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http://globin.cse.psu.edu/

Data and tools for studying the function of DNA sequences, with an emphasis on those involved in the production of hemoglobin. It includes information about naturally-occurring human hemoglobin mutations and their effects, experimental data related to the regulation of the beta-like globin gene cluster, and software tools for comparing sequences with one another to discover regions that are likely to play significant roles.

Proper citation: Globin Gene Server (RRID:SCR_001480) Copy   

•   Source: SciCrunch Registry

https://jhuccs1.us/nash/

Clinical research network to focus on the etiology, contributing factors, natural history, complications, and therapy of nonalcoholic steatohepatitis. They research the nature and underlying cause of Nonalcoholic Steatohepatitis (NASH) and conduct clinical studies on prevention and treatment. Approximately 1,500 pediatric and adult participants throughout the United States and Canada with nonalcoholic fatty liver disease (NAFLD) have enrolled into a database. The NASH CRN has recently reopened the database to enroll additional pediatric and adult participants with NAFLD. Serum, liver tissue, and genomic DNA samples are being collected and stored in the NIDDKrepository for ongoing as well as future studies. A three-arm randomized, placebo-controlled clinical trial of pioglitazone versus vitamin E completed enrollment in 2009. In addition to this adult trial, a similar trial in pediatric NASH patients randomized 180 children to receive treatment with vitamin E, metformin, or placebo.

Proper citation: Nonalcoholic Steatohepatitis Clinical Research Network (RRID:SCR_001519) Copy   

•   Source: SciCrunch Registry

http://www.stjudebgem.org/web/mainPage/mainPage.php

This database contains gene expression patterns assembled from mouse nervous tissues at 4 time points throughout brain development including embryonic (e) day 11.5, e15.5, postnatal (p) day 7 and adult p42. Using a high throughput in situ hybridization approach we are assembling expression patterns from selected genes and presenting them in a searchable database. The database includes darkfield images obtained using radioactive probes, reference cresyl violet stained sections, the complete nucleotide sequence of the probes used to generate the data and all the information required to allow users to repeat and extend the analyses. The database is directly linked to Pubmed, LocusLink, Unigene and Gene Ontology Consortium housed at the National Center for Biotechnology Information (NCBI) in the National Library of Medicine. These data are provided freely to promote communication and cooperation among research groups throughout the world.

Proper citation: Brain Gene Expression Map (RRID:SCR_001517) Copy   

•   Source: SciCrunch Registry

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

http://www.retinalmaps.com.au/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 23,2022. A database of over 700 retinal topography maps of a wide variety of species published in a diversity of journals. It has been assembled to assist vision and neuroscience researchers to locate and compare the distribution of retinal neurons within and across species. The maps can be searched by taxonomic or common name classification, cell type sampled, type of retinal specialization and staining/visualization method. Maps can be compared by selecting multiple maps and clicking the Compare Selected button. An interactive spreadsheet can be also downloaded.

Proper citation: Retinal Topography Maps Database (RRID:SCR_001399) Copy   

•   Source: SciCrunch Registry

http://www.bioconductor.org/packages/2.14/bioc/html/CGHbase.html

Software package that contains functions and classes that are needed by arrayCGH packages.

Proper citation: CGHbase (RRID:SCR_001279) Copy   

•   Source: SciCrunch Registry

http://www.nb.uw.edu/

Biomedical technology research center that provides state-of-the-art surface analysis expertise, instrumentation, experimental protocols, and data analysis methods to address surface-related biomedical problems. NESAC/BIO develops and applies surface science methodologies that produce a full understanding of the surface composition, structure, spatial distribution, and orientation of biomaterials and adsorbed biomolecules. The NESAC/BIO program identifies areas where surface science must evolve to keep pace with the growth in biochemical knowledge and biomaterial fabrication technology, and develops instrumentation, experimental protocols, and data analysis methods to achieve this evolution. NESAC/BIO provides state-of-the-art surface analysis tools to researchers in the biomedical community. You can gain access to the NESAC/BIO facilities in one of the following ways: * Collaborative: Propose a project to collaborate on with NESAC/BIO. The project should be rewarding for both groups, and the results should reflect the utility of surface analysis for biomedical research * Service: Ask NESAC/BIO to analyze your biomaterial specimens. The spectra obtained from the analyses will be interpreted for you. * Training: Visit the University of Washington to receive training in surface analysis and personally run experiments for your individual research projects. These experiments should have a high probability for yielding useful information and should not involve the development of new ESCA techniques or methodologies.

