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http://www.well.ox.ac.uk/happy/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on February 28,2023. Software package for Multipoint QTL Mapping in Genetically Heterogeneous Animals (entry from Genetic Analysis Software) The method is implemented in a C-program and there is now an R version of HAPPY. You can run HAPPY remotely from their web server using your own data (or try it out on the data provided for download).

Proper citation: Happy (RRID:SCR_001395) Copy   

•   Source: SciCrunch Registry

https://factory.euromov.eu/sml/index.php

Open source Java library dedicated to semantic measures computation and analysis. Tools based on the SML are also provided through the SML-Toolkit, a command line software giving access to some of the functionalities of the library. The SML and the toolkit can be used to compute semantic similarity and semantic relatedness between semantic elements (e.g. concepts, terms) or entities semantically characterized (e.g. entities defined in a semantic graph, documents annotated by concepts defined in an ontology).

Proper citation: Semantic Measures Library (RRID:SCR_001383) Copy   

•   Source: SciCrunch Registry

http://amp.pharm.mssm.edu/Enrichr/

A web-based gene list enrichment analysis tool that provides various types of visualization summaries of collective functions of gene lists. It includes new gene-set libraries, an alternative approach to rank enriched terms, and various interactive visualization approaches to display enrichment results using the JavaScript library, Data Driven Documents (D3). The software can also be embedded into any tool that performs gene list analysis. System-wide profiling of genes and proteins in mammalian cells produce lists of differentially expressed genes / proteins that need to be further analyzed for their collective functions in order to extract new knowledge. Once unbiased lists of genes or proteins are generated from such experiments, these lists are used as input for computing enrichment with existing lists created from prior knowledge organized into gene-set libraries.

Proper citation: Enrichr (RRID:SCR_001575) Copy   

•   Source: SciCrunch Registry

http://www.biomed.org

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 23, 2016. This laboratory facilities contain core research space for monoclonal antibody production, oligonucleotide and peptide synthesis, gene cloning, DNA sequencing, high performance liquid chromatography, tissue culture, positron emission tomography, magnetic resonance spectroscopy and electron microscopy.

Proper citation: The Biomedical Research Foundation - Current Research (RRID:SCR_001564) Copy   

•   Source: SciCrunch Registry

https://repository.niddk.nih.gov/study/21

Data and biological samples were collected by this consortium organizing international efforts to identify genes that determine an individual risk of type 1 diabetes. It originally focused on recruiting families with at least two siblings (brothers and/or sisters) who have type 1 diabetes (affected sibling pair or ASP families). The T1DGC completed enrollment for these families in August 2009. They completed enrollment of trios (father, mother, and a child with type 1 diabetes), as well as cases (people with type 1 diabetes) and controls (people with no history of type 1 diabetes) from populations with a low prevalence of this disease in January 2010. T1DGC Data and Samples: Phenotypic and genotypic data as well as biological samples (DNA, serum and plasma) for T1DGC participants have been deposited in the NIDDKCentral Repositories for future research.

Proper citation: Type 1 Diabetes Genetics Consortium (RRID:SCR_001557) Copy   

•   Source: SciCrunch Registry

http://neuronalarchitects.com/ibiofind.html

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 17, 2016. C#.NET 4.0 WPF / OWL / REST / JSON / SPARQL multi-threaded, parallel desktop application enables the construction of biomedical knowledge through PubMed, ScienceDirect, EndNote and NIH Grant repositories for tracking the work of medical researchers for ranking and recommendations. Users can crawl web sites, build latent semantic indices to generate literature searches for both Clinical Translation Science Award and non-CTSA institutions, examine publications, build Bayesian networks for neural correlates, gene to gene interactions, protein to protein interactions and as well drug treatment hypotheses. Furthermore, one can easily access potential researcher information, monitor and evolve their networks and search for possible collaborators and software tools for creating biomedical informatics products. The application is designed to work with the ModelMaker, R, Neural Maestro, Lucene, EndNote and MindGenius applications to improve the quality and quantity of medical research. iBIOFind interfaces with both eNeoTutor and ModelMaker 2013 Web Services Implementation in .NET for eNeoTutor to aid instructors to build neuroscience courses as well as rare diseases. Added: Rare Disease Explorer: The Visualization of Rare Disease, Gene and Protein Networks application module. Cinematics for the Image Finder from Yale. The ability to automatically generate and update websites for rare diseases. Cytoscape integration for the construction and visualization of pathways for Molecular targets of Model Organisms. Productivity metrics for medical researchers in rare diseases. iBIOFind 2013 database now includes over 150 medical schools in the US along with Clinical Translational Science Award Institutions for the generation of biomedical knowledge, biomedical informatics and Researcher Profiles.

