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http://ailun.stanford.edu/

Re-annotated gene expression / proteomics data from GEO by relating all probe IDs to Entrez Gene IDs once every three months, enabling you to find data from GEO, and compare them from different platforms and species. Platform Annotations adds the latest annotations to any uploaded probe / gene ID list file. Platform Comparison compares any two platforms to find corresponding probes mapping to the same gene. Cross-species mapping maps platform annotations to other species. Gene Search finds deposited platforms and samples in GEO that contain a list of genes. GPL ID Search finds the GPL ID (GEO platform ID) for your array. You can also download the latest annotations files for all arrays and their comprehensive universal gene identifier table, which relates all types of gene / protein / clone identifiers to Entrez Gene IDs for all species. Note: The database was last updated on 4/30/2011. They have successfully mapped 54932732 individual probes from 385099 GEO samples measuring 3519 GEO platforms across 217 species.

Proper citation: Array Information Library Universal Navigator (RRID:SCR_006967) Copy   

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http://androgendb.mcgill.ca/

Comprehensive listing of androgen receptor gene mutations published in journals and meetings proceedings. The majority of mutations are point mutations identified in patients with androgen insensitivity syndrome. Information is included regarding the phenotype, the nature and location of the mutations, as well as the effects of the mutations on the androgen binding activity of the receptor. In light of the difficulty in getting new AR mutations published the curator will now accept new mutations that have not been published, provided that it is from a reputable research or clinical laboratory. The database incorporates information on the exon 1 CAG repeat expansion disease, spinobulbar muscular atrophy (SBMA), as well as CAG repeat length variations associated with risk for female breast, uterine endometrial, colorectal, and prostate cancer, as well as for male infertility. The possible implications of somatic mutations, as opposed to germline mutations, in the development of future locus-specific mutation databases (LSDBs) is discussed.
The database now provides information on the external genitalia and on sex - of - rearing. Additionally, the new version of the database has an entry to show if pathogenicity has been proven. A pdf and fully searchable version of the Database is available for download.

Proper citation: Androgen Receptor Gene Mutations Database (RRID:SCR_006887) Copy   

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http://humancyc.org/

The HumanCyc database describes human metabolic pathways and the human genome. By presenting metabolic pathways as an organizing framework for the human genome, HumanCyc provides the user with an extended dimension for functional analysis of Homo sapiens at the genomic level. A computational pathway analysis of the human genome assigned human enzymes to predicted metabolic pathways. Pathway assignments place genes in their larger biological context, and are a necessary step toward quantitative modeling of metabolism. HumanCyc contains the complete genome sequence of Homo sapiens, as presented in Build 31. Data on the human genome from Ensembl, LocusLink and GenBank were carefully merged to create a minimally redundant human gene set to serve as an input to SRI''s PathoLogic software, which generated the database and predicted Homo sapiens metabolic pathways from functional information contained in the genome''s annotation. SRI did not re-annotate the genome, but worked with the gene function assignments in Ensembl, LocusLink, and GenBank. The resulting pathway/genome database (PGDB) includes information on 28,783 genes, their products and the metabolic reactions and pathways they catalyze. Also included are many links to other databases and publications. The Pathway Tools software/database bundle includes HumanCyc and the Pathway Tools software suite and is available under license. This form of HumanCyc is faster and more powerful than the Web version.

Proper citation: HumanCyc: Encyclopedia of Homo sapiens Genes and Metabolism (RRID:SCR_007050) Copy   

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http://www.microrna.org

Database of microRNA target predictions and expression profiles. Target predictions are based on a development of the miRanda algorithm which incorporates current biological knowledge on target rules and on the use of an up-to-date compendium of mammalian microRNAs. MicroRNA expression profiles are derived from a comprehensive sequencing project of a large set of mammalian tissues and cell lines of normal and disease origin. This website enables users to explore: * The set of genes that are potentially regulated by a particular microRNA. * The implied cooperativity of multiple microRNAs on a particular mRNA. * MicroRNA expression profiles in various mammalian tissues. The web resource provides users with functional information about the growing number of microRNAs and their interaction with target genes in many species and facilitates novel discoveries in microRNA gene regulation. The microRNA Target Detection Software, miRanda, is an algorithm for finding genomic targets for microRNAs. This algorithm has been written in C and is available as an open-source method under the GPL., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: microRNA.org (RRID:SCR_006997) 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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http://bioinfo.cau.edu.cn/agriGO/

