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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://www.k-state.edu/

Public doctoral university located in Manhattan, Kansas that is involved with research, especially agricultural.

Proper citation: Kansas State University; Kansas; USA (RRID:SCR_001533) Copy   

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https://repository.niddk.nih.gov/study/81

Multi-center, randomized controlled study designed to determine if continuing interferon long term over several years will suppress the Hepatitis C virus, prevent progression to cirrhosis, prevent liver cancer and reduce the need for liver transplantation. Patient enrollment began in 2000 and was completed in 2003 at 10 clinical centers, which were supported by a data coordinating center, virological testing center, and central sample repository. Patients with chronic hepatitis C and advanced fibrosis or cirrhosis on liver biopsy who failed to respond to a previous course of interferon alfa were enrolled in this study. Patients were initially treated with a 24-week course of peginterferon alfa-2a and ribavirin. Patients who remained hepatitis C virus RNA positive were then randomized to receive maintenance, low-dose peginterferon or to be followed on no treatment. Liver biopsies were done before enrollment and after 2 and 4 years of treatment or follow-up. The endpoints were development of cirrhosis, hepatic decompensation, hepatocellular carcinoma, death, or liver transplantation. 1050 patients were randomized and followed through the 4 year randomized phase of the trial and as long as 4 years off treatment. Serum samples collected at multiple time points, DNA and liver tissue are available for scientific investigation.

Proper citation: HALT-C Trial (RRID:SCR_001534) Copy   

•   Source: SciCrunch Registry
  

http://www.ncibi.org/

The Center develops conceptual models, computational infrastructure, an integrated knowledge repository, and query and analysis tools that enable scientists to effectively access and integrate the wealth of biological data. The National Center for Integrative Biomedical Informatics (NCIBI) was founded in October 2005 and is one of seven National Centers for Biomedical Computing (NCBC) in the NIH Roadmap. NCIBI is based at the University of Michigan as a part of the Center for Computational Medicine and Biology (CCMB). NCIBI is composed of biomedical researchers, computational biologists, computer scientists, developers and human-computer interaction specialists organized into seven major core functions. They work in interdisciplinary teams to collectively develop tools that are not only computationally powerful but also biologically relevant and meaningful. The four initial Driving Biological Projects (prostate cancer progression, Type 1 and type 2 diabetes and bipolar disorder) provide the nucleation point from which tool development is informed, launched, and tested. In addition to testing tools for function, a separate team is dedicated to testing usability and user interaction that is a unique feature of this Center. Once tools are developed and validated the goal of the Center is to share and disseminate data and software throughout the research community both internally and externally. This is achieved through various mechanisms such as training videos, tutorials, and demonstrations and presentations at national and international scientific conferences. NCIBI is supported by NIH Grant # U54-DA021519.

Proper citation: National Center for Integrative Biomedical Informatics (RRID:SCR_001538) Copy   

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https://github.com/CollasLab/edd

A ChIP-seq peak caller for detection of megabase domains of enrichment.

Proper citation: Enriched Domain Detector (RRID:SCR_001693) Copy   

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https://www.clarku.edu/centers/geospatial-analytics/terrset-liberagis-features/idrisi-gis-analysis/

Geospatial software for monitoring and modeling the Earth system. Includes tools for GIS, image processing, surface analysis, vertical applications for land change analysis and earth trends exploration, and more.

Proper citation: IDRISI (RRID:SCR_001696) Copy   

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http://cshprotocols.cshlp.org/cgi/collection/behavioral_assays

A bibliography of published Behavioral Assays by Cold Spring Harbor Protocols. Cold Spring Harbor Protocols is an interdisciplinary journal providing a definitive source of research methods in cell, developmental and molecular biology, genetics, bioinformatics, protein science, computational biology, immunology, neuroscience and imaging. Each monthly issue details multiple essential methods - a mix of cutting-edge and well-established techniques. Newly commissioned protocols and unsolicited submissions are supplemented with articles based on Cold Spring Harbor Laboratorys renowned courses and manuals. All protocols are up-to-date and presented in a consistent, easy-to-follow format.

Proper citation: Cold Spring Harbor Protocols: Collected Resources - Behavioral Assays (RRID:SCR_001697) Copy   

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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   

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http://www.stat.cmu.edu/~fiasco/

Collection of software designed to analyze fMRI data using a series of processing steps. The input is the raw data, and the outputs are statistical brain maps showing regions of neural activation. Corrections for different systematic variations in the k-space (raw) data obtained from an fMRI session (head motion, ghosting, etc) are performed first. The image is then reconstructed (using the Fast Fourier Transform) and statistical analyses run. The user has a great deal of flexibility in choosing which corrections and statistics are executed. FIASCO emphasizes correct statistical models, for example for group comparisons.

Proper citation: Functional Image Processing software Computational Olio (RRID:SCR_001689) Copy   

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http://www.bioconductor.org/packages/devel/bioc/html/CNVrd2.html

A software package that uses next-generation sequencing data to measure human gene copy number for multiple samples, indentify SNPs tagging copy number variants and detect copy number polymorphic genomic regions.

