Tools   Select Another Resource Report Type

http://genome-www.stanford.edu/TMA/

Software Tools for High-Throughput Analysis and Archiving of Immunohistochemistry Staining Data Obtained with Tissue Microarrays.

Proper citation: Stanford TMA Software (RRID:SCR_005598) Copy   

•   Source: SciCrunch Registry

http://www.compbio.dundee.ac.uk/downloads/oxbench/

A suite of programs aimed at developers of alignment methods rather than end-users to assess the accuracy of multiple sequence alignment methods. It includes a reference database of protein multiple sequence alignments that were generated by consideration of protein three-dimensional structure.

Proper citation: OXBench (RRID:SCR_005591) Copy   

•   Source: SciCrunch Registry

http://staden.sourceforge.net/

A fully developed set of DNA sequence assembly (Gap4 and Gap5), editing and analysis tools (Spin) for Unix, Linux, MacOSX and MS Windows.

Proper citation: Staden Package (RRID:SCR_005629) Copy   

•   Source: SciCrunch Registry

http://www.hca-vision.com/product_spot.html

Software package for analysis of microarray images. Microarray spot detection and characterization software package which extracts numerical information from cDNA microarrays., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: SPOT (RRID:SCR_005623) Copy   

•   Source: SciCrunch Registry

http://mesquiteproject.org/packages/chromaseq/

A software package in Mesquite that processes chromatograms, makes contigs, base calls, etc., using in part the programs Phred and Phrap.

Proper citation: Chromaseq (RRID:SCR_005587) Copy   

•   Source: SciCrunch Registry

http://slicer.org/

A free, open source software package for visualization and image analysis including registration, segmentation, and quantification of medical image data. Slicer provides a graphical user interface to a powerful set of tools so they can be used by end-user clinicians and researchers alike. 3D Slicer is natively designed to be available on multiple platforms, including Windows, Linux and Mac Os X. Slicer is based on VTK (http://public.kitware.com/vtk) and has a modular architecture for easy addition of new functionality. It uses an XML-based file format called MRML - Medical Reality Markup Language which can be used as an interchange format among medical imaging applications. Slicer is primarily written in C++ and Tcl.

Proper citation: 3D Slicer (RRID:SCR_005619) Copy   

•   Source: SciCrunch Registry

http://brainstars.org

BrainStars (or B*) is a quantitative expression database of the adult mouse brain. The database has genome-wide expression profile at 51 adult mouse CNS regions. For 51 CNS regions, slices (0.5-mm thick) of mouse brain were cut on a Mouse Brain Matrix, frozen, and the specific regions were punched out bilaterally with a microdissecting needle (gauge 0.5 mm) under a stereomicroscope. For each region, we took samples every 4 hours, starting at ZT0 (Zeitgaber time 0; the time of lights on), for 24 hours (6 time-point samples for each region), and we pooled the samples from the different time points. We independently sampled each region twice (n=2). These samples were purified their RNA, and measured with Affymetrix GeneChip Mouse Genome 430 2.0 arrays. Expression values were then summarized with the RMA method. After several analysis with the expression data, the data and analysis results were stored in the BrainStars database. The database has a REST-like Web API interface for accessing from your Web applications. This document shows how to access the database via our Web API.

Proper citation: BrainStars (RRID:SCR_005810) Copy   

•   Source: SciCrunch Registry

http://www.bwfund.org/

The Burroughs Wellcome Fund is an independent private foundation dedicated to advancing the biomedical sciences by supporting research and other scientific and educational activities. Within this broad mission, BWF has two primary goals: * To help scientists early in their careers develop as independent investigators * To advance fields in the basic biomedical sciences that are undervalued or in need of particular encouragement BWF''s financial support is channeled primarily through competitive peer-reviewed award programs. * BWF''s endowment: $586.8 million at the end of FY 2009 * BWF approved $26.4 million in grants during FY 2009 BWF makes grants primarily to degree-granting institutions on behalf of individual researchers, who must be nominated by their institutions. To complement these competitive award programs, BWF also makes grants to nonprofit organizations conducting activities intended to improve the general environment for science. A Board of Directors comprising distinguished scientists and business leaders governs BWF. BWF was founded in 1955 as the corporate foundation of the pharmaceutical firm Burroughs Wellcome Co. In 1993, a generous gift from the Wellcome Trust in the United Kingdom, enabled BWF to become fully independent from the company, which was acquired by Glaxo in 1995. BWF has no affiliation with any corporation.

