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http://www.genome.jp/kegg/expression/

Database for mapping gene expression profiles to pathways and genomes. Repository of microarray gene expression profile data for Synechocystis PCC6803 (syn), Bacillus subtilis (bsu), Escherichia coli W3110 (ecj), Anabaena PCC7120 (ana), and other species contributed by the Japanese research community.

Proper citation: Kyoto Encyclopedia of Genes and Genomes Expression Database (RRID:SCR_001120) Copy   

•   Source: SciCrunch Registry

http://sing.ei.uvigo.es/GC/

Tool for extensively testing the discriminatory power of biologically relevant gene sets in microarray data classification. While the user can work with different gene set collections and several microarray data files to configure specific classification experiments, the tool is able to run several tests in parallel. It is able to render valuable information for diagnostic analyses and clinical management decisions based on systematically evaluating custom hypothesis over different data sets using complementary classifiers, a key aspect in clinical research.

Proper citation: GeneCommittee (RRID:SCR_004168) Copy   

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http://www.mip-dili.eu/

Consortium that brings together Europe's top industrial and academic experts to develop new tests that will help researchers detect potential liver toxicity issues much earlier in drug development, saving many patients from the trauma of liver failure. The team aims to deepen the understanding of the science behind drug-induced liver injury, and use that knowledge to overcome the many drawbacks of the tests currently used. A major focus will be on a systematic and evidence-based evaluation of both currently available and new laboratory test systems, including cultures of liver cells in one-dimensional and three dimensional configurations. The project will also develop models that take into account the natural differences between patients. This is important because factors such as certain genes, the liver's immune response, and viral infections have all been associated with an increased risk of DILI. The project will seek to address the current lack of human liver cells available to researchers by using induced pluripotent stem cells (iPSCs) generated from patients who are particularly sensitive to DILI. Another strand of the project will develop computer models to unravel the complex, often inter-related mechanisms behind DILI. Finally, the team will assess how accurate the results of laboratory tests are at predicting actual outcomes in patients.

Proper citation: MIP-DILI (RRID:SCR_003870) Copy   

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http://www.newmeds-europe.com/

Consortium that will develop new models and methods to enable novel treatments for schizophrenia and depression including three important missing tools that will facilitate the translation of scientific findings into benefits for patients. The project will focus on developing new animal models which use brain recording and behavioral tests to identify innovative and effective drugs for schizophrenia. The project will develop standardized paradigms, acquisition and analysis techniques to apply brain imaging, especially fMRI and PET imaging to drug development. It will examine how new genetic findings (duplication and deletion or changes in genes) influence the response to various drugs and whether this information can be used to choose the right drug for the right patient. And finally, it will try and develop new approaches for shorter and more efficient trials of new medication - trials that may require fewer patients and give faster results.

Proper citation: NEWMEDS (RRID:SCR_003872) Copy   

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https://brainspan.org/

Atlas of developing human brain for studying transcriptional mechanisms involved in human brain development. One of the BrainSpan datasets, Exon microarray summarized to genes, is presented. It is a downloadable archive of files containing normalized RNA-Seq expression values for analysis.

Proper citation: BrainSpan (RRID:SCR_004219) Copy   

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http://dkcoin.org/

THIS RESOURCE IS NO LONGER IN SERVICE, documented October 13, 2014. The resource has moved to the NIDDKInformation Network (dkNET) project. Contact them at info_at_dknet.org with any questions. Database of large pools of data relevant to the mission of NIDDKwith the goal of developing a community-based network for integration across disciplines to include the larger DKuniverse of diseases, investigators, and potential users. The focus is on greater use of this data with the objective of adding value by breaking down barriers between sites to facilitate linking of different datasets. To date (2013/06/10), a total of 1,195 resources have been associated with one or more genes. Of 11,580 total genes associated with resources, the ten most represented are associated with 359 distinct resources. The main method by which they currently interconnect resources between the providers is via EntrezGene identifiers. A total of 780 unique genes provide the connectivity between 3,159 resource pairs across consortia. To further increase interconnectivity, the groups have been further annotating their data with additional gene identifiers, publications, and ontology terms from selected Open Biological and Biomedical Ontologies (OBO).