Proper citation: CNVrd2 (RRID:SCR_001723) Copy   

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http://talasso.cnb.csic.es/

Tool for quantification of human miRNA-mRNA Interactions. TaLasso is also available as Matlab or R code.

Proper citation: TaLasso (RRID:SCR_001726) Copy   

•   Source: SciCrunch Registry
  

http://www.biopax.org/

Community standard for pathway data sharing. Standard language that aims to enable integration, exchange, visualization and analysis of biological pathway data. Supports data exchange between pathway data groups and thus reduces complexity of interchange between data formats by providing accepted standard format for pathway data. Open and collaborative effort by community of researchers, software developers, and institutions. BioPAX is defined in OWL DL and is represented in RDF/XML format.Uses W3C standard Web Ontology Language, OWL.

Proper citation: Biological Pathways Exchange (RRID:SCR_001681) Copy   

•   Source: SciCrunch Registry
  

http://www.brain-dynamics.net/

The Brain Dynamics Centre (BDC) is a network of centers and units. It achieves a unique exploration of the healthy brain and disorders of brain function. It translates these insights into new ways to tailor treatments to the individual. There approach is: "integrative neuroscience" - bringing together clinical observations, theory, and modern imaging technologies. And it's theoretical framework derives from linking physiology, psychology and evolution. Additionally, BDC also actively researches ADHD and conduct disorder, stress and trauma-related problems, depression and anxiety, anorexia nervosa, psychosis (including early onset) and conversion disorders. The research facilities DBC include assessment, rooms, two cognition-brain function laboratories, genotyping and an MRI Suite with 1.5 and 3T GE systems. BDC is the coordinating site for an international network - BRAINnet. It has over 180 members, and coordinates access to the first standardized database on the human brain for scientific purposes: Brain Resource International Database.

Proper citation: Brain Dynamics Centre (RRID:SCR_001685) Copy   

•   Source: SciCrunch Registry
  

https://people.cas.sc.edu/rorden/ezdicom/index.html

Software designed to display most medical images, including MRI, CT, X-ray, and ultrasound. All versions of ezDICOM can automatically detect the format of a medical image and display it on the screen. The software is easy to use, mature, and can view a wide range of medical images including proprietary formats as well as images in the DICOM standard. The software will also automatically recognize and display Analyze, GE (LX, Genesis), Interfile, Siemens (Magnetom, Somatom) and NEMA images.

Proper citation: ezDICOM (RRID:SCR_001686) Copy   

•   Source: SciCrunch Registry
  

http://bioconductor.org/packages/2.13/bioc/html/sSeq.html

Software package to discover the genes that are differentially expressed between two conditions in RNA-seq experiments. Gene expression is measured in counts of transcripts and modeled with the Negative Binomial (NB) distribution using a shrinkage approach for dispersion estimation. The method of moment (MM) estimates for dispersion are shrunk towards an estimated target, which minimizes the average squared difference between the shrinkage estimates and the initial estimates. The exact per-gene probability under the NB model is calculated, and used to test the hypothesis that the expected expression of a gene in two conditions identically follow a NB distribution.

Proper citation: sSeq (RRID:SCR_001719) Copy   

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https://protein.mpiib-berlin.mpg.de/cgi-bin/pdbs/2d-page/extern/index.cgi

The Proteome 2D-PAGE Database system for microbial research is a curated database for storing and investigating proteomics data. Software tools are available and for data submission, please contact the Database Curator. Established at the Max Plank Institution for Infection Biology, this system contains four interconnected databases: i.) 2D-PAGE Database: Two dimensional electrophoresis (2-DE) and mass spectrometry of diverse microorganisms and other organisms. This database currently contains 4971 identified spots and 1228 mass peaklists in 44 reference maps representing experiments from 24 different organisms and strains. The data were submitted by 84 Submitters from 24 Institutes and 12 nations. It also contains various software tools that are important in formatting and analyzing gels and mass peaks; software include: *TopSpot: Scanning the gel, editing the spots and saving the information *Fragmentation: Fragmentation of the gel image into sections *MS-Screener: Perl script to compare the similarity of MALDI-PMF peaklists *MS-Screener update: MS-Screener can be used to compare mass spectra (MALDI-MS(/MS) as well as ESI-MS/MS spectra) on the basis of their peak lists (.dta, .pkm, .pkt, or .txt files), to recalibrate mass spectra, to determine and eliminate exogenous contaminant peaks, and to create matrices for cluster analyses. *GelCali: Online calibration of the Mr- and pI-axis of 2-DE gels with mathematical regression methods ii.)Isotope Coded Affinity Tag (ICAT)-LC/MS database: Isotope Coded Affinity Tag (ICAT)-LC/MS data for Mycobacterium tuberculosis strain BCG versus H37Rv. iii.) FUNC_CLASS database: Functional classification of diverse microorganism. This database also integrates genomic, proteomic, and metabolic data. iv.) DIFF database: Presentation of differently regulated proteins obtained by comparative proteomic experiments using computerized gel image analysis.