Proper citation: iBIOFind (RRID:SCR_001587) Copy   

•   Source: SciCrunch Registry

https://phenogen.org

Website for analyzing microarray data. Software toolbox for storing, analyzing and integrating microarray data and related genotype and phenotype data. The site is particularly suited for combining QTL and microarray data to search for candidate genes contributing to complex traits. In addition, the site allows, if desired by the investigators, sharing of the data. Investigators can conduct in-silico microarray experiments using their own and/or shared data. There are five major sections of the site: Genome/Transcriptome Data Browser, Microarray Analysis Tools, Gene List Analysis Tools, QTL Tools, and Downloads. The genome/transcriptome data browser combines a genome browser with all the microarray, RNA-Seq, and Genomic Sequencing data. This provides an effective platform to view all of this data side by side. Source code is available on GitHub.

Proper citation: PhenoGen Informatics (RRID:SCR_001613) Copy   

•   Source: SciCrunch Registry

http://www.norcomm.org/index.htm

Large-scale research initiative focused on developing and distributing a library of mouse embryonic stem (ES) cell lines carrying single gene trapped or targeted mutations across the mouse genome. NorCOMM's large and growing archive of ES cells is publicly available on a cost-recovery basis from the Canadian Mouse Mutant Repository. As an international public resource, access to clones is unrestricted and nonexclusive. Through NorCOMM's affiliation with the Canadian Mouse Consortium (CMC), NorCOMM also provides clients with a single point of access to regional mouse derivation, phenotyping, genetic and archiving services across Canada. These value-added services can help your company harness NorCOMM's resources for drug discovery, target discovery and preclinical validation.

Proper citation: North American Conditional Mouse Mutagenesis Project (RRID:SCR_001614) Copy   

•   Source: SciCrunch Registry

http://www.tigm.org/

Resource for any researcher looking to obtain knockout mice and embryonic stem (ES) cells quickly and with favorable intellectual property (IP) terms. Our resources include the world’s largest gene trap library of ES cells in the C57BL/6N mouse strain and a constantly expanding repository of cryopreserved germplasm of knockout lines. TIGM provides both ES cell clones and mice as well as other transgenic core services including CRISPR/Cas9-based genome modifications within the Texas A&M system and to the public and private international research community.

Proper citation: Texas A and M Institute for Genomic Medicine (RRID:SCR_001615) Copy   

•   Source: SciCrunch Registry

http://www.epilepsygenetics.eu/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on August 16,2023. Group of clinical care and epilepsy research centers who are committed to improving the lives of people with epilepsy through an understanding of the genetics of epilepsy. The consoritum was in an effort to speed discovery to epilepsy genetics by pooling the resources of several research centres., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: EPIGEN (RRID:SCR_000093) Copy   

•   Source: SciCrunch Registry

http://deweylab.biostat.wisc.edu/rsem/

Software package for quantifying gene and isoform abundances from single end or paired end RNA Seq data. Accurate transcript quantification from RNA Seq data with or without reference genome. Used for accurate quantification of gene and isoform expression from RNA-Seq data.

Proper citation: RSEM (RRID:SCR_000262) Copy   

•   Source: SciCrunch Registry

http://cran.r-project.org/src/contrib/Archive/iFad/

An R software package implementing a bayesian sparse factor model for the joint analysis of paired datasets, the gene expression and drug sensitivity profiles, measured across the same panel of samples, e.g. cell lines.

Proper citation: iFad (RRID:SCR_000271) Copy   

•   Source: SciCrunch Registry

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

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on July 31,2025. A web program that organizes lists of genes of interest (for example, under- and overexpressed genes from a microarray experiment) for biological interpretation in the context of the Gene Ontology and automates the analysis of multiple microarrays then integrates the results across all of them in exportable output files and visualizations. High-Throughput GoMiner is an enhancement of GoMiner and is implemented with both a command line interface and a web interface. The program can also: efficiently perform automated batch processing of an arbitrary number of microarrays; produce a human- or computer-readable report that rank-orders the multiple microarray results according to the number of significant GO categories; integrate the multiple microarray results by providing organized, global clustered image map visualizations of the relationships of significant GO categories; provide a fast form of false discovery rate multiple comparisons calculation; and provide annotations and visualizations for relating transcription factor binding sites to genes and GO categories.