A web-based tool and database for the gene ontology analysis. Its focus is on agricultural species and is user-friendly. The agriGO is designed to provide deep support to agricultural community in the realm of ontology analysis. Compared to other available GO analysis tools, unique advantages and features of agriGO are: # The agriGO especially focuses on agricultural species. It supports 45 species and 292 datatypes currently. And agriGO is designed as an user-friendly web server. # New tools including PAGE (Parametric Analysis of Gene set Enrichment), BLAST4ID (Transfer IDs by BLAST) and SEACOMPARE (Cross comparison of SEA) were developed. The arrival of these tools provides users with possibilities for data mining and systematic result exploration and will allow better data analysis and interpretation. # The exploratory capability and result visualization are enhanced. Results are provided in different formats: HTML tables, tabulated text files, hierarchical tree graphs, and flash bar graphs. # In agriGO, PAGE and SEACOMPARE can be used to carry out cross-comparisons of results derived from different data sets, which is very important when studying multiple groups of experiments, such as in time-course research. Platform: Online tool, THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: agriGO (RRID:SCR_006989) Copy   

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http://pga.mgh.harvard.edu/primerbank/

Database of human and mouse primer pairs for gene expression analysis by polymerase chain reaction (PCR) and quantitative PCR (qPCR). A total of 306,800 primers covering most known human and mouse genes can be accessed from the PrimerBank database, together with information on these primers such as T(m), location on the transcript and amplicon size. For each gene, at least one primer pair has been designed and in many cases alternative primer pairs exist. Primers have been designed to work under the same PCR conditions, thus facilitating high-throughput QPCR. All primers in PrimerBank were carefully designed to ensure gene specificity. All experimental validation data for mouse primers are available from PrimerBank. You can submit your primers. They will be added to the database once they are properly QCd.

Proper citation: PrimerBank (RRID:SCR_006898) Copy   

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http://yetfasco.ccbr.utoronto.ca/

Collection of all available transcription factor (TF) specificities for the yeast Saccharomyces cerevisiae in Position Frequency Matrix (PFM) or Position Weight Matrix (PWM) formats. The specificities are evaluated for quality using several metrics. With this website, you can scan sequences with the motifs to find where potential binding sites lie, inspect precomputed genome-wide binding sites, find which TFs have similar motifs to one you have found, and download the collection of motifs. Submissions are welcome.

Proper citation: YeTFaSCo (RRID:SCR_006893) Copy   

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http://www.softpedia.com/get/Science-CAD/DynGO.shtml

DynGO is a client-server application that provides several advanced functionalities in addition to the standard browsing capability. DynGO allows users to conduct batch retrieval of GO annotations for a list of genes and gene products, and semantic retrieval of genes and gene products sharing similar GO annotations (which requires more disk and memory to handle the semantic retrieval). The result are shown in an association tree organized according to GO hierarchies and supported with many dynamic display options such as sorting tree nodes or changing orientation of the tree. For GO curators and frequent GO users, DynGO provides fast and convenient access to GO annotation data. DynGO is generally applicable to any data set where the records are annotated with GO terms, as illustrated by two examples. Requirements: Java Platform: Windows compatible, Linux compatible, Unix compatible

Proper citation: DynGO (RRID:SCR_007009) Copy   

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http://mga.bionet.nsc.ru/soft/maia-1.0/

Software package of programs for complex segregation analysis in animal pedigrees.

