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

Nucleotide database as collection of sequences from several sources, including GenBank, RefSeq, TPA and PDB. Genome, gene and transcript sequence data provide the foundation for biomedical research and discovery.

Proper citation: Nucleotide database (RRID:SCR_004630) Copy   

•   Source: SciCrunch Registry

http://blast.ncbi.nlm.nih.gov/Blast.cgi

Web search tool to find regions of similarity between biological sequences. Program compares nucleotide or protein sequences to sequence databases and calculates statistical significance. Used for identifying homologous sequences.

Proper citation: NCBI BLAST (RRID:SCR_004870) Copy   

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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

http://dgv.tcag.ca/dgv/app/home

Public repository that accepts direct submissions and provides archiving, accessioning and distribution of publicly available genomic structural variants, in all species. Variants are accessioned at the study and sample level, granting stable identifiers that can be used in publications. DGVa data is integrated with other EBI resources, including comprehensive EBI search and Ensembl genome browser. Exchanges data with companion database, dbVar, at National Center for Biotechnology Information.NOTE: since 2019 DGVa doesn't accept submissions. Please send the data for submission to European Variation Archive (EVA).

Proper citation: Database of Genomic Variants Archive (DGVa) (RRID:SCR_004896) Copy   

•   Source: SciCrunch Registry

https://datashare.ed.ac.uk/handle/10283/3844

Genome transcriptome atlas by RNA in situ hybridization on sagittal sections of developing mouse at embryonic day 14.5. Consists of searchable database of annotated images that can be interactively viewed. Anatomy based expression profiles for coding genes and microRNAs, tissue specific genes. Expression data generated by using human and murine tissue arrays.

Proper citation: Eurexpress (RRID:SCR_005093) Copy   

•   Source: SciCrunch Registry

http://smart.embl.de/

Software tool for identification and annotation of genetically mobile domains and analysis of domain architectures.

Proper citation: SMART (RRID:SCR_005026) Copy   

•   Source: SciCrunch Registry

http://birdgenenames.org/cgnc/

International group of researchers interested in providing standardized gene nomenclature for chicken genes. A Chicken Gene Annotation Tool is available from CGNC-UK which assigns chicken nomenclature based on predicted orthology to human genes. The CGNC-US database includes CGNC-UK information and adds manually biocurated from biocurators and interested contributors. A Human Chicken Ortholog Predictions Search is available. Both resources are part of a united CGNC effort and nomenclature data is shared and co-ordinated between these two resources. They strongly encourage researchers with domain knowledge to participate in this nomenclature effort by requesting a login and providing gene nomenclature for their genes of interest. Please contact them for further information or assistance. The AGNC works in conjunction with public resources such as NCBI and Ensembl and in consultation with existing nomenclature committees, including the Chicken Gene Nomenclature Committee (CGNC). The Avian and Chicken nomenclature efforts are co-ordinated and chicken data is shared between these two groups.

Proper citation: Chicken Gene Nomenclature Consortium (RRID:SCR_004966) Copy   

•   Source: SciCrunch Registry

http://neurowiki.alleninstitute.org/index.php/Main_Page

THIS RESOURCE IS NO LONGER IN SERVICE, documented September 6, 2016. The Allen Institute Neurowiki is a joint project between Vulcan Inc. and the Allen Institute to build a Semantic Wiki mapping genetic instances. It is a finished prototype testing the import pipelines and display componenets for combining 5 major RDF datasets from 4 different sources. Current planning includes mapping complete datasets, curating a better ontology, and creating multiple ontology management for a user class. Biological Linked Data Map: * Open, public online access * Data from multiple RDF data stores * Complete import pipeline using LDIF framework * Outlines of each imported instance embedding inline wiki properties and providing views of imported properties from original RDF datasets * Charting tools that ''''pivot'''' SPARQL queries providing several views of each query * Navigation and composition tools for accessing and mining the data Where did we get the data? * KEGG: Kyoto Encyclopedia of Genes and Genomes: KEGG GENES is a collection of gene catalogs for all complete genomes generated from publicly available resources, mostly NCBI RefSeq * Diseasome: The Diseasome website is a disease / disorder relationships explorer and a sample of an innovative map-oriented scientific work. Built by a team of researchers and engineers, it uses the Human Disease Network dataset. * DrugBank: The DrugBank database is a unique bioinformatics and cheminformatics resource that combines detailed drug data with comprehensive drug target information. * Sider: Sider contains information on marketed medicines and their recorded adverse drug reactions. The information is extracted from public documents and package inserts. Every piece of content on every instance page is generated by Semantic Result Formatters interpreting SPARQL results.

