent: Antibodies * Data: Clinical Trials * Data: Gene Expression * Data: Drugs * Data: Taxonomy * Data: Images * Data: Animal Model * Data: Microarray * Data: Brain connectivity * Data: Volumetric observation * Data: Value observation * Data: Activation Foci * Data: Neuronal properties * Data: Neuronal reconstruction * Data: Chemosensory receptor * Data: Electrophysiology * Data: Computational model * Data: Brain anatomy * Data: Gene annotation * Data: Disease annotation * Data: Cell Model * Data: Chemical * Data: Pathways For more information refer to Create a LinkOut file, http://neuinfo.org/nif_components/disco/interoperation.shtm Participating resources ( http://disco.neuinfo.org/webportal/discoLinkoutServiceSummary.do?id=4 ): * Addgene http://www.addgene.org/pgvec1 * Animal Imaging Database http://aidb.crbs.ucsd.edu * Antibody Registry http://www.neuinfo.org/products/antibodyregistry/ * Avian Brain Circuitry Database http://www.behav.org/abcd/abcd.php * BAMS Connectivity http://brancusi.usc.edu/ * Beta Cell Biology Consortium http://www.betacell.org/ * bioDBcore http://biodbcore.org/ * BioGRID http://thebiogrid.org/ * BioNumbers http://bionumbers.hms.harvard.edu/ * Brain Architecture Management System http://brancusi.usc.edu/bkms/ * Brede Database http://hendrix.imm.dtu.dk/services/jerne/brede/ * Cell Centered Database http://ccdb.ucsd.edu * CellML Model Repository http://www.cellml.org/models * CHEBI http://www.ebi.ac.uk/chebi/ * Clinical Trials Network (CTN) Data Share http://www.ctndatashare.org/ * Comparative Toxicogenomics Database http://ctdbase.org/ * Coriell Cell Repositories http://ccr.coriell.org/ * CRCNS - Collaborative Research in Computational Neuroscience - Data sharing http://crcns.org * Drug Related Gene Database https://confluence.crbs.ucsd.edu/display/NIF/DRG * DrugBank http://www.drugbank.ca/ * FLYBASE http://flybase.org/ * Gene Expression Omnibus http://www.ncbi.nlm.nih.gov/geo/ * Gene Ontology Tools http://www.geneontology.org/GO.tools.shtml * Gene Weaver http://www.GeneWeaver.org * GeneDB http://www.genedb.org/Homepage * Glomerular Activity Response Archive http://gara.bio.uci.edu * GO http://www.geneontology.org/ * Internet Brain Volume Database http://www.cma.mgh.harvard.edu/ibvd/ * ModelDB http://senselab.med.yale.edu/modeldb/ * Mouse Genome Informatics Transgenes ftp://ftp.informatics.jax.org/pub/reports/MGI_PhenotypicAllele.rpt * NCBI Taxonomy Browser http://www.ncbi.nlm.nih.gov/Taxonomy/taxonomyhome.html * NeuroMorpho.Org http://neuromorpho.org/neuroMorpho * NeuronDB http://senselab.med.yale.edu/neurondb * SciCrunch Registry http://neuinfo.org/nif/nifgwt.html?tab=registry * NIF Registry Automated Crawl Data http://lucene1.neuinfo.org/nif_resource/current/ * NITRC http://www.nitrc.org/ * Nuclear Receptor Signaling Atlas http://www.nursa.org * Olfactory Receptor DataBase http://senselab.med.yale.edu/ordb/ * OMIM http://omim.org * OpenfMRI http://openfmri.org * PeptideAtlas http://www.peptideatlas.org * RGD http://rgd.mcw.edu * SFARI Gene: AutDB https://gene.sfari.org/autdb/Welcome.do * SumsDB http://sumsdb.wustl.edu/sums/ * Temporal-Lobe: Hippocampal - Parahippocampal Neuroanatomy of the Rat http://www.temporal-lobe.com/ * The Cell: An Image Library http://www.cellimagelibrary.org/ * Visiome Platform http://platform.visiome.neuroinf.jp/ * WormBase http://www.wormbase.org * YPED http://medicine.yale.edu/keck/nida/yped.aspx * ZFIN http://zfin.org

