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http://adrc.ucsd.edu/

The UCSD ADRC conducts a wide variety of research studies dedicated to understanding the causes, clinical features, and treatments for Alzheimer's disease and related memory disorders. The goal of the center is to discover ways to prevent and eradicate the disease. The Center aims to maintain research subjects, clinical resources, and clinical data to support ongoing and proposed research and to assist in the development of new clinical and interdisciplinary research. An Alzheimer's brain bank with well characterized cases, including Mild Cognitive Impairment and Lewy Body disease, is maintained at the Center.

Proper citation: Shiley-Marcos Alzheimer's Disease Research Center (RRID:SCR_001928) Copy   

•   Source: SciCrunch Registry

https://ftp.ncbi.nlm.nih.gov/pub/mhc/mhc/Final%20Archive/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on August 23, 2019 Database was open, publicly accessible platform for DNA and clinical data related to human Major Histocompatibility Complex (MHC). Data from IHWG workshops were provided as well., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: dbMHC (RRID:SCR_002302) Copy   

•   Source: SciCrunch Registry

http://www.genenetwork.org/

Web platform that provides access to data and tools to study complex networks of genes, molecules, and higher order gene function and phenotypes. Sequence data (SNPs) and transcriptome data sets (expression genetic or eQTL data sets). Quantitative trait locus (QTL) mapping module that is built into GN is optimized for fast on-line analysis of traits that are controlled by combinations of gene variants and environmental factors. Used to study humans, mice (BXD, AXB, LXS, etc.), rats (HXB), Drosophila, and plant species (barley and Arabidopsis). Users are welcome to enter their own private data.

Proper citation: GeneNetwork (RRID:SCR_002388) Copy   

•   Source: SciCrunch Registry

http://www.thevirtualbrain.org/

Simulation software for modeling the entire human brain by combining structural and functional data from empirical neuroimaging data. It can generate local field potentials, EEG, MEG and fMRI BOLD data based on neural mass models. The user can also modify the model parameters to match clinical conditions from focal lesions or degenerative disorders.

Proper citation: Virtual brain (RRID:SCR_002249) Copy   

•   Source: SciCrunch Registry

http://amedeo.com/

A service created to allow healthcare professionals to access timely, relevant information within their respective fields. Users can subscribe to receive weekly emails with bibliographic lists about new scientific publications, personal web pages for one-time download of available abstracts, and an overview of the medical literature published in relevant journals over the past 12 to 24 months.

Proper citation: AMEDEO: The Medical Literature Guide (RRID:SCR_002284) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/miva/

Software package that is a powerful graphical interface that displays, segments, aligns, manipulates, and blends image (pixel) and geometry (real-world coordinates) data simultaneously. Several applications are directly built into MIVA. Registration modes include interactive affine transformations. Fiducial registration tools facilitate rapid alignments for inter-modality volumes. Interactive Region of Interst (ROI) and Volume-of-Interest (VOI) tools exist to segment medical images. Virtually unique to MIVA are its 3D geometry tools and their compatibility with pixel based medical images. A full 3D interactive rat brain atlas is in an fMRI module which walks one through the necessary steps of fMRI. A multiple material surface routine takes segmented medical slices and creates 3D triangulated surfaces that align along all region boarders without overlap or gaps. These surfaces are the direct input into the MIVA tetrahedral mesh generator.

Proper citation: Medical Image Visualization and Analysis (RRID:SCR_002315) Copy   

•   Source: SciCrunch Registry

http://www.ncbi.nlm.nih.gov/HTGS/

Database of high-throughput genome sequences from large-scale genome sequencing centers, including unfinished and finished sequences. It was created to accommodate a growing need to make unfinished genomic sequence data rapidly available to the scientific community in a coordinated effort among the International Nucleotide Sequence databases, DDBJ, EMBL, and GenBank. Sequences are prepared for submission by using NCBI's software tools Sequin or tbl2asn. Each center has an FTP directory into which new or updated sequence files are placed. Sequence data in this division are available for BLAST homology searches against either the htgs database or the month database, which includes all new submissions for the prior month. Unfinished HTG sequences containing contigs greater than 2 kb are assigned an accession number and deposited in the HTG division. A typical HTG record might consist of all the first-pass sequence data generated from a single cosmid, BAC, YAC, or P1 clone, which together make up more than 2 kb and contain one or more gaps. A single accession number is assigned to this collection of sequences, and each record includes a clear indication of the status (phase 1 or 2) plus a prominent warning that the sequence data are unfinished and may contain errors. The accession number does not change as sequence records are updated; only the most recent version of a HTG record remains in GenBank.

