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https://nda.nih.gov/

The National Institute of Mental Health Data Archive (NDA) makes available human subjects data collected from hundreds of research projects across many scientific domains. Research data repository for data sharing and collaboration among investigators. Used to accelerate scientific discovery through data sharing across all of mental health and other research communities, data harmonization and reporting of research results. Infrastructure created by National Database for Autism Research (NDAR), Research Domain Criteria Database (RDoCdb), National Database for Clinical Trials related to Mental Illness (NDCT), and NIH Pediatric MRI Repository (PedsMRI).

Proper citation: NIMH Data Archive (RRID:SCR_004434) Copy   

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http://rgd.mcw.edu

Database for genetic, genomic, phenotype, and disease data generated from rat research. Centralized database that collects, manages, and distributes data generated from rat genetic and genomic research and makes these data available to scientific community. Curation of mapped positions for quantitative trait loci, known mutations and other phenotypic data is provided. Facilitates investigators research efforts by providing tools to search, mine, and analyze this data. Strain reports include description of strain origin, disease, phenotype, genetics, immunology, behavior with links to related genes, QTLs, sub-strains, and strain sources.

Proper citation: Rat Genome Database (RGD) (RRID:SCR_006444) Copy   

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http://www.biobankcentral.org/resource/wwibb.php

THIS RESOURCE IS NO LONGER IN SERVICE, documented on March 27, 2013. Web-based portal to connect all the constituencies in the global biobank community. The project seeks to increase the transparency and accessibility of the scientific research process by connecting researchers with an additional source of funding - microinvestments received from the broader online community. In exchange for these public investments, researchers will maintain research logs detailing the play-by-play progress made in their project, as well as publishing all of their data in a public database under a science commons license. These research projects, in turn, will serve to continually update a research-based neuroscience-based human brain & body curriculum. Biobanks are the meeting point of two major information trends in biomedical research: the generation of huge amounts of genomic and other laboratory data, and the electronic capture and integration of patient clinical records. They are comprised of large numbers of human biospecimens supplemented with clinical data. Biobanks when implemented effectively can harness the power of both genomic and clinical data and serve as a critical bridge between basic and applied research, linking laboratory to patient and getting to cures faster. As science and technology leaders work to address the many challenges facing U.S. biobanks logistical, technical, ethical, financial, intellectual property, and IT BioBank Central will serve as an accurate and timely source of knowledge and news about biorepositories and their role in research and drug development. The Web site also provides a working group venue, patient and public education programs, and a forum for international collaboration and harmonization of best practices.

Proper citation: BioBank Central (RRID:SCR_008645) Copy   

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Ratings or validation data are available for this resource

http://www.ingenuity.com/products/pathways_analysis.html

A web-based software application that enables users to analyze, integrate, and understand data derived from gene expression, microRNA, and SNP microarrays, metabolomics, proteomics, and RNA-Seq experiments, and small-scale experiments that generate gene and chemical lists. Users can search for targeted information on genes, proteins, chemicals, and drugs, and build interactive models of experimental systems. IPA allows exploration of molecular, chemical, gene, protein and miRNA interactions, creation of custom molecular pathways, and the ability to view and modify metabolic, signaling, and toxicological canonical pathways. In addition to the networks and pathways that can be created, IPA can provide multiple layering of additional information, such as drugs, disease genes, expression data, cellular functions and processes, or a researchers own genes or chemicals of interest.

Proper citation: Ingenuity Pathway Analysis (RRID:SCR_008653) Copy   

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http://genes2mind.org

genes2mind is a tool for rapid exploratory analysis of psychotropic drug-induced gene expression in the brain. We present here an open resource containing comparison of effects of various classes of psychotropic drugs on transcriptional alterations of ~20,000 genes in the mouse brain (C57BL/6J). Data stored in the database include raw gene expression values as well as results of drug comparison. * Genomic Signature Identification section allows for the identification of drug-specific genomic signatures. * Genomic Signature Analysis section allows for further inspection and visualization of the signatures using multidimensional data analysis (PCA), co-expression analysis and heatmaps. * Single Gene Inspection allows for brief review of expression of specific candidate genes using barplots.

