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http://www.stanford.edu/

Private, non profit university in Stanford, California, USA for research and undergraduate and graduate studies. Known for its academic strength, wealth, proximity to Silicon Valley, and ranking as one of the world's top universities. Particularly noted for its entrepreneurship and is one of the most successful universities in attracting funding for start-ups.

Proper citation: Stanford University; Stanford; California (RRID:SCR_011538) Copy   

•   Source: SciCrunch Registry

http://sri.com/

Independent, nonprofit research institute conducting client sponsored research and development for government agencies, commercial businesses, foundations, and other organizations. SRI also brings its innovations to the marketplace by licensing its intellectual property and creating new ventures. SRI was founded as Stanford Research Institute in 1946 by a group of West Coast industrialists and Stanford University. SRI formally separated from the University in 1970, and we changed our name to SRI International in 1977.

Proper citation: Stanford Research Institute International (RRID:SCR_004926) Copy   

•   Source: SciCrunch Registry

http://www.betacell.org/

THIS RESOURCE IS NO LONGER IN SERVICE, documented May 10, 2017. A pilot effort that has developed a centralized, web-based biospecimen locator that presents biospecimens collected and stored at participating Arizona hospitals and biospecimen banks, which are available for acquisition and use by researchers. Researchers may use this site to browse, search and request biospecimens to use in qualified studies. The development of the ABL was guided by the Arizona Biospecimen Consortium (ABC), a consortium of hospitals and medical centers in the Phoenix area, and is now being piloted by this Consortium under the direction of ABRC. You may browse by type (cells, fluid, molecular, tissue) or disease. Common data elements decided by the ABC Standards Committee, based on data elements on the National Cancer Institute''s (NCI''s) Common Biorepository Model (CBM), are displayed. These describe the minimum set of data elements that the NCI determined were most important for a researcher to see about a biospecimen. The ABL currently does not display information on whether or not clinical data is available to accompany the biospecimens. However, a requester has the ability to solicit clinical data in the request. Once a request is approved, the biospecimen provider will contact the requester to discuss the request (and the requester''s questions) before finalizing the invoice and shipment. The ABL is available to the public to browse. In order to request biospecimens from the ABL, the researcher will be required to submit the requested required information. Upon submission of the information, shipment of the requested biospecimen(s) will be dependent on the scientific and institutional review approval. Account required. Registration is open to everyone., documented on August 1, 2015. Consortium that aims to facilitate interdisciplinary collaborations to advance the understanding of pancreatic islet development and function, with the goal of developing innovative therapies to correct the loss of beta cell mass in diabetes, including cell reprogramming, regeneration and replacement. They are responsible for collaboratively generating the necessary reagents, mouse strains, antibodies, assays, protocols, technologies and validation assays that are beyond the scope of any single research effort. The scientific goals for the BCBC are to: * Use cues from pancreatic development to directly differentiate pancreatic beta cells and islets from stem / progenitor cells for use in cell-replacement therapies for diabetes, * Determine how to stimulate beta cell regeneration in the adult pancreas as a basis for improving beta cell mass in diabetic patients, * Determine how to reprogram progenitor / adult cells into pancreatic beta-cells both in-vitro and in-vivo as a mean for developing cell-replacement therapies for diabetes, and * Investigate the progression of human type-1 diabetes using patient-derived cells and tissues transplanted in humanized mouse models. Many of the BCBC investigator-initiated projects involve reagent-generating activities that will benefit the larger scientific community. The combination of programs and activities should accelerate the pace of major new discoveries and progress within the field of beta cell biology.

Proper citation: Beta Cell Biology Consortium (RRID:SCR_005136) Copy   

•   Source: SciCrunch Registry

https://metadatacenter.org

Develops information technologies that make authoring complete metadata more manageable. Its products aim to facilitate using the metadata in further research.Center to improve metadata and its use throughout biomedical sciences. Develops information technologies that make authoring complete metadata more manageable through better interfaces, terminology, metadata practices, and analytics. Optimizes metadata pathway from provider to end user. Provides way for funders to specify what metadata they want to collect as part of research life cycle.

Proper citation: Center for Expanded Data Annotation and Retrieval (RRID:SCR_016269) Copy   

•   Source: SciCrunch Registry

http://diabeticfootconsortium.org/

Group of academic institutions committed to studying diabetic foot conditions, such as foot ulcers and wound healing, to develop predictive biomarkers which can be later used to create better treatment plans and improve health and quality of life for people living with diabetes.

Proper citation: Diabetic Foot Consortium (RRID:SCR_018914) Copy   

•   Source: SciCrunch Registry

https://www.ctsacentral.org/

National consortium of medical research institutions working together to transform the local, regional, and national environment to increase the efficiency and speed of clinical and translational research across the country. Consortium members share a common vision to reduce the time it takes for laboratory discoveries to become treatments for patients, to engage communities in clinical research efforts and to train clinical and translational researchers. This consortium includes 60 medical research institutions located throughout the nation, linking them together to energize the discipline of clinical and translational science. The CTSA consortium has five Strategic Goals: * National Clinical and Translational Research Capability * The Training and Career Development of Clinical and Translational Scientists * Consortium-Wide Collaborations * The Health of our Communities and the Nation * T1 Translational Research

Proper citation: Clinical and Translational Science Awards Consortium (RRID:SCR_008339) Copy   

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http://www.adgenetics.org/

Consortium to conduct genome-wide association studies (GWAS) to identify genes associated with an increased risk of developing late-onset Alzheimer''''s disease (LOAD). The goal of the ADGC is to identify genetic variants associated with risk for AD. It plans to do this through the following collaborative goals: # Identify genes responsible for AD susceptibility # Identify AD sub-phenotype genes rate-of-progression plaque / tangle load / distribution biomarker variability # Generate a genetic data resource for the AD research community Data generated by ADGC is available at the following website: https://www.niagads.org/content/alzheimers-disease-genetics-consortium-adgc-collection

Proper citation: Alzheimers Disease Genetics Consortium (RRID:SCR_004004) Copy   

•   Source: SciCrunch Registry

https://www.sharelatex.com/

An collaborative tool which allows users to edit LaTeX documents in their browser. Multiple users can simultaneously access and edit the same LaTeX document and see the changes in real time. The latest version is available online, and the built in chat helps communicate with others while editing.