Proper citation: Allen Institute Neurowiki (RRID:SCR_005042) Copy   

•   Source: SciCrunch Registry

http://smd.princeton.edu/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on December 17, 2021. Database to store, annotate, view, analyze and share microarray data. It provides registered users access to their own data, provides users access to public data, and tools with which to analyze those data, to any public user anywhere in the world. The GenePattern software package has been incorporated directly into SMD, providing access to many new analysis tools, as well as a plug-in architecture that allows users to directly integrate and share additional tools through SMD. This extension is available with the SMD source code that is fully and freely available to others under an Open Source license, enabling other groups to create a local installation of SMD with an enriched data analysis capability. SMD search options allow the user to Search By Experiments, Search By Datasets, or Search By Gene Names. Web services are provided using common standards, such as Simple Object Access Protocol (SOAP). This enables both local and remote researchers to connect to an installation of the database and retrieve data using pre-defined methods, without needing to resort to use of a web browser.

Proper citation: SMD (RRID:SCR_004987) Copy   

•   Source: SciCrunch Registry

http://comgen.pl/mirex/

mirEX is a comprehensive platform for comparative analysis of primary microRNA expression data. quantitative real-time PCR-based gene expression profiles are stored in a universal and expandable database scheme and wrapped by an intuitive user-friendly interface. A new way of accessing gene expression data in mirEX includes a simple mouse operated querying system and dynamic graphs for data mining analyses. In contrast to other publicly available databases, the mirEX interface allows a simultaneous comparison of expression levels between various microRNA genes in diverse organs and developmental stages. Currently, mirEX integrates information about the expression profile of 190 Arabidopsis thaliana pri-miRNAs in seven different developmental stages: seeds, seedlings and various organs of mature plants. Additionally, by providing RNA structural models, publicly available deep sequencing results, experimental procedure details and careful selection of auxiliary data in the form of web links, mirEX can function as a one-stop solution for Arabidopsis microRNA information. This database aims to be useful to anyone investigating the role of microRNAs in shaping plant development, organ formation and response to different biotic and abiotic stresses. To start exploring the database just press the "Browse Atlas" button or search for a particular microRNA record by typing at least two numbers from its ID in the window.

Proper citation: mirEX (RRID:SCR_006060) Copy   

•   Source: SciCrunch Registry

http://ucsd.researchaccelerator.org/

Software platform that allows researchers to easily collaborate on research and share reagents, antibodies, cell lines and more. It is designed to increase scientific collaboration across disciplines and geographical boundaries. Among the institutions now using the platform include Yale University, U of Pennsylvania, U of Chicago, Washington U, Cambridge University, University College London. The platform is licensed to select institutions. ResearchAccelerator.org allows researchers to form targeted, data driven collaborations. Researchers can search for data based on gene, disease and pathway, and they can post data which would otherwise be orphaned. The resulting collaborations, which are likely to be transdisciplinary, can greatly amplify impact and research productivity.

Proper citation: Research Accelerator (RRID:SCR_006051) Copy   

•   Source: SciCrunch Registry

http://ogeedb.embl.de/#summary

Online GEne Essentiality database containing genes that were tested experimentally for essentiality and their features; it also provides a set of tools to systematically explore and analyze these data. The main purpose of this project is to better understand gene essentiality by facilitating the comparisons of the differences and similarities between essential and non-essential genes. This is achieved by collecting not only experimentally tested essential and non-essential genes, but also associated gene features such as expression profiles, duplication status, conservation across species, evolutionary origins and involvement in embryonic development. We focus on large-scale experiments and complement our data with text-mining results. Genes are organized into data sets according to their sources. Genes with variable essentiality status across data sets are tagged as conditionally essential, highlighting the complex interplay between gene functions and environments. Linked tools allow the user to compare gene essentiality among different gene groups, or compare features of essential genes to non-essential genes, and visualize the results. Why is it different from existing databases? * we included both essential and non-essential genes so that we could better understand the gene essentiality by comparing the similarities and differences between the two gene sets; * we compiled a list of features for each gene, including whether they are duplicates or involved in development, the number of other homologous genes in the same genome, as well as their earliest expression stages during development. These features are keys to understand the essentiality of genes; * we also provide a set of tools to explore our data and visualize the results. For example, users can simply divide genes into two groups according to whether they are duplicates, calculate the proportion of essential genes (PE%) in each group and then visualize the results in a bar plot; or they can classify genes into multiple groups according to their earliest expression stages during evolution, compare the essentiality of genes that were expressed earlier with those were latter, and plot the results in a line chart.