Proper citation: Integrated Manually Extracted Annotation (RRID:SCR_008876) Copy   

•   Source: SciCrunch Registry

http://bioportal.bioontology.org/

Open repository of biomedical ontologies that provides access via Web browsers and Web services to ontologies. It supports ontologies in OBO format, OWL, RDF, Rich Release Format (RRF), Protege frames, and LexGrid XML. Functionality includes the ability to browse, search and visualize ontologies as well as to comment on, and create mappings for ontologies. Any registered user can submit an ontology. The NCBO Annotator and NCBO Resource Index can also be accessed via BioPortal. Additional features: * Add Reviews: rate the ontology according to several criteria and describe your experience using the ontology. * Add Mappings: submit point-to-point mappings or upload bulk mappings created with external tools. Notification of new Mappings is RSS-enabled and Mappings can be browsed via BioPortal and accessed via Web services. * NCBO Annotator: Tool that tags free text with ontology terms. NCBO uses the Annotator to generate ontology annotations, creating an ontology index of these resources accessible via the NCBO Resource Index. The Annotator can be accessed through BioPortal or directly as a Web service. The annotation workflow is based on syntactic concept recognition (using the preferred name and synonyms for terms) and on a set of semantic expansion algorithms that leverage the ontology structure (e.g., is_a relations). * NCBO Resource Index: The NCBO Resource Index is a system for ontology based annotation and indexing of biomedical data; the key functionality of this system is to enable users to locate biomedical data linked via ontology terms. A set of annotations is generated automatically, using the NCBO Annotator, and presented in BioPortal. This service uses a concept recognizer (developed by the National Center for Integrative Biomedical Informatics, University of Michigan) to produce a set of annotations and expand them using ontology is_a relations. * Web services: Documentation on all Web services and example code is available at: BioPortal Web services.

Proper citation: BioPortal (RRID:SCR_002713) Copy   

•   Source: SciCrunch Registry

http://www.cmhd.ca/genetrap/

Generate gene trap insertions using mutagenic polyA trap vectors, followed by sequence tagging to develop a library of mutagenized ES cells freely available to the scientific community. This library is searchable by sequence or key word searches including gene name or symbol, chromosome location, or Gene Ontology (GO) terms. In addition,they offer a custom email alert service in which researchers are able to submit search criteria. Researchers will receive automated e-mail notification of matching gene trap clones as they are entered into the library and database. The resource features the use of complementary second and third generation polyA trap vectors developed by the Stanford lab and the laboratory of Professor Yasumasa Ishida of the Nara Institute of Science and Technology (NAIST) in Japan to mutagenize murine embryonic stem (ES) cells. CMHD gene trap clones are distributed by the Canadian Mouse Mutant Repository(CMMR). Information about ordering, services, and pricing can be found on their web site (http://www.cmmr.ca/services/index.html)., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 15,2026.

Proper citation: Centre for Modeling Human Disease Gene Trap Resource (RRID:SCR_002785) Copy   

•   Source: SciCrunch Registry

http://www.bioperl.org

BioPerl is a community effort to produce Perl code which is useful in biology. This toolkit of perl modules is useful in building bioinformatics solutions in Perl. It is built in an object-oriented manner so that many modules depend on each other to achieve a task. The collection of modules in the bioperl-live repository consist of the core of the functionality of bioperl. Additionally auxiliary modules for creating graphical interfaces (bioperl-gui), persistent storage in RDMBS (bioperl-db), running and parsing the results from hundreds of bioinformatics applications (Run package), software to automate bioinformatic analyses (bioperl-pipeline) are all available as Git modules in our repository. The BioPerl toolkit provides a library of hundreds of routines for processing sequence, annotation, alignment, and sequence analysis reports. It often serves as a bridge between different computational biology applications assisting the user to construct analysis pipelines. This chapter illustrates how BioPerl facilitates tasks such as writing scripts summarizing information from BLAST reports or extracting key annotation details from a GenBank sequence record. BioPerl includes modules written by Sohel Merchant of the GO Consortium for parsing and manipulating OBO ontologies. Platform: Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible

