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http://www.ifti.org/

A resource for information pertaining to methodologies, tools and technologies of gene expression. The website offers resources for sequence analysis, database services, and other technologies of gene expression and regulation.

Proper citation: IFTI-Mirage (RRID:SCR_000505) Copy   

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http://biosciencedbc.jp/

The National Bioscience Database Center (NBDC) intends to integrate all databases for life sciences in Japan, by linking each database with expediency to maximize convenience and make the entire system more user-friendly. We aim to focus our attention on the needs of the users of these databases who have all too often been neglected in the past, rather than the needs of the people tasked with the creation of databases. It is important to note that we will continue to honor the independent integrity of each database that will contribute to our endeavor, as we are fully aware that each database was originally crafted for specific purposes and divergent goals. Services: * Database Catalog - A catalog of life science related databases constructed in Japan that are also available in English. Information such as URL, status of the database site (active vs. inactive), database provider, type of data and subjects of the study are contained for each database record. * Life Science Database Cross Search - A service for simultaneous searching across scattered life-science databases, ranging from molecular data to patents and literature. * Life Science Database Archive - maintains and stores the datasets generated by life scientists in Japan in a long-term and stable state as national public goods. The Archive makes it easier for many people to search datasets by metadata in a unified format, and to access and download the datasets with clear terms of use. * Taxonomy Icon - A collection of icons (illustrations) of biological species that is free to use and distribute. There are more than 200 icons of various species including Bacteria, Fungi, Protista, Plantae and Animalia. * GenLibi (Gene Linker to bibliography) - an integrated database of human, mouse and rat genes that includes automatically integrated gene, protein, polymorphism, pathway, phenotype, ortholog/protein sequence information, and manually curated gene function and gene-related or co-occurred Disease/Phenotype and bibliography information. * Allie - A search service for abbreviations and long forms utilized in life sciences. It provides a solution to the issue that many abbreviations are used in the literature, and polysemous or synonymous abbreviations appear frequently, making it difficult to read and understand scientific papers that are not relevant to the reader's expertise. * inMeXes - A search service for English expressions (multiple words) that appear no less than 10 times in PubMed/MEDLINE titles or abstracts. In addition, you can easily access the sentences where the expression was used or other related information by clicking one of the search results. * HOWDY - (Human Organized Whole genome Database) is a database system for retrieving human genome information from 14 public databases by using official symbols and aliases. The information is daily updated by extracting data automatically from the genetic databases and shown with all data having the identifiers in common and linking to one another. * MDeR (the MetaData Element Repository in life sciences) - a web-based tool designed to let you search, compare and view Data Elements. MDeR is based on the ISO/IEC 11179 Part3 (Registry metamodel and basic attributes). * Human Genome Variation Database - A database for accumulating all kinds of human genome variations detected by various experimental techniques. * MEDALS - A portal site that provides information about databases, analysis tools, and the relevant projects, that were conducted with the financial support from the Ministry of Economy, Trade and Industry of Japan.

Proper citation: NBDC - National Bioscience Database Center (RRID:SCR_000814) Copy   

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https://www.ibdgc.org/

Repository of biospecimen and phenotype data collected from Crohn's disease and ulcerative colitis cases and controls recruited at six sites throughout North America that are available to the scientific community. Phenotyping is performed using a standardized protocol, and lymphoblastoid cell lines are established for each subject. Phenotype data for each subject are collected by the Consortium's Data Coordinating Center (DCC), and phenotype data for all subjects with DNA samples are available. The resulting DNA samples have already been utilized by the Consortium to complete various association studies, including genome-wide association studies using dense genotyping arrays. Researchers can obtain DNA samples and phenotype, genotype, and pedigree data through the Data Repository. GWAS data must be requested through dbGAP. The IBDGC is involved with independent genetic research studies and actively works with members of the IBD and genetic communities on collaborative projects. They are also members of the International IBD Genetics Consortium. Phenotype Tools: The Consortium Phenotype Committee, led by Dr. Hillary Steinhart designed and validated paper forms to collect extensive phenotype data on Crohn's Disease and ulcerative colitis. Consortium phenotype tools are available for use by non-Consortium members.