Proper citation: OGEE - Online GEne Essentiality database (RRID:SCR_006080) Copy   

•   Source: SciCrunch Registry

http://db-mml.sjtu.edu.cn/ICEberg/

ICEberg is an integrated database that provides comprehensive information about integrative and conjugative elements (ICEs) found in bacteria. ICEs are conjugative self-transmissible elements that can integrate into and excise from a host chromosome. An ICE contains three typical modules, integration and excision, conjugation, and regulation modules, that collectively promote vertical inheritance and periodic lateral gene flow. Many ICEs carry likely virulence determinants, antibiotic-resistant factors and/or genes coding for other beneficial traits. ICEberg offers a unique, highly organized, readily explorable archive of both predicted and experimentally supported ICE-relevant data. It currently contains details of 428 ICEs found in representatives of 124 bacterial species, and a collection of >400 directly related references. A broad range of similarity search, sequence alignment, genome context browser, phylogenetic and other functional analysis tools are readily accessible via ICEberg. ICEberg will facilitate efficient, multidisciplinary and innovative exploration of bacterial ICEs and be of particular interest to researchers in the broad fields of prokaryotic evolution, pathogenesis, biotechnology and metabolism. The ICEberg database will be maintained, updated and improved regularly to ensure its ongoing maximum utility to the research community.

Proper citation: ICEberg (RRID:SCR_006026) Copy   

•   Source: SciCrunch Registry

https://www.braintest.org/brain_test/BrainTest

A portal of online studies that encourage community participation to tackle the most challenging problems in neuropsychiatry, including attention-deficit / hyperactivity disorder, schizophrenia, and bipolar disorder. Our approach is to engage the community and try to recruit tens of thousands of people to spend an hour of their time on our site. You folks will provide data in both brain tests and questionnaires, as well as DNA, and in return, we will provide some information about your brain and behavior. You will also be entered to win amazon.com gift cards. While large collaborative efforts were made in genetics in order to discover the secrets of the human genome, there are still many mysteries about the behaviors that are seen in complex neuropsychiatric syndromes and the underlying biology that gives rise to these behaviors. We know that it will require studying tens of thousands of people to begin to answer these questions. Having you, the public, as a research partner is the only way to achieve that kind of investment. This site will try to reach that goal, by combining high-throughput behavioral assessment using questionnaires and game-like cognitive tests. You provide the data and then we will provide information and feedback about why you should help us achieve our goals and how it benefits everyone in the world. We believe that through this online study, we can better understand memory and attention behaviors in the general population and their genetic basis, which will in turn allow us to better characterize how these behaviors go awry in people who suffer from mental illness. In the end, we hope this will provide better, more personalized treatment options, and ultimately prevention of these widespread and extremely debilitating brain diseases. We will use the data we collect to try to identify the genetic basis for memory and impulse control, for example. If we can achieve this goal, maybe we can then do more targeted research to understand how the biology goes awry in people who have problems with cognition, including memory and impulse control, like those diagnosed with ADHD, Schizophrenia, Bipolar Disorder, and Autism Spectrum Disorders. By participating in our research, you can learn about mental illness and health and help researchers tackle these complex problems. We can''t do it without your help.

Proper citation: Brain Test (RRID:SCR_006212) Copy   

•   Source: SciCrunch Registry

http://www.gwascentral.org/

Publicly available database of summary level findings from genetic association studies in humans, including genome wide association studies (GWAS). Previously named HGBASE, HGVbase and HGVbaseG2P.