Proper citation: dkCOIN (RRID:SCR_004438) Copy   

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http://bioinfo.au.tsinghua.edu.cn/software/TAGS/

Software tool for gene set enrichment analysis for expression time series, which can incorporate existing knowledge and analyze the dynamic property of a group of genes that have functional or structural associations. The installation file is for Windows., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: TAGS (RRID:SCR_004294) Copy   

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http://nematode.lab.nig.ac.jp/

Expression pattern map of the 100Mb genome of the nematode Caenorhabditis elegans through EST analysis and systematic whole mount in situ hybridization. NEXTDB is the database to integrate all information from their expression pattern project and to make the data available to the scientific community. Information available in the current version is as follows: * Map: Visual expression of the relationships among the cosmids, predicted genes and the cDNA clones. * Image: In situ hybridization images that are arranged by their developmental stages. * Sequence: Tag sequences of the cDNA clones are available. * Homology: Results of BLASTX search are available. Users of the data presented on our web pages should not publish the information without our permission and appropriate acknowledgment. Methods are available for: * In situ hybridization on whole mount embryos of C.elegans * Protocols for large scale in situ hybridization on C.elegans larvae

Proper citation: NEXTDB (RRID:SCR_004480) Copy   

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http://stemcellcommons.org/

Open source environment for sharing, processing and analyzing stem cell data bringing together stem cell data sets with tools for curation, dissemination and analysis. Standardization of the analytical approaches will enable researchers to directly compare and integrate their results with experiments and disease models in the Commons. Key features of the Stem Cell Commons * Contains stem cell related experiments * Includes microarray and Next-Generation Sequencing (NGS) data from human, mouse, rat and zebrafish * Data from multiple cell types and disease models * Carefully curated experimental metadata using controlled vocabularies * Export in the Investigation-Study-Assay tabular format (ISA-Tab) that is used by over 30 organizations worldwide * A community oriented resource with public data sets and freely available code in public code repositories such as GitHub Currently in development * Development of Refinery, a novel analysis platform that links Commons data to the Galaxy analytical engine * ChIP-seq analysis pipeline (additional pipelines in development) * Integration of experimental metadata and data files with Galaxy to guide users to choose workflows, parameters, and data sources Stem Cell Commons is based on open source software and is available for download and development.

Proper citation: Stem Cell Commons (RRID:SCR_004415) Copy   

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http://en.wikibooks.org/wiki/Handbook_of_Genetic_Counseling

The Handbook of Genetic Counseling is a wikibook designed as an introduction to the discipline and practice of genetic counseling. The text provides an introduction to genetic counseling as a clinical practice and includes sample counseling outlines and letters for students of genetic counseling. Additional outline and letter examples are highly encouraged. Wikibooks contains books on many medical topics; however, no warranty whatsoever is made that any of the books are accurate.

Proper citation: Handbook of Genetic Counseling (RRID:SCR_004564) Copy   

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

Database that provides access to biological systems and their component genes, proteins, and small molecules, as well as literature describing those biosystems and other related data throughout Entrez. A biosystem, or biological system, is a group of molecules that interact directly or indirectly, where the grouping is relevant to the characterization of living matter. BioSystem records list and categorize components, such as the genes, proteins, and small molecules involved in a biological system. The companion FLink tool, in turn, allows you to input a list of proteins, genes, or small molecules and retrieve a ranked list of biosystems. A number of databases provide diagrams showing the components and products of biological pathways along with corresponding annotations and links to literature. This database was developed as a complementary project to (1) serve as a centralized repository of data; (2) connect the biosystem records with associated literature, molecular, and chemical data throughout the Entrez system; and (3) facilitate computation on biosystems data. The NCBI BioSystems Database currently contains records from several source databases: KEGG, BioCyc (including its Tier 1 EcoCyc and MetaCyc databases, and its Tier 2 databases), Reactome, the National Cancer Institute's Pathway Interaction Database, WikiPathways, and Gene Ontology (GO). It includes several types of records such as pathways, structural complexes, and functional sets, and is desiged to accomodate other record types, such as diseases, as data become available. Through these collaborations, the BioSystems database facilitates access to, and provides the ability to compute on, a wide range of biosystems data. If you are interested in depositing data into the BioSystems database, please contact them.