Proper citation: NIDDK Inflammatory Bowel Disease Genetics Consortium (RRID:SCR_001461) Copy   

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http://www.genetrap.org/

Consortium represents all publicly available gene trap cell lines, which are available on non-collaborative basis for nominal handling fees. Researchers can search and browse IGTC database for cell lines of interest using accession numbers or IDs, keywords, sequence data, tissue expression profiles and biological pathways, can find trapped genes of interest on IGTC website, and order cell lines for generation of mutant mice through blastocyst injection. Consortium members include: BayGenomics (USA), Centre for Modelling Human Disease (Toronto, Canada), Embryonic Stem Cell Database (University of Manitoba, Canada), Exchangeable Gene Trap Clones (Kumamoto University, Japan), German Gene Trap Consortium provider (Germany), Sanger Institute Gene Trap Resource (Cambridge, UK), Soriano Lab Gene Trap Resource (Mount Sinai School of Medicine, New York, USA), Texas Institute for Genomic Medicine - TIGM (USA), TIGEM-IRBM Gene Trap (Naples, Italy).

Proper citation: International Gene Trap Consortium (RRID:SCR_002305) Copy   

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http://discover.nci.nih.gov/gominer/

GoMiner is a tool for biological interpretation of "omic" data including data from gene expression microarrays. Omic experiments often generate lists of dozens or hundreds of genes that differ in expression between samples, raising the question, What does it all mean biologically? To answer this question, GoMiner leverages the Gene Ontology (GO) to identify the biological processes, functions and components represented in these lists. Instead of analyzing microarray results with a gene-by-gene approach, GoMiner classifies the genes into biologically coherent categories and assesses these categories. The insights gained through GoMiner can generate hypotheses to guide additional research. GoMiner displays the genes within the framework of the Gene Ontology hierarchy in two ways: * In the form of a tree, similar to that in AmiGO * In the form of a "Directed Acyclic Graph" (DAG) The program also provides: * Quantitative and statistical analysis * Seamless integration with important public databases GoMiner uses the databases provided by the GO Consortium. These databases combine information from a number of different consortium participants, include information from many different organisms and data sources, and are referenced using a variety of different gene product identification approaches.

Proper citation: GoMiner (RRID:SCR_002360) Copy   

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https://orwh.od.nih.gov/

The mission of the Office of Research on Women's Health (ORWH) is to stimulate and encourage meritorious research on women's health, including the role of sex and gender in health and disease. The priorities signify approaches and areas for which there is a need to stimulate and encourage research on women's health, or sex/gender factors, and the advancement of women in biomedical research careers. These research priorities are not an exclusive list of research areas important to women's health; therefore other innovative or significant research areas should also be considered. The following four overarching themes are important for addressing research on women's health: Lifespan, Sex/Gender Determinants, Health Disparities/Differences and Diversity, ad Interdisciplinary Research. Special Areas of Emphasis - Prevention/Treatment: from basic biological factors, including identifying and validating biomarkers, to risk and its applications to disease prevention, early detection, and treatment. - Sex and Genetics/Pharmacogenomics: genetic, molecular, and cellular basis for action of pharmacologic agents known to have different effects in females than in males. Research on effects of sex as a modifier of gene function and response is under-investigated. Sponsors: This research is funded by the NAtional Institutes of Health.

Proper citation: Office of Research on Womens Health: Reseach (RRID:SCR_001822) Copy   

•   Source: SciCrunch Registry

https://plantcyc.org/content/plantcyc-15.2.0

Multi species reference database. Comprehensive plant biochemical pathway database, containing curated information from literature and computational analyses about genes, enzymes, compounds, reactions, and pathways involved in primary and secondary metabolism.

Proper citation: PlantCyc (RRID:SCR_002110) Copy   

•   Source: SciCrunch Registry

https://www.thermofisher.com/us/en/home/technical-resources/software-downloads/dataassist-software.html

Data analysis tool that utilizes the Comparative CT (ddCT) method to rapidly and accurately quantitate relative gene expression across a large number of genes and samples. Raw input from plates or arrays can be analyzed according to user-determined settings.