Proper citation: MAIA (RRID:SCR_007153) Copy   

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http://www.biomanta.org/

This project encompasses development of novel biological network analysis methods and infrastructure for querying biological data in a semantically-enabled format, and aims to create a semantic interactome model. Research within the BioMANTA project will focus on computational modelling and analysis, primarily using Semantic Web technologies and Machine Learning methods, of large-scale protein-protein interaction and compound activity networks across a wide variety of species. A range of information such as kinetic activity, tissue expression, and subcellular localization and disease state attributes will be included in the resulting data model. Protein interactions are a fundamental component of biological processes. Many proteins are functional only in multimeric complexes, or require interaction partners to achieve their correct localisation or function. For this reason, the study of protein-protein interaction (PPI) networks has become an area of growing interest in computational biology. Through the use of Semantic Web technologies such as Resource Description Framework (RDF) and Web Ontology Language (OWL), interaction data is modelled to create a knowledge representation in which meaning is vested in the ontology rather than instances of data. Stochastic and computational intelligence methods are applied to this data to infer high coverage networks. Semantic inferencing is used to infer previously unknown and meaningful pathways. Major project components: - The BioMANTA Ontology:- An OWL DL ontology incorporating the PSI-MI Ontology, the NCBI Taxonomy, and elements of BioPax ontology and Gene Ontology (describing subcellular localisation). This allows us to re-use existing ontologies, thereby reducing overheads associated with knowledge acquisition in the ontology development process. We are able to integrate existing public data that contain annotation in these formats. - Data conversion & semantic protein integration:- A set of software components that convert protein-protein databases (DIP, MPact, IntAct, etc.) from PSI-MI XML to RDF compliant with the BioMANTA ontology. These software allow us to make these protein-protein interaction datasets (and more generally, any PSI-MI XML data) semantically available for querying and inference within BioMANTA. - A RDF triple store based on RDF Molecules and the MapReduce architecture:- A proof-of-concept RDF triple store using RDF molecules and Hadoop scale-out architectures. Regular RDF graphs are deconstructed into RDF molecules, which are distributed over distributed compute nodes in the MapReduce architecture, and are subsequently combined to form equivalent RDF graphs. Such an approach makes the distributed SPARQL querying and reasoning on RDF triple stores possible. - A quantitative framework to integrate networks extracted from independent data sources (gene expression, subcellular localization, and ortholog mapping):- The model is multi-layer, with a first layer based on Decision Trees where each Decision tree is built on each dataset independently. The tree nodes are cut using Shannon''s entropy (mutual information); the decision of these independent trees is integrated using logistic regression, and the parameters are optimised using maximum likelihood. Sponsors: This resource is supported by the Pfizer Global Research and Development, the Institute for Molecular Bioscience (IMB), and the University of Queensland, Australia.

Proper citation: BioMANTA (RRID:SCR_007177) Copy   

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http://sites.huji.ac.il/malaria/

Data set of metabolic pathways for the malaria parasite based on the present knowledge of parasite biochemistry and on pathways known to occur in other unicellular eukaryotes. This site extracted the pertinent information from the universal sites and presented them in an educative and informative format. The site also includes, cell-cell interactions (cytoadherence and rosetting), invasion of the erythrocyte by the parasite and transport functions. It also contains an artistic impression of the ultrastructural morphology of the interaerythrocytic cycle stages and some details about the morphology of mitochondria and the apicoplast. Most pathways are relevant to the erythrocytic phase of the parasite cycle. All maps were checked for the presence of enzyme-coding genes as they are officially annotated in the Plasmodium genome (http://plasmodb.org/). The site is constructed in a hierarchical pattern that permits logical deepening: * Grouped pathways of major chemical components or biological process ** Specific pathways or specific process *** Chemical structures of substrates and products or process **** Names of enzymes and their genes or components of process Each map is linked to other maps thus enabling to verify the origin of a substrate or the fate of a product. Clicking on the EC number that appears next to each enzyme, connects the site to BRENDA, SWISSPROT ExPASy ENZYME, PlasmoDB and to IUBMB reaction scheme. Clicking of the name of a metabolite, connects the site to KEGG thus providing its chemical structure and formula. Next to each enzyme there is a pie that depicts the stage-dependent transcription of the enzyme''s coding gene. The pie is constructed as a clock of the 48 hours of the parasite cycle, where red signifies over-transcription and green, under-transcription. Clicking on the pie links to the DeRisi/UCSF transcriptome database.