Proper citation: genes2mind (RRID:SCR_008872) Copy   

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http://www.allelix.net

THIS RESOURCE IS NO LONGER IN SERVICE, documented on September 23, 2013. Software application / data analysis service where one can enter the alleles of commonly used STR by clicking the mouse. The algorithm calculates the paternity index and the Essen-Moeller probability of kinship for the deficiency- and the trio case. Everybody can use the network-software online after registering. The usage on the internet is free. Academic users can ask me to unlock an option to display the details (formulas/frequencies etc.) and to have an export-funktion to MS Word. The program is in German and (non-professional) English. An expansion to other languages is easy, if somebody helps us with the translation. For those who are interested to have the software running on their own intranet (for database security reasons) an individual agreement can be found. (entry from Genetic Analysis Software) (German version is: http://www.allelix.de)

Proper citation: ALLELIX (RRID:SCR_009115) Copy   

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http://wpicr.wpic.pitt.edu/WPICCompGen/bars.htm

Software application that is a statistical method that bridges the gap between single-locus and haplotype-based tests of association. It is based on the non-parametric regression techniques embodied by Bayesian Adaptive Regression Splines. (entry from Genetic Analysis Software), THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: BARS (RRID:SCR_009123) Copy   

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https://gmod.org/wiki/CMap.1

Web-based tool that allows users to view comparisons of genetic and physical maps. The package also includes tools for curating map data. (entry from Genetic Analysis Software)

Proper citation: CMAP (RRID:SCR_009034) Copy   

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https://wiki.nci.nih.gov/display/caGWAS/caGWAS

Too that allows researchers to integrate, query, report, and analyze significant associations between genetic variations and disease, drug response or other clinical outcomes. SNP array technologies make it possible to genotype hundreds of thousands of single nucleotide polymorphisms (SNPs) simultaneously, enabling whole genome association studies. Within the Clinical Genomic Object Model (CGOM), the caIntegrator team created a domain model for Whole Genome Association Study Analysis. CGOM-caGWAS is a A semantically annotated domain model that captures associations between Study, Study Participant, Disease, SNP Association Analysis, SNP Population Frequency and SNP annotations. caGWAS APIs and web portal provide: * a semantically annotated domain model, database schema with sample data, seasoned middleware, APIs, and web portal for GWAS data; * platform and disease agnostic CGOM-caGWAS model and associated APIs; * the opportunity for developers to customize the look and feel of their GWAS portal; * a foundation of open source technologies; * a well-tested and performance-enhanced platform, as the same software is being used to house the CGEMS data portal; * accelerated analysis of results from various biomedical studies; and * a single application through which researchers and bioinformaticians can access and analyze clinical and experimental data from a variety of data types, as caGWAS objects are part of the CGOM, which includes microarray, genomic, immunohistochemistry, imaging, and clinical data.

Proper citation: caGWAS (RRID:SCR_009617) Copy   

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http://www.mogene.com/

Core provides services to its partners in deploying genomic capabilities to bring critical solutions to both agriculture and industrial biotech operations. Core facility also provides assistance to research, biotech/pharma and government facilities. In addition to being an Agilent Certified Service Provider MOgene is also a CLIA certified genomics service facility offering one stop service and solution from Tissue/Cells to Analysis. Core offers RNA/DNA isolation, Microarrays, NextGen sequencing, Real time PCR and bioinformatics services.

Proper citation: MOgene (RRID:SCR_012433) Copy   

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http://www.geisha.arizona.edu/geisha/

Online repository for chicken in situ hybridization information. This site presents whole mount in situ hybridization images and corresponding probe and genomic information for genes expressed in chicken embryos in Hamburger Hamilton stages 1-25 (0.5-5 days). The GEISHA project began in 1998 to investigate using high throughput whole mount in situ hybridization to identify novel, differentially expressed genes in chicken embryos. An initial expression screen of approximately 900 genes demonstrated feasibility of the approach, and also highlighted the need for a centralized repository of in situ hybridization expression data. Objectives: The goals of the GEISHA project are to obtain whole mount in situ hybridization expression information for all differentially expressed genes in the chicken embryo between HH stages 1-25, to integrate expression data with the chicken genome browsers, and to offer this information through a user-friendly graphical user interface. In situ hybridization images are obtained from three sources: 1. In house high throughput in situ hybridization screening: cDNAs obtained from several embryonic cDNA libraries or from EST repositories are screened for expression using high throughput in situ hybridization approaches. 2. Literature curation: Agreements with journals permit posting of published in situ hybridization images and related information on the GEISHA site. 3. Unpublished in situ hybridization information from other laboratories: laboratories generally publish only a small fraction of their in situ hybridization data. High quality images for which probe identity can be verified are welcome additions to GEISHA.