Proper citation: BioPerl (RRID:SCR_002989) Copy   

•   Source: SciCrunch Registry

http://gemdock.life.nctu.edu.tw/3D-Interologs

Database of physical protein-protein interactions across multiple genomes. Based on 3D-domain interolog mapping and a scoring function, protein-protein interactions are inferred by using three-dimensional (3D) structure heterodimers to search the UniProt database. For a query protein, the database utilizes BLAST to identify homologous proteins and the interacting partners from multiple species. Based on the scoring function and structure complexes, it provides the statistic significances, the interacting models (e.g. hydrogen bonds and conserved amino acids), and functional annotations of interacting partners of a query protein. The identification of orthologous proteins of multiple species allows the study of protein-protein evolution, protein functions, and cross-referencing of proteins.

Proper citation: 3D-Interologs (RRID:SCR_003101) Copy   

•   Source: SciCrunch Registry

http://genecruiser.broadinstitute.org/genecruiser3/

A web service and web application for the annotation of microarray data providing integrated access to genomic information freely available from public data sources.

Proper citation: GeneCruiser (RRID:SCR_003153) Copy   

•   Source: SciCrunch Registry

https://planttfdb.gao-lab.org/

Comprehensive plant transcription factor database. Interface to allow users to search the database by IDs or free texts, to make sequence similarity search against TFs of all or individual species, and to download TF sequences for local analysis.PlantTFDB 3.0: a portal for the functional and evolutionary study of plant transcription factors

Proper citation: PLANTTFDB (RRID:SCR_003362) 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://ophid.utoronto.ca/navigator/

A software package for visualizing and analyzing protein-protein interaction networks. NAViGaTOR can query OPHID / I2D - online databases of interaction data - and display networks in 2D or 3D. To improve scalability and performance, NAViGaTOR combines Java with OpenGL to provide a 2D/3D visualization system on multiple hardware platforms. NAViGaTOR also provides analytical capabilities and supports standard import and export formats such as GO and the Proteomics Standards Initiative (PSI). NAViGaTOR can be installed and run on Microsoft Windows, Linux / UNIX, and Mac OS systems. NAViGaTOR is written in Java and uses JOGL (Java bindings for OpenGL) to support scalability, highlighting or suppressing of information, and other advanced graphic approaches.

Proper citation: Network Analysis, Visualization and Graphing TORonto (RRID:SCR_008373) Copy   

•   Source: SciCrunch Registry

http://akt.ucsf.edu/EGAN/

Exploratory Gene Association Networks (EGAN) is a software tool that allows a bench biologist to visualize and interpret the results of high-throughput exploratory assays in an interactive hypergraph of genes, relationships (protein-protein interactions, literature co-occurrence, etc.) and meta-data (annotation, signaling pathways, etc.). EGAN provides comprehensive, automated calculation of meta-data coincidence (over-representation, enrichment) for user- and assay-defined gene lists, and provides direct links to web resources and literature (NCBI Entrez Gene, PubMed, KEGG, Gene Ontology, iHOP, Google, etc.). EGAN functions as a module for exploratory investigation of analysis results from multiple high-throughput assay technologies, including but not limited to: * Transcriptomics via expression microarrays or RNA-Seq * Genomics via SNP GWAS or array CGH * Proteomics via MS/MS peptide identifications * Epigenomics via DNA methylation, ChIP-on-Chip or ChIP-Seq * In-silico analysis of sequences or literature EGAN has been built using Cytoscape libraries for graph visualization and layout, and is comparable to DAVID, GSEA, Ingenuity IPA and Ariadne Pathway Studio. There are pre-collated EGAN networks available for human (Homo sapiens), mouse (Mus musculus), rat (Rattus norvegicus), chicken (Gallus gallus), zebrafish (Danio rerio), fruit fly (Drosophila melanogaster), nematode (Caenorhabditis elegans), mouse-ear cress (Arabidopsis thaliana), rice (Oryza sativa) and brewer's yeast (Saccharomyces cerevisiae). There is now an EGAN module available for GenePattern (human-only). Platform: Windows compatible, Mac OS X compatible, Linux compatible