Proper citation: Malaria Parasite Metabolic Pathways (RRID:SCR_007072) Copy   

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http://www.vbase2.org/

Integrative database of germ-line V genes from the immunoglobulin loci of human and mouse. It presents V gene sequences extracted from the EMBL nucleotide sequence database and Ensembl together with links to the respective source sequences. Based on the properties of the source sequences, V genes are classified into 3 different classes: * Class 1: genomic and rearranged evidence * Class 2: genomic evidence only * Class 3: rearranged evidence only This allows careful sequence quality validation by the user. References to other immunological databases ( KABAT, IMGT/LIGM and VBASE ) are given to provide all public annotation data for each V gene. The VBASE2 database can be accessed either by the Direct Query interface or by the DNAPLOT Query interface. The Sequences given by the user are aligned with DNAPLOT against the VBASE2 database. Direct Query allows to enter sequence IDs and names (Field 1), choose species, locus, V gene family and class (Field 2) or search for 100% sequences (Field 3). At the DNAPLOT Query, the sequences given by the user are aligned with DNAPLOT against the VBASE2 database. The DNAPLOT program offers V gene nucleotide sequence alignment referring to the IMGT V gene unique numbering. The Quick Search can be used either for Direct Query to search for sequence IDs and V gene names or for DNAPLOT Query for up to 5 sequences. The new Fab Analysis allows you to align Fab, scFab, scAb or scFv sequences with DNAPLOT against the VBASE2 database, where both heavy and light chain are analyzed.

Proper citation: VBASE2 (RRID:SCR_007082) Copy   

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http://www.komp.org/

Repository of mouse vectors, ES cells, mice, embryos, and sperm generated by NIH KOMP Mutagenesis Project. In addition, KOMP Repository offers services in support of KOMP products, including ES cell microinjection, vector cloning, post-insertional modification of cloned ES cells, cryopreservation, assisted reproduction techniques (IVF, ICSI) and mouse breeding, pathology services, phenotyping services, etc. KOMP Repository is final component of more than $50 million trans-NIH initiative to increase availability of genetically altered mice and related materials. The University of California, Davis (UC Davis) and Children''s Hospital Oakland Research Institute (CHORI) in Oakland, Calif., are collaborating to preserve, protect, and make available about 8,500 types of knockout mice and related products available to research community. Products are generated by two KOMP mutagenesis teams (CSD consortium and Regeneron Inc). All KOMP products generated by CSD consortium and Regeneron are available through KOMP Repository. Notice as of December 19, 2019: Materials from KOMP Repository have been deposited into MMRRC, including all mouse models and mouse embryonic stem cell lines. Eventually www.komp.org will be sunsetting, and IMSR will remove KOMP Repository listings, since they were double listed in MMRRC. MMRRC will contain the most accurate and up to date resource models.

Proper citation: Knockout Mouse Project Repository (RRID:SCR_007318) Copy   

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http://www.hgsc.bcm.tmc.edu/content/honey-bee-genome-project