Proper citation: ShareLaTeX (RRID:SCR_002652) Copy   

•   Source: SciCrunch Registry

http://genes.mit.edu/GENSCAN.html

Web server for identification of complete gene structures in genomic DNA.Tool for predicting locations and exon-intron structures of genes in genomic sequences from variety of organisms. Used for prediction of complete gene structures in human genomic DNA.

Proper citation: GENSCAN (RRID:SCR_013362) Copy   

•   Source: SciCrunch Registry

http://www.labarchives.com

An ELN (electronic lab notebook) software application where researchers can record and organize their data in lieu of a paper notebook. Users can store and edit texts, PDFs, spreadsheets, images, sample collections, and other types of data. LabArchives automatically backs up data and data can be accessed anywhere. Users can choose to use the professional edition of LabArhives, the classroom edition, or to purchase an enterprise license.

Proper citation: LabArchives (RRID:SCR_013973) Copy   

•   Source: SciCrunch Registry

http://lilab.stanford.edu/SNPiR/

Software for reliable Identification of Genomic Variants Using RNA-seq Data.

Proper citation: SNPiR (RRID:SCR_000557) Copy   

•   Source: SciCrunch Registry

http://www.stanford.edu/~cpatton/maxc.html

A series of programs for determining the free metal concentration in the presence of chelators or total metal given a desired free concentration.

Proper citation: MAXCHELATOR (RRID:SCR_000459) Copy   

•   Source: SciCrunch Registry

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

A Simple Software Tool to Permit Analysis of Replicate Cores on Tissue Microarrays., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: TMA-Combiner (RRID:SCR_005600) Copy   

•   Source: SciCrunch Registry

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

https://cran.r-project.org/src/contrib/Archive/PoissonSeq/

Software package that implements a method for normalization, testing, and false discovery rate estimation for RNA-sequencing data.

Proper citation: PoissonSeq (RRID:SCR_001784) Copy   

•   Source: SciCrunch Registry

https://github.com/pmelsted/BFCounter

Software program for counting k-mers in DNA sequence data. It identifies all the k-mers that occur more than once in a DNA sequence data set using a Bloom filter, a probabilistic data structure that stores all the observed k-mers implicitly in memory with greatly reduced memory requirements.

Proper citation: BFCounter (RRID:SCR_001248) Copy   

•   Source: SciCrunch Registry

https://github.com/nolanlab/cytospade

Cytoscape plugin that provides a high-performance implementation of an interface for the Spanning-tree Progression Analysis of Density-normalized Events (SPADE) algorithm for tree-based analysis and visualization of high-dimensional cytometry data.

Proper citation: CytoSPADE (RRID:SCR_001457) Copy   

•   Source: SciCrunch Registry

http://genomine.org/qvalue/

Features: * This software takes a list of p-values resulting from the simultaneous testing of many hypotheses and estimates their q-values. A point-and-click interface is now available! * The q-value of a test measures the proportion of false positives incurred (called the false discovery rate) when that particular test is called significant. * A short tutorial on q-values and false discovery rates is provided with the manual. * Various plots are automatically generated, allowing one to make sensible significance cut-offs. * Several mathematical results have recently been shown on the conservative accuracy of the estimated q-values from this software. * The software can be applied to problems in genomics, brain imaging, astrophysics, and data mining. This research was supported in part by a National Science Foundation graduate research fellowship.

Proper citation: Q-Value Software (RRID:SCR_008538) Copy   

•   Source: SciCrunch Registry

http://www.hybrow.org/

A prototype bioinformatics tool for designing hypotheses and evaluating them for consistency with existing knowledge. It consists of a modeling framework with the ability to accommodate diverse biological information sources, an event-based ontology for representing biological processes at different levels of detail, a database to query information in the ontology, and programs to perform hypothesis design and evaluation. There are five key components involved in making HyBrow work. # The Event-based ontology for representing biological knowledge # The Discreet Event Systems based conceptual framework which provides the theory that allows us to make statements in a context free formal language (made up of the ontology) and evaluate the statements for validity using constraints declared on existing data # The rule library that provides the steps to apply those constraints and decide support, contradiction or no comment. # The relational database that stores existing information structured into the ontology. # The user interface.

Proper citation: HyBrow (Hypothesis Browser) (RRID:SCR_006272) Copy   

•   Source: SciCrunch Registry

http://vis.stanford.edu/wrangler/

Wrangler is an interactive tool for data cleaning and transformation. Spend less time formatting and more time analyzing your data. Why wrangle? * Too much time is spent manipulating data just to get analysis and visualization tools to read it. Wrangler is designed to accelerate this process: spend less time fighting with your data and more time learning from it. * Wrangler allows interactive transformation of messy, real-world data into the data tables analysis tools expect. Export data for use in Excel, R, Tableau, Protovis, ... * Want to learn more about Wrangler''s design? Take a look at our research paper. * Wrangler is still a work-in-progress. Please share your feedback and feature requests!

Proper citation: DataWrangler (RRID:SCR_006335) Copy   

•   Source: SciCrunch Registry