Proper citation: Proteome 2D-PAGE Database (RRID:SCR_001678) Copy   

•   Source: SciCrunch Registry
  

https://bvsalud.org/en/

VHL is a library, a decentralized and dynamic information-source collection, designed to provide equitable access to scientific knowledge on health. This collection operates as an Internet network of products and services, structured to progressively meet the need for information on health on the part of authorities, administrators, researchers, professors, students, professionals, the media and the general public. It sets itself apart from other information sources available on the Internet due to its selection criteria and quality control. The Virtual Health Library is envisioned as the broad of scientific and technical knowledge based in health-entered, organized, and stored in electronic format in the countries of the Region, universally accessible on the Internet and compatible with international databases. The VHL is a common space shared by information users, producers and intermediaries. It is based on the information paradigm set by the Internet, where users may interact with networks of information sources and with other users. The most important consequence of this paradigm is the convergence of functions and activities of production, intermediation and use of information sources. It will also be possible to enrich, schedule, reformulate, and/or translate the basic information sources into new information products and services, with value added, in order to meet more efficiently the information needs of users from specific communities. BIREME has established a plan of action to implement the Virtual Health Library based on 5 lines of action: promotion and marketing; realignment of traditional products and services; production of electronic publications; development of tools for integrating and locating information; and development of other Virtual Health Library components. Sponsors: VHL is supported by the Latin-American and Caribbean Center on Health Sciences Information.

Proper citation: Virtual Health Library (RRID:SCR_001676) Copy   

•   Source: SciCrunch Registry
  

http://ribosome.fandm.edu

This is a database of 16S and 23S ribosomal RNA mutations reported in literature, expanded to include mutations in ribosomal proteins and ribosomal factors. Access to the expanded versions of the 16S and 23S Ribosomal RNA Mutation Databases has been improved to permit searches of the lists of alterations for all the data from (1) one specific organism, (2) one specific nucleotide position, (3) one specific phenotype, or (4) a particular author. Please send bibliographic citations for published work to be included in The Ribosomal Mutation Database to the curator via email. The database currently consists of 1024 records, including 485 16S rRNA records from Escherichia coli, 37 16S-like rRNA records from other organisms, 421 23S rRNA records from E. coli, and 81 23S-like records from other organisms. The numbering of positions in all records corresponds to the numbering in E. coli. We welcome any suggested revisions to the database, as well as information about newly characterized 16S or 23S rRNA mutations. The expanded database will be renamed to The Ribosomal Mutation Database and will include mutations in ribosomal proteins and ribosomal factors.

Proper citation: Ribosomal Mutation Database (RRID:SCR_001677) Copy   

•   Source: SciCrunch Registry
  

http://dial.mc.duke.edu/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 23,2022. The Duke Image Analysis Laboratory (DIAL) is committed to providing comprehensive imaging support in research studies and clinical trials to various agencies. The capabilities of the lab include protocol development, site training and certification, and image archival and analysis for a variety of modalities including magnetic resonance imaging, magnetic resonance spectroscopy, computed tomography and nuclear medicine. DIAL uses the latest technologies to analyze Magnetic Resonance Imaging (MRI) data sets of the brain. Currently the lab is engaged in measurement of the hippocampus, amygdala, caudate, ventricular system, and other brain regional volumes. Each of these techniques have undergone a rigorous validation process. The measurements of brain structures provide a useful means of non-invasively testing for changes in the brain of the patient. Changes over time in the brain can be detected, and evaluated with respect to the treatment that the patient is receiving. Magnetic Resonance Spectroscopy (MRS) allows DIAL to obtain an accurate profile of the chemical content of the brain. This sensitive technique can detect small changes in the metabolic state of the brain; changes that vary in response to administration of therapeutic agents. The ability to detect these subtle shifts in brain chemistry allows DIAL to identify changes in the brain with more sensitivity than allowed by image analysis. In this respect, NMR spectroscopy can provide early detection of changes in the brain, and serves to compliment the data obtained from image analysis. Additionally, DIAL also contains SQUID (Scalable Query Utility and Image Database). It is an image management system developed to facilitate image management in research and clinical trials: SQUID offers secure, redundant image storage and organizational functions for sorting and searching digital images for a variety of modalities including MRI, MRS, CAT Scan, X-Ray and Nuclear Medicine. SQUID can access images directly from DUMC scanners. Data can also be loaded via DICOM CDs, THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: Duke University Medical Center: Duke Image Analysis Laboratory (RRID:SCR_001716) Copy   

•   Source: SciCrunch Registry
  

http://www.kcl.ac.uk/index.aspx

Public research university located in London, United Kingdom that offers undergraduate, graduate, and professional degree programs in medicine, economics, social sciences, etc.

Proper citation: King's College London; London; United Kingdom (RRID:SCR_001744) Copy   

•   Source: SciCrunch Registry