Proper citation: High-Throughput GoMiner (RRID:SCR_000173) Copy   

•   Source: SciCrunch Registry

http://icbi.at/software/gpviz/gpviz.shtml

A versatile Java-based software used for dynamic gene-centered visualization of genomic regions and/or variants.

Proper citation: GPViz (RRID:SCR_000346) Copy   

•   Source: SciCrunch Registry

http://teddy.epi.usf.edu/

International consortium of six centers assembled to participate in the development and implementation of studies to identify infectious agents, dietary factors, or other environmental agents, including psychosocial factors, that trigger type 1 diabetes in genetically susceptible people. The coordinating centers recruit and enroll subjects, obtaining informed consent from parents prior to or shortly after birth, genetic and other types of samples from neonates and parents, and prospectively following selected neonates throughout childhood or until development of islet autoimmunity or T1DM. The study tracks child diet, illnesses, allergies and other life experiences. A blood sample is taken from children every 3 months for 4 years. After 4 years, children will be seen every 6 months until the age of 15 years. Children are tested for 3 different autoantibodies. The study will compare the life experiences and blood and stool tests of the children who get autoantibodies and diabetes with some of those children who do not get autoantibodies or diabetes. In this way the study hopes to find the triggers of T1DM in children with higher risk genes.

Proper citation: TEDDY (RRID:SCR_000383) Copy   

•   Source: SciCrunch Registry

http://www.arb-home.de/

Software environment for maintaining databases of molecular sequences and additional information, and for analyzing the sequence data, with emphasis on phylogeny reconstruction. Programs have primarily been developed for ribosomal ribonucleic acid (rRNA) sequences and, therefore, contain special tools for alignment and analysis of these structures. However, other molecular sequence data can also be handled. Protein gene sequences and predicted protein primary structures as well as protein secondary structures can be stored in the same database. ARB package is designed for graphical user interface. Program control and data display are available in a hierarchical set of windows and subwindows. Majority of operations can be controlled using mouse for moving pointer and the left mouse button for initiating and performing operations.

Proper citation: ARB project (RRID:SCR_000515) Copy   

•   Source: SciCrunch Registry

http://fulxie.0fees.us/?type=reference&ckattempt=1

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 1,2023. Web-based tool for evaluating and screening reference genes from extensive experimental datasets. It integrates major computational programs (geNorm, Normfinder, BestKeeper, and the comparative delta-Ct method) to compare and rank the tested candidate reference genes. Based on the rankings from each program, it assigns an appropriate weight to an individual gene and calculated the geometric mean of their weights for the overall final ranking., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: RefFinder (RRID:SCR_000472) Copy   

•   Source: SciCrunch Registry

http://www.flybrain.org/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 23,2022. Interactive database of Drosophila melanogaster nervous system. Used by drosophila neuroscience community and by other researchers studying arthropod brain structure.

Proper citation: FlyBrain (RRID:SCR_000706) Copy   

•   Source: SciCrunch Registry

http://www.psb.ugent.be/esb/PiNGO/

A Java-based tool to easily find unknown genes in a network that are significantly associated with user-defined target Gene Ontology (GO) categories. PiNGO is implemented as a plugin for Cytoscape, a popular open source software platform for visualizing and integrating molecular interaction networks. PiNGO predicts the categorization of a gene based on the annotations of its neighbors, using the enrichment statistics of its sister tool BiNGO. Networks can either be selected from the Cytoscape interface or uploaded from file. Platform: Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible

Proper citation: PiNGO (RRID:SCR_000692) Copy   

•   Source: SciCrunch Registry

http://franklin.imgen.bcm.tmc.edu/

The mission of the Baylor College of Medicine - Shaw Laboratory is to apply methods of statistics and bioinformatics to the analysis of large scale genomic data. Our vision is data integration to reveal the underlying connections between genes and processes in order to cure disease and improve healthcare.

Proper citation: Baylor College of Medicine - Shaw Laboratory (RRID:SCR_000604) Copy   

•   Source: SciCrunch Registry