Proper citation: Burroughs Wellcome Fund (RRID:SCR_005772) Copy   

•   Source: SciCrunch Registry

http://corneliu.henegar.info/FunCluster.htm

FunCluster is a genomic data analysis algorithm which performs functional analysis of gene expression data obtained from cDNA microarray experiments. Besides automated functional annotation of gene expression data, FunCluster functional analysis aims to detect co-regulated biological processes through a specially designed clustering procedure involving biological annotations and gene expression data. FunCluster''''s functional analysis relies on Gene Ontology and KEGG annotations and is currently available for three organisms: Homo Sapiens, Mus Musculus and Saccharomyces Cerevisiae. FunCluster is provided as a standalone R package, which can be run on any operating system for which an R environment implementation is available (Windows, Mac OS, various flavors of Linux and Unix). Download it from the FunCluster website, or from the worldwide mirrors of CRAN. FunCluster is provided freely under the GNU General Public License 2.0. Platform: Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible

Proper citation: FunCluster (RRID:SCR_005774) Copy   

•   Source: SciCrunch Registry

http://vibez.informatik.uni-freiburg.de/

An imaging and image analysis framework for virtual colocalization studies in larval zebrafish brains, currently available for 72hpf, 48hpf and 96hpf old larvae. ViBE-Z contains a database with precisely aligned gene expression patterns (1����m^3 resolution), an anatomical atlas, and a software. This software creates high-quality data sets by fusing multiple confocal microscopic image stacks, and aligns these data sets to the standard larva. The ViBE-Z database and atlas are stored in HDF5 file format. They are freely available for download. ViBE-Z provides a software that automatically maps gene expression data with cellular resolution to a 3D standard larval zebrafish (Danio rerio) brain. ViBE-Z enhances the data quality through fusion and attenuation correction of multiple confocal microscope stacks per specimen and uses a fluorescent stain of cell nuclei for image registration. It automatically detects 14 predefined anatomical landmarks for aligning new data with the reference brain. ViBE-Z performs colocalization analysis in expression databases for anatomical domains or subdomains defined by any specific pattern. The ViBE-Z database, atlas and software are provided via a web interface.

Proper citation: ViBE-Z (RRID:SCR_005895) Copy   

•   Source: SciCrunch Registry

http://www.cbs.dtu.dk/ws/ws.php?entry=BLASTatlas

The BLASTatlas is a tool that is useful for mapping and visualizing whole genome homology of genes and proteins within a reference strain compared to other strains or species of one or more prokaryotic organisms using either blastp, blastn, tblastn, or blastx. DNA structural information is also included in the atlas to visualize the DNA chromosomal context of regions. Additional information can be added to these plots. The tool is SOAP compliant and WSDL (web services description language) files are available with programming examples available in Perl. The resolution is per-residue or per nucleotide depending on the regime of the blast search: For each annotation in the reference genome, the best hit in the database genome is found using one of the above algorithms. Each matching or mismatching residue/nucleotide of the best hit (based on BLAST score) is then mapped back to the genome sequence, using the coordinates provided in the annotations. By providing an interoperable method to carry out whole genome visualization of homology, this service offers bioinformaticians as well as biologists an easy-to-adopt workflow that can be directly called from the programming language of the user, hence enabling automation of repeated tasks. This tool can be relevant in many pangenomic as well as in metagenomic studies, by giving a quick overview of clusters of insertion sites, genomic islands and overall homology between a reference sequence and a data set.