Proper citation: DataAssist (RRID:SCR_014969) Copy   

•   Source: SciCrunch Registry

https://www.jax.org/news-and-insights/2013/february/komp2-mice-phenotyping-and-availability

Knockout Mouse Phenotyping Project, JAX information about their contributions to KOMP2 project. Project to generate and phenotype single gene KO mouse strains from KOMP ES cell lines. Strains are phenotyped using protocols in pipeline designed by International Mouse Phenotyping Consortium. There are three NIH-funded phenotyping centers in United States: JAX, BaSH Consortium (Baylor College of Medicine, the Wellcome Trust Sanger Institute and MRC Harwell), and the DTCC Consortium (University of California at Davis, the Toronto Center for Phenogenomics, Children’s Hospital Oakland Research Institute (CHORI) and Charles River ).

Proper citation: KOMP2 (RRID:SCR_017528) Copy   

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https://github.com/AlexsLemonade/refinebio

Software tool to uniformly process and normalize large amounts of data. Harmonizes petabytes of publicly available biological data into ready-to-use datasets for cancer researchers and AI/ML scientists.

Proper citation: refine.bio (RRID:SCR_017471) Copy   

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https://github.com/lufuhao/ExonerateTransferAnnotation

Software tool as pipeline to make anntotations using cDNA and CDS sequences.

Proper citation: ExonerateTransferAnnotation (RRID:SCR_017557) Copy   

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

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on July 31,2025. Software application aiming at identifying haplotype blocks. The likelihood of the data is calculated minus the model complexity. The resulting blocks have very low diversity and the linkage disequilibrium with SNP's outside the blocks is low. (entry from Genetic Analysis Software)

Proper citation: ENTROPY BLOCKER (RRID:SCR_000123) Copy   

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http://django.nubic.northwestern.edu/fundo/

Tool that takes a list of genes and finds relevant diseases based on statistical analysis of the Disease Ontology annotation database. It accepts Entrez gene ids or gene symbols, separated by tabs, newlines, or commas. This list of genes can be obtained by microarray, proteomics, sequencing or other high-throughput screening methods.

Proper citation: FunDO (RRID:SCR_001725) Copy   

•   Source: SciCrunch Registry

http://www.homozygositymapper.org/

A web-based approach of homozygosity mapping that can handle tens of thousands markers. User can upload their own SNP genotype files to the database. Intuitive graphic interface is provided to view the homozygous stretches, with the ability of zooming into single chromosomes or user-defined chromosome regions. The underlying genotypes in all samples are displayed. The software is also integrated with our candidate gene search engine, GeneDistiller, so that users can interactively determine the most promising gene. (entry from Genetic Analysis Software)

Proper citation: HOMOZYGOSITYMAPPER (RRID:SCR_001714) Copy   

•   Source: SciCrunch Registry

http://weatherby.genetics.utah.edu/cgi-bin/Phevor/PhevorWeb.html

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on October 28,2025. Tool that integrates phenotype, gene function, and disease information with personal genomic data for improved power to identify disease-causing alleles. It works by combining knowledge resident in multiple biomedical ontologies with the outputs of variant prioritization tools. It does so using an algorithm that propagates information across and between ontologies. This process enables Phevor to accurately reprioritize potentially damaging alleles identified by variant prioritization tools in light of gene function, disease, and phenotype knowledge. Phevor is especially useful for single exome and family trio-based diagnostic analyses, the most commonly occurring clinical scenarios, and ones for which existing personal-genomes diagnostic tools are most inaccurate and underpowered. Phevor not only improves diagnostic accuracy for individuals presenting with established disease phenotypes, but also for those with previously undescribed and atypical disease presentations. Importantly, Phevor is not limited to known diseases, or known disease-causing alleles.