Proper citation: GEISHA - Gallus Expression in Situ Hybridization Analysis: A Chicken Embryo Gene Expression Database (RRID:SCR_007440) Copy   

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http://www.genomesize.com

Comprehensive catalogue of animal genome size data. Haploid DNA contents (C-values, in picograms) are available for 4972 species (3231 vertebrates and 1741 non-vertebrates) based on 6518 records from 669 published sources. Data may be submitted directly to the database or reprints and notifications of new papers may be sent to database curation staff.

Proper citation: Animal Genome Size Database (RRID:SCR_007551) Copy   

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http://claire.bardel.free.fr/software.html

Software package to perform phylogeny based association and localization analysis.Used for association detection and localization of susceptibility sites using haplotype phylogenetic trees. Performs these two phylogeny-based analysis: tests association between candidate gene and disease; pinpoints markers (SNPs) that are putative disease susceptibility loci.

Proper citation: ALTree (RRID:SCR_007562) Copy   

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http://mitores.ba.itb.cnr.it

MitoRes, is a comprehensive and reliable resource for massive extraction of sequences and sub-sequences of nuclear genes and encoded products targeting mitochondria in metazoa. It has been developed for supporting high-throughput in-silico analyses aimed to studies of functional genomics related to mitochondrial biogenesis, metabolism and to their pathological dysfunctions. It integrates information from the most accredited world-wide databases to bring together gene, transcript and encoded protein sequences associated to annotations on species name and taxonomic classification, gene name, functional product, organelle localization, protein tissue specificity, Enzyme Classification (EC), Gene Ontology (GO) classification and links to other related public databases. The section Cluster, has been dedicated to the collection of data on protein clustering of the entire catalogue of MitoRes protein sequences based on all versus all global pair-wise alignments for assessing putative intra- and inter-species functional relationships. The current version of MitoRes is based on the UniProt release 4 and contains 64 different metazoan species. The incredible explosion of knowledge production in Biology in the past two decades has created a critical need for bioinformatic instruments able to manage data and facilitate their retrieval and analysis. Hundreds of biological databases have been produced and the integration of biological data from these different resources is very important when we want to focus our efforts towards the study of a particular layer of biological knowledge. MitoRes is a completely rebuilt edition of MitoNuc database, which has been extensively modified to deal successfully with the challenges of the post genomic era. Its goal is to represent a comprehensive and reliable resource supporting high-quality in-silico analyses aimed to the functional characterization of gene, transcript and amino acid sequences, encoded by the nuclear genome and involved in mitochondrial biogenesis, metabolism and pathological dysfunctions in metazoa. The central features of MitoRes are: # an integrated catalogue of protein, transcript and gene sequences and sub-sequences # a Web-based application composed of a wide spectrum of search/retrieval facilities # a sequence export manager allowing massive extraction of bio-sequences (genes, introns, exons, gene flanking regions, transcripts, UTRs, CDS, proteins and signal peptides) in FASTA, EMBL and GenBank formats. It is an interconnected knowledge management system based on a MySQL relational database, which ensures data consistency and integrity, and on a Web Graphical User Interface (GUI), built in Seagull PHP Framework, offering a wide range of search and sequence extraction facilities. The database is compiled extracting and integrating information from public resources and data generated by the MitoRes team. The MitoRes database consists of comprehensive sequence entries whose core data are protein, transcript and gene sequences and taxonomic information describing the biological source of the protein. Additional information include: bio-sequences structure and location, biological function of protein product and dynamic links to both, external public databases used as data resources and public databases reporting complementary information. The core entity of the MitoRes database is represented by the protein so that each MitoRes entry is generated for each protein reported in the UniProt database as a nuclear encoded protein involved in mitochondrial biogenesis and function. Sponsors: MitoRes has been supported by Ministero Universit e Ricerca Scientifica, Italy (PRIN, Programma Biotecnologie legge 95/95-MURST 5, Proiect MURST Cluster C03/2000, CEGBA). Currently it is supported by operating grants from the Ministero dellIstruzione, dellUniversit e della Ricerca (MIUR), Italy (PNR 2001-2003 (FIRB art.8) D.M. 199, Strategic Program: Post-genome, grant 31-063933 and Project n.2, Cluster C03 L. 488/929).