Proper citation: GWAS Central (RRID:SCR_006170) Copy   

•   Source: SciCrunch Registry

http://intramural.nimh.nih.gov/gcap/index.htm

Schizophrenia related portal that aims to solve the mystery of genetic predisposition to psychosis, develop new methods for early diagnosis and prevention, and discover new treatments that will cure people suffering from it. Our objectives are to fully characterize: # neurobiological mechanisms related to susceptibility genes for schizophrenia and related clinical disorders; # genetic variation in aspects of cognition and emotionality associated with schizophrenia; and # small molecular targets for novel therapies. A unique feature of this Program is that its diverse scientific resources will be focused on a highly specific scientific agenda, that is to acquire the critical biological information about the susceptibility genes associated with schizophrenia and related illnesses. Our mission and goal, to understand the basic mechanisms of serious mental illness, has again guided us into new areas of research and to new insights. We have found evidence of new genes implicated in the cause of schizophrenia and involved in brain functions related to cognition and emotion and we have begun to explore how genes interact with each other and with the environment to individualize risk for these conditions. We are working now with over 20 genes related to schizophrenia. One of the key developments in our research over the past year has been the emergence of some targets for the development of novel therapeutics. We have discovered a new schizophrenia susceptibility gene, KCNH2, which represents the first clear target for the development of novel treatments. Just in this past year, for example, we published the first extensive statistical analysis of how schizophrenia genes may vary in their risk effects based on different genetic background (Nicodemus et al Hum Gen 2006), the first studies of schizophrenia genes interacting in effecting gene expression in brain (Lipska et al Hum Mol Genetics 2006a, Lipska et al Hum Mol Gen 2006 b); the first evidence that the mechanism of genetic association of NRG1 with schizophrenia involves a novel isoform of the gene in human brain (Law et al PNAS 2006), and the first evidence that MAOA may be linked to mood and impulse control because it effects critical mood regulatory neural networks (Meyer-Lindenberg et al PNAS 2006).

Proper citation: Genes Cognition and Psychosis Program (RRID:SCR_006292) Copy   

•   Source: SciCrunch Registry

http://www.umd.be/BRCA1/

The UMD-BRCA1/BRCA2 databases have been set up in a joined national effort through the network of 16 diagnostic laboratories to provide up-to-date information about mutations of the BRCA1 and BRCA2 genes identified in patients with breast and/or ovarian cancer. These databases currently contain published and unpublished information about the BRCA1/BRCA2 mutations reported in French diagnostic laboratories. This database includes 28 references and 5530 mutations (1440 different mutations and 786 protein variants) The databases of BRCA1 and BRCA2 mutations were built using the Universal Mutation Database tool. For each mutation, information is provided at several levels: * at the gene level: exon and codon number, wild type and mutant codon, mutation event, mutation name and, * at the protein level: wild type and mutant amino acid, binding domain, affected domain. If you want to submit a mutation, please contact R. Lidereau., S. Caputo. or E. Rouleau.

Proper citation: UMD-BRCA1/ BRCA2 databases (RRID:SCR_006128) Copy   

•   Source: SciCrunch Registry

http://isaac.bioapps.biozentrum.uni-wuerzburg.de/isaac/modules/genome/species.xhtml

Web based tool to enable the analysis of sets of genes, transcripts and proteins under different biological viewpoints and to interactively modify these sets at any point of the analysis. Detailed history and snapshot information allows tracing each action. One can switch back to previous states and perform new analyses. Sets can be viewed in the context of genomes, protein functions, protein interactions, pathways, regulation, diseases and drugs. Additionally, users can switch between species with an automatic, orthology based translation of existing gene sets. Sets as well as results of analyses can be exchanged between members of groups.

Proper citation: InterSpecies Analysing Application using Containers (RRID:SCR_006243) Copy   

•   Source: SciCrunch Registry

http://cran.r-project.org/web/packages/fcros/

A fold change ranks ordering statistics based software for detecting differentially expressed genes.

Proper citation: FCROS (RRID:SCR_006195) Copy   

•   Source: SciCrunch Registry

http://crezoo.org/

The CreZOO database is the European virtual repository of Cre and other targeted conditional driver strains. CreZOO is being developed in the context of the CREATE consortium, a core of major European and international mouse database holders and research groups involved in conditional mutagenesis. Its aim is to capture and disseminate extant and new information on Cre driver strains. CreZOO also aims to contribute data to the CREATE portal for worldwide access of related information. All transgenic strains carry detailed information on the promoter, specificity (using Adult Mouse Anatomy terms and Theiler Stages) and expressed gene(s) including IDs and direct links where available. Allele details are also presented, in addition to strain, background and availability (in the form of live mice, cryopreserved embryos or sperm etc) information (including EMMA, MGI, MMRRC etc hyperlinks where available). Handling and genotyping details (in the form of documents or hyperlinks) together with all relevant publications are clearly presented with PMID(s) and direct PubMed links.

Proper citation: CreZOO (RRID:SCR_006132) Copy   

•   Source: SciCrunch Registry