Proper citation: Phevor (RRID:SCR_002273) Copy   

•   Source: SciCrunch Registry

http://www.roslin.ed.ac.uk/alan-archibald/porcine-genome-sequencing-project/

Map of identifyied genes controlling traits of economic and welfare significance in the pig. The project objectives were to produce a genetic map with markers spaced at approximately 20 centiMorgan intervals over at least 90% of the pig genome; to produce a physical map with at least one distal and one proximal landmark locus mapped on each porcine chromosome arm and also genetically mapped; to develop a flow karyotype for the pig based on FACS sorted chromosomes; to develop PCR based techniques to enable rapid genotyping for polymorphic markers; to evaluate synteny conservation between pigs, man, mice and cattle; to develop and evaluate the statistical techniques required to analyze data from QTL mapping experiments and to plan and initiate the mapping of QTLs in the pig; to map loci affecting traits of economic and biological significance in the pig; and to develop the molecular tools to allow the future identification and cloning of mapped loci. Animal breeders currently assume that economically important traits such as growth, carcass composition and reproductive performance are controlled by an infinite number of genes each of infinitessimal effect. Although this model is known to be unrealistic, it has successfully underpinned the genetic improvement of livestock, including pigs, over recent decades. A map of the pig genome would allow the development of more realistic models of the genetic control of economic traits and the ultimately the identification of the major trait genes. This would allow the development of more efficient marker assisted selection which may be of particular value for traits such as disease resistance and meat quality.

Proper citation: Pig Genome Mapping (RRID:SCR_012884) Copy   

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http://www.aniseed.cnrs.fr/

Database of ascidian embryonic development at the level of the genome (cis-regulatory sequences, gene expression, protein annotation), of the cell (morphology, fate, induction, lineage) or of the whole embryo (anatomy, morphogenesis). Currently, four organism models are described in Aniseed: Ciona intestinalis, Ciona savignyi, Halocynthia roretzi and Phallusia mammillata.
This version supports four sets of Ciona intestinalis transcript models: JGI v1.0, KyotoGrail 2005, KH and ENSEMBL, all functionally annotated, and grouped into Aniseedv3.0 gene models. Users can explore their expression profiles during normal or manipulated development, access validated cis-regulatory regions, get the molecular tools used to assay gene function, or all articles related to the function, or regulation of a given gene. Known transcriptional regulators and targets are listed for each gene, as are the gene regulatory networks acting in individual anatomical territories.
ANISEED is a community tool, and the direct involvement of external contributors is important to optimize the quality of the submitted data. Virtual embryo: The 3D Virtual embryo is available to download in the download section of the website.

Proper citation: Ascidian Network for InSitu Expression and Embryological Data (RRID:SCR_013030) Copy   

•   Source: SciCrunch Registry

http://www.clcbio.com/products/clc-genomics-workbench/

Commercially available software for visualization and analysis of next generation sequencing data. Used for viewing, exploring, and sharing of NGS analysis results. Complete toolkit for genomics, transcriptomics, epigenomics, and metagenomics in one program.

Proper citation: CLC Genomics Workbench (RRID:SCR_011853) Copy   

•   Source: SciCrunch Registry

http://www.daimi.au.dk/%7Emailund/SNPFile/

Software library and API for manipulating large SNP datasets with associated meta-data, such as marker names, marker locations, individuals'' phenotypes, etc. in an I/O efficient binary file format. In its core, SNPFile assumes very little about the metadata associated with markers and individuals, but leaves this up to application program protocols. (entry from Genetic Analysis Software)

Proper citation: SNPFILE (RRID:SCR_009402) Copy   

•   Source: SciCrunch Registry

https://nidagenetics.org/

Site for collection and distribution of clinical data related to genetic analysis of drug abuse phenotypes. Anonymous data on family structure, age, sex, clinical status, and diagnosis, DNA samples and cell line cultures, and data derived from genotyping and other genetic analyses of these clinical data and biomaterials, are distributed to qualified researchers studying genetics of mental disorders and other complex diseases at recognized biomedical research facilities. Phenotypic and Genetic data will be made available to general public on release dates through distribution mechanisms specified on website.

Proper citation: National Institute on Drug Abuse Center for Genetic Studies (RRID:SCR_013061) Copy   

•   Source: SciCrunch Registry