The HGSC has sequenced the honey bee, Apis mellifera. The version 4.0 assembly was released in March 2006 and published in October 2006. The genome sequence is being upgraded with additional sequence coverage. The honey bee is important in the agricultural community as a producer of honey and as a facilitator of pollination. It is a model organism for studying the following human health issues: immunity, allergic reaction, antibiotic resistance, development, mental health, longevity and diseases of the X chromosome. In addition, biologists are interested in the honey bee's social organization and behavioral traits. This project was proposed to the HGSC by a group of dedicated insect biologists, headed by Gene Robinson. Following a workshop at the HGSC and a honey bee white paper, the HGSC began the project in 2002. A 6-fold coverage WGS, BAC sequence from pooled arrays, and an initial genome assembly (Amel_v1.0) were released beginning in 2003. This has been a challenging project with difficulty in recovering AT-rich regions. The WGS data had lower coverage in AT-rich regions and BAC data from clones showed evidence of internal deletions. Additional reads from AT enriched DNA addressed these underrepresented regions. The current assembly Amel_4.0 was produced with Atlas and includes 2.7 million reads (1.8 Gb) or 7.5x coverage of the (clonable) genome. About 97% of STSs, 98% of ESTs, and 96% of cDNAs are represented in the 231 Mb assembly. About 2,500 reads were also produced from a strain of Africanized honey bee and SNPs were extracted. These were released in dbSNP and the NCBI Trace Archive. Analysis of the genome by a consortium of 20 labs has been completed. This produced a gene list derived from five different methods melded through the GLEAN software. Publications include a main paper in Nature and up to forty companion papers in Genome Research and Insect Molecular Biology. Sponsors: Sequencing of the honey bee is jointly funded by National Human Genome Research Institute (NHGRI) and the Department of Agriculture (USDA). Multiple drones from the same queen (strain DH4) were obtained from Danny Weaver of B. Weaver Apiaries. All libraries were made from DNA isolated from these drones. The honey bee BAC library (CHORI-224) was prepared by Pieter de Jong and Katzutoyo Osoegawa at the Children's Hospital Oakland Research Institute.

Proper citation: Honey Bee Genome Project (RRID:SCR_002890) Copy   

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http://www.gramene.org

Curated, open-source, integrated data resource for comparative functional genomics in crops and model plant species to facilitate the study of cross-species comparisons using information generated from projects supported by public funds. It currently hosts annotated whole genomes in over two dozen plant species and partial assemblies for almost a dozen wild rice species in the Ensembl browser, genetic and physical maps with genes, ESTs and QTLs locations, genetic diversity data sets, structure-function analysis of proteins, plant pathways databases (BioCyc and Plant Reactome platforms), and descriptions of phenotypic traits and mutations. The web-based displays for phenotypes include the Genes and Quantitative Trait Loci (QTL) modules. Sequence based relationships are displayed in the Genomes module using the genome browser adapted from Ensembl, in the Maps module using the comparative map viewer (CMap) from GMOD, and in the Proteins module displays. BLAST is used to search for similar sequences. Literature supporting all the above data is organized in the Literature database. In addition, Gramene now hosts a variety of web services including a Distributed Annotation Server (DAS), BLAST and a public MySQL database. Twice a year, Gramene releases a major build of the database and makes interim releases to correct errors or to make important updates to software and/or data. Additionally you can access Gramene through an FTP site.

Proper citation: Gramene (RRID:SCR_002829) Copy   

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https://genenames.org

Only worldwide authority that provides standardized nomenclature, i.e. gene names and symbols (short form abbreviations), for all known human genes, and stores all approved symbols in the HGNC database. Approved human gene nomenclature. Database of gene symbols and names. Manually curated genes into groups based on shared characteristics such as homology, function or phenotype. Data for protein-coding genes, pseudogenes and non-coding RNAs.

Proper citation: HGNC (RRID:SCR_002827) Copy   

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http://trans.nih.gov/bmap/resources/resources.htm

As part of BMAP gene discovery efforts, mouse brain cDNA libraries and Expressed Sequence Tags (ESTs) have been generated. Through this project a BMAP mouse brain UniGene set consisting of over 24,000 non-redundant members of unique clusters has been developed from EST sequencing of more than 50,000 cDNA clones from 10 regions of adult mouse brain, spinal cord, and retina (http://brainEST.eng.uiowa.edu/). In 2001, NIMH along with NICHD, NIDDK, and NIDA, awarded a contract to the University of Iowa ( M.B. Soares, PI) to isolate full-length cDNA clones corresponding to genes expressed in the developing mouse nervous system and determine their full-coding sequences. The BMAP mouse brain EST sequences can be accessed at NCBI's dbEST database (http://www.ncbi.nlm.nih.gov/dbEST/). Arrayed sets of BMAP mouse brain UniGenes and cDNA libraries, and individual BMAP cDNA clones can be purchased from Open Biosystems, Huntsville, AL (http://www.openbiosystems.com