Proper citation: NCBI BioSystems Database (RRID:SCR_004690) Copy   

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http://www.ebi.ac.uk/QuickGO/

A web-based browser for Gene Ontology terms and annotations, which is provided by the UniProtKB-GOA group at the EBI. It is able to offer a range of facilities including bulk downloads of GO annotation data which can be extensively filtered by a range of different parameters and GO slim set generation. The software for QuickGO is freely available under the Apache 2 license. QuickGO can supply GO term information and GO annotation data via REST web services.

Proper citation: QuickGO (RRID:SCR_004608) Copy   

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http://openflydata.org/

A cross-database search service for Drosophila gene expression data, including microarray data from FlyAtlas and in situ images from BDGP and Fly-TED. The applications provide different ways to search for and compare gene expression data for the fruit fly Drosophila melanogaster. You may Search Gene Expression Data by Gene, Gene Batch, and by Tissue Expression Profile. A number of Web services (SPARQL endpoints) are provided from this site which may be queried programmatically for data.

Proper citation: OpenFlyData.org (RRID:SCR_004807) Copy   

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http://www.genmapp.org/

GenMAPP is a free computer application designed to visualize gene expression and other genomic data on maps representing biological pathways and groupings of genes. Integrated with GenMAPP are programs to perform a global analysis of gene expression or genomic data in the context of hundreds of pathway MAPPs and thousands of Gene Ontology Terms (MAPPFinder), import lists of genes/proteins to build new MAPPs (MAPPBuilder), and export archives of MAPPs and expression/genomic data to the web. The main features underlying GenMAPP are: *Draw pathways with easy to use graphics tools *Color genes on MAPP files based on user-imported genomic data *Query data against MAPPs and the GeneOntology Enhanced features include the simultaneous view of multiple color sets, expanded species-specific gene databases and custom database options.

Proper citation: Gene Map Annotator and Pathway Profiler (RRID:SCR_005094) Copy   

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http://glioblastoma.alleninstitute.org/

Platform for exploring the anatomic and genetic basis of glioblastoma at the cellular and molecular levels that includes two interactive databases linked together by de-identified tumor specimen numbers to facilitate comparisons across data modalities: * The open public image database, here, providing in situ hybridization data mapping gene expression across the anatomic structures inherent in glioblastoma, as well as associated histological data suitable for neuropathological examination * A companion database (Ivy GAP Clinical and Genomic Database) offering detailed clinical, genomic, and expression array data sets that are designed to elucidate the pathways involved in glioblastoma development and progression. This database requires registration for access. The hope is that researchers all over the world will mine these data and identify trends, correlations, and interesting leads for further studies with significant translational and clinical outcomes. The Ivy Glioblastoma Atlas Project is a collaborative partnership between the Ben and Catherine Ivy Foundation, the Allen Institute for Brain Science and the Ben and Catherine Ivy Center for Advanced Brain Tumor Treatment.

Proper citation: Ivy Glioblastoma Atlas Project (RRID:SCR_005044) Copy   

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http://variant.bioinfo.cipf.es/

Analysis tool that can report the functional properties of any variant in all the human, mouse or rat genes (and soon new model organisms will be added) and the corresponding neighborhoods. Also other non-coding extra-genic regions, such as miRNAs are included in the analysis. It not only reports the obvious functional effects in the coding regions but also analyzes noncoding SNVs situated both within the gene and in the neighborhood that could affect different regulatory motifs, splicing signals, and other structural elements. These include: Jaspar regulatory motifs, miRNA targets, splice sites, exonic splicing silencers, calculations of selective pressures on the particular polymorphic positions, etc. Software analysis pipelines used in the analysis of NGS data are highly modular, heterogeneous, and rapidly evolving. VARIANT can easily be incorporated into a NGS resequencing pipeline either as a CLI or invoked a webservice. It inputs data directly from the most widely used programs for SNV detection., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: VARIANT (RRID:SCR_005194) Copy   