Proper citation: National ESCA and Surface Analysis Center for Biomedical Problems (RRID:SCR_001430) Copy   

•   Source: SciCrunch Registry

https://www.mristudio.org/

An image processing program running under Windows suitable for such tasks as tensor calculation, color mapping, fiber tracking, and 3D visualization. Most of operations can be done with only a few clicks. This tool evolved from DTI Studio. Tools in the program can be grouped in the following way: * Image Viewer * Diffusion Tensor Calculations * Fiber Tracking and Editing * 3D Visualization * Image File Management * Region of Interesting (ROI) Drawing and Statistics * Image Registration

Proper citation: MRI Studio (RRID:SCR_001398) Copy   

•   Source: SciCrunch Registry

http://bmsr.usc.edu/software/pneuma/

A set of modules that are used to simulate the autoregulation of the cardiovascular and respiratory systems under conditions of changing sleep-wake state and a variety of physiological and pharmacological interventions. It models the dynamic interactions that take place among the various component mechanisms, including those involved in the chemical control of breathing, heart rate, and blood pressure, as well as the effects of changes in the sleep-wake state and arousal from sleep. PNEUMA includes the autonomic control of the cardiovascular system, chemoreflex and state-related control of breath-to-breath ventilation, state-related and chemoreflex control of upper airway potency, as well as respiratory and circulatory mechanics. The model is capable of simulating the cardiorespiratory responses to sleep onset, arousal, continuous positive airway pressure, the administration of inhaled carbon dioxide and oxygen, Valsalva and Mueller maneuvers, and Cheyne-Stokes respiration during sleep. In PNEUMA 3.0, we have extended the existing integrative model of respiratory, cardiovascular, and sleepwake state control, to incorporate a sub-model of glucoseinsulinfatty acid regulation. The extended model is capable of simulating the metabolic control of glucoseinsulin dynamics and its interactions with the autonomic nervous system. The interactions between autonomic and metabolic control include the circadian regulation of epinephrine secretion, epinephrine regulation on dynamic fluctuations in glucose and free fatty acids in plasma, metabolic coupling among tissues and organs mediated by insulin and epinephrine, as well as the effect of insulin on peripheral vascular sympathetic activity. This extended model represents a starting point from which further in silico investigations into the interaction between the autonomic nervous system and the metabolic control system can proceed. Features in PNEUMA 3.0 * Incorporates metabolic component based on prior models of glucose-insulin regulation and free fatty acid (FFA) regulation. * Changes in sympathetic activity from the autonomic portion of PNEUMA produce changes in epinephrine output, which in turn affects the metabolic sub-model. * Inputs from the dietary intake of glucose and external interventions, such as insulin injections, have also been incorporated. * Also incorporated is autonomic feedback from the metabolic component to the rest of PNEUMA: changes in insulin level lead to changes in sympathetic tone. System Requirements: PNEUMA requires Matlab R2007b or higher with the accompanying version of Simulink to be installed on your computer.

Proper citation: PNEUMA (RRID:SCR_001391) Copy   

•   Source: SciCrunch Registry

https://cde.nlm.nih.gov/

A repository of Common Data Elements (CDE). The CDE is a standardized, precisely defined question, paired with a set of allowable responses, used systematically across different sites, studies, or clinical trials to ensure consistent data collection. Multiple CDEs (from one or more Collections) can be curated into Forms. Forms in the Repository might be original, or might recreate the format of real-world data collection instruments or case report forms. NIH has endorsed collections of CDEs that meet established criteria. NIH-endorsed CDEs are designated with a gold ribbon. Users can Browse NIH-Endorsed CDEs, Browse All CDEs, or Browse Forms.

Proper citation: NIH Common Data Element Repository (RRID:SCR_001390) Copy   

•   Source: SciCrunch Registry

http://www.bioconductor.org/packages/release/bioc/html/simpleaffy.html

Software package that provides high level functions for reading Affy .CEL files, phenotypic data, and then computing simple things with it, such as t-tests, fold changes and the like. It makes heavy use of the affy library. It also has some basic scatter plot functions and mechanisms for generating high resolution journal figures.

Proper citation: Simpleaffy (RRID:SCR_001302) Copy   

•   Source: SciCrunch Registry

http://www.opencolleges.edu.au/informed/learning-strategies/

Interactive infographic of a brain exploring more than 100,000 chemical reactions, highlighted by areas and explanations of what that area is known to do.

Proper citation: Open Colleges Interactive Brain (RRID:SCR_001427) Copy   

•   Source: SciCrunch Registry

https://codr.c-path.org/

A repository of de-identified control arm data of patients from clinical studies of Alzheimer's disease and Mild Cognitive Impairment. It provides the ability to analyze the data online with the R statistical analysis program, create and download standard reports, run complex queries, or download data to a desktop for further analysis. Additional data will be added to the database over time. Critical Path Institute consortia members and qualified researchers may upload and work on scientific data relevant to biomarkers of drug toxicity, neurodegenerative diseases, and patient-reported outcomes.