Proper citation: EGAN: Exploratory Gene Association Networks (RRID:SCR_008856) Copy   

•   Source: SciCrunch Registry

http://link.springer.com/article/10.1007%2Fs11357-003-0002-y

A database that stores information on the biomolecules which are modulated during aging and by caloric restriction (CR). To enhance its usefulness, data collected from studies of CR''''s anti-oxidative action on gene expression, oxidative stress, and many chronic age-related diseases are included. AgingDB is organized into two sections A) apoptosis and the various mitochondrial biomolecules that play a role in aging; B) nuclear transcription factors known to be_sensitive to oxidative environment. AgingDB features an imagemap of biomolecular signal pathways and visualized information that includes protein-protein interactions of biomolecules. Authorized users can submit a new biomolecule or edit an existing biomolecule to reflect latest developments.

Proper citation: AgingDB (RRID:SCR_010226) Copy   

•   Source: SciCrunch Registry

http://purl.bioontology.org/ontology/GO-EXT

An extension of the Gene Ontology.

Proper citation: Gene Ontology Extension (RRID:SCR_010327) Copy   

•   Source: SciCrunch Registry

https://bio.tools

Community registry of software tools and data resources for life sciences. Tools and data services registry as community effort to document bioinformatics resources. Registry of software and databases, facilitating researchers from across spectrum of biological and biomedical science. When adding tools to registry, information including URL, contact information, resource function, field its relevant in, and its primary publication are required. Development is supported by ELIXIR - the European Infrastructure for Biological Information.

Proper citation: bio.tools (RRID:SCR_014695) Copy   

•   Source: SciCrunch Registry

https://bioportal.bioontology.org/ontologies/REX?p=classes&conceptid=http%3A%2F%2Fpurl.obolibrary.org%2Fobo%2FREX_0000000

An ontology of physico-chemical processes, i.e. physico-chemical changes occurring in course of time. It includes both microscopic processes (involving molecular entities or subatomic particles) and macroscopic processes. Some biochemical processes from Gene Ontology (GO Biological process) can be described as instances of REX.

Proper citation: Physico-Chemical Process (RRID:SCR_003530) Copy   

•   Source: SciCrunch Registry

http://eagl.unige.ch/GOCat/

Software tool that uses a machine learning (ML) approach to classify text, based on the Gene Ontology. It relies on a k-Nearest Neighbours algorithm, a simple algorithm which assigns to a new text the categories that are the most prevalent among the k most similar instances contained in the knowledge base. The ML classifier operates in two steps and combines two components. First, a related article search engine retrieves instances (i.e. abstracts) in the knowledge base that are the most similar to the input text (its nearest neighbours); second, a score computer infers the functional profile from the k most similar instances.

Proper citation: GOCat (RRID:SCR_003608) Copy   

•   Source: SciCrunch Registry

http://purl.bioontology.org/ontology/NIGO

Ontology that is a subset of GO directed for neurological and immunological systems. It was created by clipping those GO terms that are not associated to any gene in human, rat and mouse, and by clipping terms not found to be relevant to the neural and/or immune domains.