Proper citation: BLASTatlas - Mapping of whole genome homology (RRID:SCR_005891) Copy   

•   Source: SciCrunch Registry

http://great.stanford.edu/public/html/splash.php

Data analysis service that predicts functions of cis-regulatory regions identified by localized measurements of DNA binding events across an entire genome. Whereas previous methods took into account only binding proximal to genes, GREAT is able to properly incorporate distal binding sites and control for false positives using a binomial test over the input genomic regions. GREAT incorporates annotations from 20 ontologies and is available as a web application. The utility of GREAT extends to data generated for transcription-associated factors, open chromatin, localized epigenomic markers and similar functional data sets, and comparative genomics sets. Platform: Online tool

Proper citation: GREAT: Genomic Regions Enrichment of Annotations Tool (RRID:SCR_005807) Copy   

•   Source: SciCrunch Registry

http://www.hormone.org/

A portal for hormone-related health information for the public, physicians, allied health professionals and the media. It serves as a resource for the public by promoting the prevention, treatment and cure of hormone-related conditions through outreach and education. It provides free educational materials, public forums, physician referral service, and media education campaigns. It offers a library of educational materials and programs covering a wide range of endocrine topics, including adrenal disorders, breast cancer, diabetes, osteoporosis, stress, thyroid disease and cancer.

Proper citation: Hormone Health Network (RRID:SCR_005765) Copy   

•   Source: SciCrunch Registry

https://www.google.com/docs/about/

Authoring tool to create, share, and collaborate on the web with documents, spreadsheets, presentations, and more in real time. All your changes are saved automatically in Drive.

Proper citation: Google Docs (RRID:SCR_005886) Copy   

•   Source: SciCrunch Registry

http://manuals.bioinformatics.ucr.edu/home/R_BioCondManual#GOHyperGAll

To test a sample population of genes for overrepresentation of GO terms, the R/BioC function GOHyperGAll computes for all GO nodes a hypergeometric distribution test and returns the corresponding p-values. A subsequent filter function performs a GO Slim analysis using default or custom GO Slim categories. Basic knowledge about R and BioConductor is required for using this tool. Platform: Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible, THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: GOHyperGAll (RRID:SCR_005766) Copy   

•   Source: SciCrunch Registry

https://gene-atlas.brainminds.jp/

Database of gene expression in the marmoset brain.Comparative anatomy of marmoset and mouse cortex from genomic expression. Atlas comparing brain of neonatal marmoset with mouse using in situ hybridization.

Proper citation: Expression Atlas of the Marmoset (RRID:SCR_005760) Copy   

•   Source: SciCrunch Registry

http://www.cancer.fi/syoparekisteri/en/

The Finnish Cancer Registry maintains a nation-wide database on all cancer cases in Finland going back to 1953. It is also an internationally active institute for statistical and epidemiological cancer research. The Mass Screening Registry is a department of the Finnish Cancer Registry, and is responsible of planning and evaluating national cancer screening programs in Finland. The site contains information on cancer research and up to date statistics on the prevalence of different types of cancer in Finland, the Nordic countries and on a global level. The web pages include information for participants in cancer screening and for professionals involved in organizing such screening.

Proper citation: Finnish Cancer Registry (RRID:SCR_005881) Copy   

•   Source: SciCrunch Registry

http://www.scytek.com/

An Antibody supplier

Proper citation: ScyTek Laboratories (RRID:SCR_005919) Copy   

•   Source: SciCrunch Registry

http://www.vectorbase.org

Bioinformatics Resource Center for invertebrate vectors. Provides web-based resources to scientific community conducting basic and applied research on organisms considered potential agents of biowarfare or bioterrorism or causing emerging or re-emerging diseases.

Proper citation: VectorBase (RRID:SCR_005917) Copy   

•   Source: SciCrunch Registry

http://snp-magma.sourceforge.net

Software that utilizes a multiobjective evolutionary algorithm for genetic mapping. It is based on a the ECJ evolutionary software package written by Sean Luke and includes the Strength Pareto Evoluationary Algorithm Version 2 changes for multiobjective analysis. The code runs on any platform with Java Version 2. A genetic mapping project, typically implemented during a search for genes responsible for a disease, requires the acquisition of a set of data from each of a large number of individuals. This data set includes the values of multiple genetic markers. These genetic markers occur at discrete positions along the genome, which is a collection of one or more linear chromosomes. Typing the value of a marker in an individual carries a cost; one seeks to minimize the number of markers typed without excessively jeopardizing the probability of detecting an association between a marker and a disease phenotype. MAGMA is a project which employ''s a multiobjective evolutionary algorithm to solve this problem.

Proper citation: MAGMA (RRID:SCR_005757) Copy   

•   Source: SciCrunch Registry