Proper citation: CODR: C PATH On Line Data Repository (RRID:SCR_001388) Copy   

•   Source: SciCrunch Registry

http://c-path.org/programs/camd/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on July 8, 2022. Consortium developing new technologies and methods to accelerate the development and review of medical products for neurodegenerative diseases. It is focused on accelerating drug development for patients with chronic neurodegenerative disease, namely, Alzheimer's disease (AD) and Parkinson's disease (PD), by advancing drug development tools for evaluating drug efficacy, conducting clinical trials, and streamlining the process of regulatory review. The consortium focuses on sharing precompetitive patient-level data from the control arms of legacy clinical trials, developing new tools to be submitted to the regulatory agencies, and developing consensus data standards. CAMD has the following areas of focus: (1) qualification of biomarkers, (2) development of common data standards, (3) creation of integrated databases for clinical trials data, and (4) development of quantitative model-based tools for drug development. Regulatory milestones include a qualification opinion with EMA for the use of low baseline hippocampal volume for patient enrichment in pre-dementia trials, and most recently, positive regulatory decisions from the FDA and EMA for the use of a clinical trial simulation tool to aid in trials for mild to moderate stages of AD., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: CAMD (RRID:SCR_001389) Copy   

•   Source: SciCrunch Registry

http://sourceforge.net/projects/mutascope/

Software suite to analyze data from high throughput sequencing of PCR amplicons, with an emphasis on normal-tumor comparison for the accurate and sensitive identification of low prevalence mutations.

Proper citation: Mutascope (RRID:SCR_001265) Copy   

•   Source: SciCrunch Registry

http://mugsy.sourceforge.net/

Software resource for multiple whole genome alignment. It uses Nucmer, a custom graph-based segmentation procedure, for pairwise alignment, and the Seqan:TCoffee's multiple alignment strategy.

Proper citation: Mugsy (RRID:SCR_001414) Copy   

•   Source: SciCrunch Registry

http://www.immunetolerance.org/

International clinical research consortium dedicated to the clinical evaluation of novel tolerogenic approaches for the treatment of autoimmune diseases, asthma and allergic diseases, and the prevention of graft rejection. They aim to advance the clinical application of immune tolerance by performing high quality clinical trials of emerging therapeutics integrated with mechanism-based research. In particular, they aim to: * Establish new tolerance therapeutics * Develop a better understanding of the mechanisms of immune function and disease pathogenesis * Identify new biomarkers of tolerance and disease Their goals are to identify and develop treatment game changers for tolerance modulating therapies for the treatment of immune mediated diseases and disabling conditions, and to conduct high quality, innovative clinical trials and mechanistic studies not likely to be funded by other sources or to be conducted by private industry that advance our understanding of immunological disorders. In the Immune Tolerance Network's (ITN) unique hybrid academic/industry model, the areas of academia, government and industry are integral to planning and conducting clinical studies. They develop and fund clinical trials and mechanistic studies in partnership. Their development model is a unique, interactive process. It capitalizes on their wide-ranging, multidisciplinary expertise provided by an advisory board of highly respected faculty from institutions worldwide. This model gives investigators special insight into developing high quality research studies. The ITN is comprised of leading scientific and medical faculty from more than 50 institutions in nine countries worldwide and employs over 80 full-time staff at the University of California San Francisco (UCSF), Bethesda, Maryland and Benaroya Research Institute in Seattle, Washington.

Proper citation: Immune Tolerance Network (ITN) (RRID:SCR_001535) 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.farsight-toolkit.org/wiki/FARSIGHT_Toolkit

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 23, 2022. A collection of software modules for image data handling, pre-processing, segmentation, inspection, editing, post-processing, and secondary analysis. These modules can be scripted to accomplish a variety of automated image analysis tasks. All of the modules are written in accordance with software practices of the Insight Toolkit Community. Importantly, all modules are accessible through the Python scripting language which allows users to create scripts to accomplish sophisticated associative image analysis tasks over multi-dimensional microscopy image data. This language works on most computing platforms, providing a high degree of platform independence. Another important design principle is the use of standardized XML file formats for data interchange between modules.

Proper citation: Farsight Toolkit (RRID:SCR_001728) Copy   

•   Source: SciCrunch Registry

http://www.glycosciences.de/tools/glytorsion/

Service that performs a statistical analysis of carbohydrate torsion angles derived from the Protein Data Bank. Such as protein conformation can be described by the backbone torsion angles, a carbohydrate structure is mainly characterised by its linkage torsions. With the aid of pdb2linucs, a dataset of carbohydrate torsion angles was derived from from carbohydrate structures found in the PDB. This weekly updated dataset contains, besides linkage torsions, also ring torsions, omega torsions, N-acetyle group torsions and sidechain torsions of Asn residues involved in Glycan bonds. It can be queried by GlyTorsion.

Proper citation: GlyTorsion (RRID:SCR_001568) Copy   

•   Source: SciCrunch Registry