Proper citation: BMAP cDNA Resources (RRID:SCR_002973) Copy   

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http://hembase.niddk.nih.gov/

Database designed for web-based examination of the human erythroid transcriptome. The database is organized to provide a cytogenetic band position, a unique name as well as a concise annotation for each entry. Search queries may be performed by name, keyword or cytogenetic location. Search results are linked to primary sequence data and three major human genome browsers for access to information considered current at the time of each search. Hembase provides interested scientists and clinical hematologists with a genome-based approach toward the study of erythroid biology. Red blood cells in the circulation arise from hematopoietic stem cells that proliferate as erythroid progenitors and differentiate into erythroid precursor cells in response to the hormone erythropoietin. Messenger RNA was isolated from those cells and used to generate gene libraries. Sequencing several thousand expressed sequence tags (EST) from those libraries was then performed. Those EST and sequences encoding several hundred additional genes with known expression in erythroid cells are compiled here as a database of human erythroid gene activity. The database is organized and linked according to the location of these sequences within the human genome., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 15,2026.

Proper citation: HemBase (RRID:SCR_002880) Copy   

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http://www.pathway.com/

The mission of Pathway Genomics is to empower you with the most secure, comprehensive and affordable personal genomic information available and to become your partner in utilizing that information to improve your health and wellness. Pathway is the only DNA testing service with an on-site federal and state CLIA-licensed laboratory. This means it offers: - Better Science: Its certified geneticists are on-staff and on-site in our own state-of-the-art laboratory in California. Their 10,600 square foot, high-complexity CLIA licensed lab facility is equipped with the latest high-throughput robotics and Affymetrix, Illumina and Sequenom genotyping equipment. As scientists committed to staying on the cutting-edge, they diligently monitor all new developments in the rapidly evolving DNA research field allowing us to provide you immediate access to more meaningful markers than any other DNA testing firm. - Better Security: Because Pathway Genomics has its own laboratory, your DNA never leaves the building, and is never shared with third parties. At Pathway Genomics the integrity of your genetic material and information are protected. Instead, enjoy the security of our proprietary DNA Lockbox. Everyone has the right to know the secrets hidden within their own DNA. That's why Pathway has created the most secure, comprehensive and affordable way to unlock those secrets. This way you can: - Identify genetic health and drug response - Personalize your medical care - Help your doctor help you - Uncover your ancestral path - Explore the traits that make you unique With Personal DNA Testing, you can take preventative steps to improve your future, and even extend your life. Pathway Genomics provides cutting-edge research and easy-to-read scientific information customized for you, and you alone, based on your genes and your lifestyle. For the first time in human history, modern science has made it possible for you to learn your genetic predisposition for more than 90 diseases and conditions, drug responses and pre-pregnancy carrier status. With this powerful knowledge and our easy-to-understand guidance, you can modify your health regime so that you may live a healthier, longer life. DNA testing will discover more about your personal heritage than you ever thought possible. We uncover your deep ancestry by taking giant leaps into the past, going back more than 10,000 years. We test both your mitochondrial DNA, which is passed down from mother to child and reveals your direct maternal ancestry; and your Y chromosome (males only), which is passed down from father to son and reveals your direct paternal ancestry. If you're like most people, you've always wondered about the genes you have inherited and what traits you will pass on to future generations. Discover your genetically inherited predispositions and characteristics and whether they are beneficial or potentially harmful. You may also find that some traits are simply fun to uncover.

Proper citation: Pathway Genomics (RRID:SCR_002883) Copy   

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