Proper citation: MitoRes (RRID:SCR_008208) Copy   

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http://medblast.sibsnet.org/

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 29, 2016. An algorithm that finds articles most relevant to a genetic sequence. In the genomic era, researchers often want to know more information about a biological sequence by retrieving its related articles. However, there is no available tool yet to achieve conveniently this goal. Here, a new literature-mining tool MedBlast is developed, which uses natural language processing techniques, to retrieve the related articles of a given sequence. An online server of this program is also provided. The genome sequencing projects generate such a large amount of data every day that many molecular biologists often encounter some sequences that they know nothing about. Literature is usually the principal resource of such information. It is relatively easy to mine the articles cited by the sequence annotation; however, it is a difficult task to retrieve those relevant articles without direct citation relationship. The related articles are those described in the given sequence (gene/protein), or its redundant sequences, or the close homologs in various species. They can be divided into two classes: direct references, which include those either cited by the sequence annotation or citing the sequence in its text; indirect references, those which contain gene symbols of the given sequence. A few additional issues make the task even more complicated: (1) symbols may have aliases; and (2) one sequence may have a couple of relatives that we want to take into account too, which include redundant (e.g. protein and gene sequences) and close homologs. Here the issues are addressed by the development of the software MedBlast, which can retrieve the related articles of the given sequence automatically. MedBlast uses BLAST to extend homology relationships, precompiled species-specific thesauruses, a useful semantics technique in natural language processing (NLP), to extend alias relationship, and EUtilities toolset to search and retrieve corresponding articles of each sequence from PubMed. MedBlast take a sequence in FASTA format as input. The program first uses BLAST to search the GenBank nucleic acid and protein non-redundant (nr) databases, to extend to those homologous and corresponding nucleic acid and protein sequences. Users can input the BLAST results directly, but it is recommended to input the result of both protein and nucleic acid nr databases. The hits with low e-values are chosen as the relatives because the low similarity hits often do not contain specific information. Very long sequences, e.g. 100k, which are usually genomic sequences, are discarded too, for they do not contain specific direct references. User can adjust these parameters to meet their own needs.

Proper citation: MedBlast (RRID:SCR_008202) Copy   

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http://www.ebi.ac.uk/parasites/parasite-genome.html

This website contains information about the genomic sequence of parasites. It also contains multiple search engines to search six frame translations of parasite nucleotide databases for motifs, parasite protein databases for motifs, and parasite protein databases for keywords and text terms. * Guide to Internet Access to Parasite Genome Information * Guide to web-based analysis tools * Parasite Genome BLAST Server: Search a range of parasite specific nucleotide sequence databases with your own sequence. * Parasite Proteome Keyword Search Facility: Search parasite protein databases for keywords and text terms * Parasite Proteome Motif Search Facility: Search parasite protein databases for motifs * Parasite Six Frame Translation Motif Search Facility: Search six frame translations of parasite nucleotide databases for motifs * Genome computing resources: A list of ftp and gopher sites where genome computing applications and other resources can be found.