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http://www.pazar.info/

Database that unites independently created and maintained data collections of transcription factor and regulatory sequence annotation. The flexible PAZAR schema permits the representation of diverse information derived from experiments ranging from biochemical protein-DNA binding to cellular reporter gene assays. Data collections can be made available to the public, or restricted to specific system users. The data ''boutiques'' within the shopping-mall-inspired system facilitate the analysis of genomics data and the creation of predictive models of gene regulation., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: PAZAR (RRID:SCR_005410) Copy   

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http://www.gene-regulation.com/pub/databases.html#transpath

Database on eukaryotic transcription factors, their experimentally-proven binding sites, consensus binding sequences (positional weight matrices) and regulated genes. Its broad compilation of binding sites allows the derivation of positional weight matrices. It can either be used as an encyclopedia, for both specific and general information on signal transduction, or can serve as a network analyzer. Cross-references to important sequence and signature databases such as EMBL/GenBank UniProt/Swiss-Prot InterPro or Ensembl EntrezGene RefSeq are provided. The database is equipped with the tools for data visualization and analysis. It has three modules: the first one is the data, which have been manually extracted, mostly from the primary literature; the second is PathwayBuilder, which provides several different types of network visualization and hence facilitates understanding; the third is ArrayAnalyzer, which is particularly suited to gene expression array interpretation, and is able to identify key molecules within signalling networks (potential drug targets). These key molecules could be responsible for the coordinated regulation of downstream events. Manual data extraction focuses on direct reactions between signalling molecules and the experimental evidence for them, including species of genes/proteins used in individual experiments, experimental systems, materials and methods. This combination of materials and methods is used in TRANSPATH to assign a quality value to each experimentally proven reaction, which reflects the probability that this reaction would happen under physiological conditions. Another important feature in TRANSPATH is the inclusion of transcription factor-gene relations, which are transferred from TRANSFAC, a database focused on transcription regulation and transcription factors. Since interactions between molecules are mainly direct, this allows a complete and stepwise pathway reconstruction from ligands to regulated genes.

Proper citation: TRANSPATH (RRID:SCR_005640) Copy   

•   Source: SciCrunch Registry

http://llama.mshri.on.ca/synergizer/translate/

The Synergizer database is a growing repository of gene and protein identifier synonym relationships. This tool facilitates the conversion of identifiers from one naming scheme (a.k.a namespace) to another. The Synergizer is a service for translating between sets of biological identifiers. It can, for example, translate Ensembl Gene IDs to Entrez Gene IDs, or IPI IDs to HGNC gene symbols, and much more. Unlike some other tools for this purpose, The Synergizer is simple and easy to learn. The Synergizer works via a web interface (for users who are not programmers) or through a web service (for programmatic access).

Proper citation: Synergizer (RRID:SCR_005308) Copy   

•   Source: SciCrunch Registry

http://www.nimh.nih.gov/educational-resources/brain-basics/brain-basics.shtml

Brain Basics provides information on how the brain works, how mental illnesses are disorders of the brain, and ongoing research that helps us better understand and treat disorders. Mental disorders are common. You may have a friend, colleague, or relative with a mental disorder, or perhaps you have experienced one yourself at some point. Such disorders include depression, anxiety disorders, bipolar disorder, attention deficit hyperactivity disorder (ADHD), and many others. Some people who develop a mental illness may recover completely; others may have repeated episodes of illness with relatively stable periods in between. Still others live with symptoms of mental illness every day. They can be moderate, or serious and cause severe disability. Through research, we know that mental disorders are brain disorders. Evidence shows that they can be related to changes in the anatomy, physiology, and chemistry of the nervous system. When the brain cannot effectively coordinate the billions of cells in the body, the results can affect many aspects of life. Scientists are continually learning more about how the brain grows and works in healthy people, and how normal brain development and function can go awry, leading to mental illnesses. Brain Basics will introduce you to some of this science, such as: * How the brain develops * How genes and the environment affect the brain * The basic structure of the brain * How different parts of the brain communicate and work with each other * How changes in the brain can lead to mental disorders, such as depression.

Proper citation: Brain Basics (RRID:SCR_005606) Copy   

•   Source: SciCrunch Registry