Proper citation: Neural-Immune Gene Ontology (RRID:SCR_004120) Copy   

•   Source: SciCrunch Registry

http://www.grissom.gr/stranger/

StRAnGER (Statistical Ranking of ANotated Genomic Experimental Results) is a web application for the automated statistical analysis of annotated gene profiling experiments, exploiting controlled biological vocabularies, like the Gene Ontology or the KEGG pathways terms. Starting from annotated lists of differentially expressed genes StRAnGER repartitions and reorders the initial distribution of terms to define a new distribution of elements where each element pools terms holding the same enrichment score. The elements are then prioritized according to StRAnGER''''s algorithm and, by applying bootstrapping techniques, a corrected measure of the statistical significance of these elements is derived, enabling the selection of terms mapped to these elements, unambiguously associated with respective significant gene sets. Besides their high statistical score, another selection criterion for the terms is the number of their members, something that incurs a biological prioritization in line with a Systems Biology context. Platform: Online tool

Proper citation: StRAnGER (RRID:SCR_004247) Copy   

•   Source: SciCrunch Registry

http://sequenceontology.org/

A collaborative ontology for the definition of sequence features used in biological sequence annotation. SO was initially developed by the Gene Ontology Consortium. Contributors to SO include the GMOD community, model organism database groups such as WormBase, FlyBase, Mouse Genome Informatics group, and institutes such as the Sanger Institute and the EBI. Input to SO is welcomed from the sequence annotation community. The OBO revision is available here: http://sourceforge.net/p/song/svn/HEAD/tree/ SO includes different kinds of features which can be located on the sequence. Biological features are those which are defined by their disposition to be involved in a biological process. Biomaterial features are those which are intended for use in an experiment such as aptamer and PCR_product. There are also experimental features which are the result of an experiment. SO also provides a rich set of attributes to describe these features such as polycistronic and maternally imprinted. The Sequence Ontologies use the OBO flat file format specification version 1.2, developed by the Gene Ontology Consortium. The ontology is also available in OWL from Open Biomedical Ontologies. This is updated nightly and may be slightly out of sync with the current obo file. An OWL version of the ontology is also available. The resolvable URI for the current version of SO is http://purl.obolibrary.org/obo/so.owl.

Proper citation: SO (RRID:SCR_004374) Copy   

•   Source: SciCrunch Registry

http://caintegrator-info.nci.nih.gov/rembrandt

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on April 28,2023. REMBRANDT is a data repository containing diverse types of molecular research and clinical trials data related to brain cancers, including gliomas, along with a wide variety of web-based analysis tools that readily facilitate the understanding of critical correlations among the different data types. REMBRANDT aims to be the access portal for a national molecular, genetic, and clinical database of several thousand primary brain tumors that is fully open and accessible to all investigators (including intramural and extramural researchers), as well as the public at-large. The main focus is to molecularly characterize a large number of adult and pediatric primary brain tumors and to correlate those data with extensive retrospective and prospective clinical data. Specific data types hosted here are gene expression profiles, real time PCR assays, CGH and SNP array information, sequencing data, tissue array results and images, proteomic profiles, and patients'''' response to various treatments. Clinical trials'''' information and protocols are also accessible. The data can be downloaded as raw files containing all the information gathered through the primary experiments or can be mined using the informatics support provided. This comprehensive brain tumor data portal will allow for easy ad hoc querying across multiple domains, thus allowing physician-scientists to make the right decisions during patient treatments., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: Repository of molecular brain neoplasia data (RRID:SCR_004704) Copy   

•   Source: SciCrunch Registry

http://www.pantherdb.org/

System that classifies genes by their functions, using published scientific experimental evidence and evolutionary relationships to predict function even in absence of direct experimental evidence. Orthologs view is curated orthology relationships between genes for human, mouse, rat, fish, worm, and fly., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: PANTHER (RRID:SCR_004869) Copy   

•   Source: SciCrunch Registry