Proper citation: Parasite genome databases and genome research resources (RRID:SCR_008150) Copy   

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http://www.jcsg.org/

The JCSG is a multi-institutional consortium that aims to explore the expanding protein universe to find new challenges and opportunities to significantly contribute to new biology, chemistry and medicine through development of HT approaches to structural genomics. The mission of JCSG is to to operate a robust HT protein structure determination pipeline as a large-scale production center for PSI-2. A major goal is to ensure that innovative high-throughput approaches are developed that advance not only structural genomics, but also structural biology in general, via investigation of large numbers of high-value structures that populate protein fold and family space and by increasing the efficiency of structure determination at substantially reduced cost. The JCSG centralizes each core activity into single dedicated sites, each handling distinct, but interconnected objectives. This unique approach allows each specialized group to focus on its own area of expertise and provides well-defined interfaces among the groups. In addition, this approach addresses the requirements for the scalability needed to process large numbers of targets at a greatly reduced cost per target. JCSG production groups are: - Administrative Core - Bioinformatics Core - Crystallomics Core - Structure Determination Core - NMR Core JCSG is deeply committed to the development of new technologies that facilitate high throughput structural genomics. The areas of development include hardware, software, new experimental methods, and adaptation of existing technologies to advance genome research. In the hardware arena, their commitment is to the development of technologies that accelerate structure solution by increasing throughput rates at every stage of the production pipeline. Therefore, one major area of hardware development has been the implementation of robotics. In the software arena, they have developed enterprise resource software that track success, failures, and sample histories from target selection to PDB deposition, annotation and target management tools, and helper applications aimed at facilitating and automating multiple steps in the pipeline. Sponsors: The Joint Center for Structural Genomics is funded by the National Institute of General Medical Sciences (NIGMS), as part of the second phase of the Protein Structure Initiative (PSI) of the National Institutes of Health (U54 GM074898).

Proper citation: Joint Center for Structural Genomics (RRID:SCR_008251) Copy   

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http://ccm.ucdavis.edu/

The University of California Davis Center for Comparative Medicine (CCM) is a cooperative, interdisciplinary research and teaching center that is co-sponsored by the School of Medicine and the School of Veterinary Medicine. CCM Faculty members have academic appointments in one or both Schools. The CCM Research Mission is to investigate the pathogenesis of human and animal disease, using animal models or naturally occurring animal diseases. Areas of emphasis include host-agent interactions during infectious disease, intervention and prevention strategies for infectious diseases, cancer, and mouse biology. CCM faculty contribute a broad range of expertise to these areas, including the disciplines of immunology, genomics, pathology, biochemistry, physiology, microbiology, molecular virology, and informatics. Through its robust and interdisciplinary research programs, the CCM provides a rich academic environment for teaching at the professional, graduate, and post-graduate levels within the School of Medicine and School of Veterinary Medicine. Opportunities are available for professional students from both schools to gain research experience. PhD candidates can pursue training opportunities in the CCMs faculty-sponsored research laboratories, with support from a number of training grants. This diverse research environment is intended to attract and train high-quality candidates to the disciplines of comparative medicine, independent and collaborative research, and mouse biology. Sponsors: CCM is supported by UC Davis.

Proper citation: University of California Davis Center for Comparative Medicine (RRID:SCR_008294) Copy   

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http://bar.utoronto.ca/welcome.htm

Web-based tools for working with functional genomics and other data, including Gene Expression and Protein Tools, Molecular Markers and Mapping Tools, and Other Genomic Tools. Most are designed with the plant (mainly Arabidopsis) researcher in mind, but a couple of them can be useful to the wider research community, e.g. Mouse eFP Browser or BlastDigester. The associated paper for most tools is available.

Proper citation: BAR (RRID:SCR_006748) Copy   

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http://goblet.molgen.mpg.de/cgi-bin/goblet2008/goblet.cgi

Tool that performs annotation based on GO and pathway terms for anonymous cDNA or protein sequences. It uses the species independent GO structure and vocabulary together with a series of protein databases collected from various sites, to perform a detailed GO annotation by sequence similarity searches. The sensitivity and the reference protein sets can be selected by the user. GOblet runs automatically and is available as a public service on our web server. GOblet expects query sequences to be in FASTA-Format (with header-lines). Protein and nucleotide sequences are accepted. Total size of all sequences submitted per request should not be larger than 50kb currently. For security reasons: Larger post's will be rejected. Due to limited capacities the queries may be processed in batches depending on the server load. The output of the BLAST job is filtered automatically and the relevant hits are displayed. In addition, the respective GO-terms are shown together with the complete GO-hierarchy of parent terms., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: GOblet (RRID:SCR_006998) Copy   

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