Proper citation: High Throughput Genomic Sequences Division (RRID:SCR_002150) Copy   

•   Source: SciCrunch Registry

http://ftp://ftp.ncbi.nlm.nih.gov/pub/mhc/rbc/Final Archive

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on August 23, 2019.BGMUT was database that provided publicly accessible platform for DNA sequences and curated set of blood mutation information. Data Archive are available at ftp://ftp.ncbi.nlm.nih.gov/pub/mhc/rbc/Final Archive.

Proper citation: Blood Group Antigen Gene Mutation Database (RRID:SCR_002297) Copy   

•   Source: SciCrunch Registry

http://www.ark-genomics.org/

Portal for studies of genome structure and genetic variation, gene expression and gene function. Provides services including DNA sequencing of model and non-model genomes using both Next Generation and Sanger sequencing , Gene expression analysis using both microarrays and Next Generation Sequencing, High throughput genotyping of SNP and copy number variants, Data collection and analysis supported in-house high performance computing facilities and expertise, Extensive EST clone collections for a number of animal species, all of commercially available microarray tools from Affymetrix, Illumina, Agilent and Nimblegen, Parentage testing using microsatellites and smaller SNP panels. ARK-Genomics has developed network of researchers whom they support through each stage of their genomics research, from grant application, experimental design and technology selection, performing wet laboratory protocols, through to analysis of data often in conjunction with commercial partners.

Proper citation: ARK-Genomics: Centre for Functional Genomics (RRID:SCR_002214) Copy   

•   Source: SciCrunch Registry

http://hardinmd.lib.uiowa.edu/index.html

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 2, 2025. A medical database with lists, or directories, of information in health and medicine and images of medical conditions. Users may search Hardin MD, browse through the Medical picture gallery, and sort search results by disease or alphabetical letter.

Proper citation: Hardin MD (RRID:SCR_002364) Copy   

•   Source: SciCrunch Registry

https://www.humanbrainproject.eu/

Global, collaborative effort for neuroscience, medicine and computing to understand brain, its diseases and its computational capabilities. Goal is to obtain access to research, data sources, platforms and infrastructures offered by other organisations, and enabling organizations outside HBP to use HBP platforms to pursue their own research. Coordinating these activities is the responsibility of the European Research Programme.

Proper citation: Human Brain Project EU (RRID:SCR_002241) Copy   

•   Source: SciCrunch Registry

https://cghub.ucsc.edu/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on March 17, 2022. A secure repository for storing, cataloging, and accessing cancer genome sequences, alignments, and mutation information from the Cancer Genome Atlas (TCGA) consortium and related projects. CGHub gives scientific researchers the statistical power of large cancer genome datasets to attack the molecular complexity of cancer.

Proper citation: Cancer Genomics Hub (RRID:SCR_002657) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/multimodal/

Scan-rescan imaging sessions on 21 healthy volunteers (no history of neurological disease) intended to be a resource for statisticians and imaging scientists to be able to quantify the reproducibility of their imaging methods using data available from a generic 1 hour session at 3T. Imaging modalities include MPRAGE, FLAIR, DTI, resting state fMRI, B0 and B1 field maps, ASL, VASO, quantitative T1 mapping, quantitative T2 mapping, and magnetization transfer imaging. All data have been converted to NIFTI format. Please cite: Bennett. A. Landman, Alan J. Huang, Aliya Gifford, Deepti S. Vikram, Issel Anne L. Lim, Jonathan A.D. Farrell, John A. Bogovic, Jun Hua, Min Chen, Samson Jarso, Seth A. Smith, Suresh Joel, Susumu Mori, James J. Pekar, Peter B. Barker, Jerry L. Prince, and Peter C.M. van Zijl. ?Multi-Parametric Neuroimaging Reproducibility: A 3T Resource Study?, NeuroImage. (2010) NIHMS/PMC:252138 doi:10.1016/j.neuroimage.2010.11.047

Proper citation: Multi-Modal MRI Reproducibility Resource (RRID:SCR_002442) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/msseg

Training material for the MS lesion segmentation challenge 2008 to compare different algorithms to segment the MS lesions from brain MRI scans. Data used for the workshop is composed of 54 brain MRI images and represents a range of patients and pathology which was acquired from Children's Hospital Boston and University of North Carolian. Data has initially been randomized into three groups: 20 training MRI images, 24 testing images for the qualifying and 8 for the onsite contest at the 2008 workshop. The downloadable online database consists now of the training images (including reference segmentations) and all the 32 combined testing images (without segmentations). The naming has not been changed in comparison to the workshop compeition in order to allow easy comparison between the workshop papers and the online database papers. One dataset has been removed (UNC_test1_Case02) due to considerable motion present only in its T2 image (without motion artifacts in T1 and FLAIR). Such a dataset unfairly penalizes methods that use T2 images versus methods that don't use the T2 image. Currently all cases have been segmented by expert raters at each institution. They have significant intersite variablility in segmentation. MS lesion MRI image data for this competition was acquired seperately by Children's Hospital Boston and University of North Carolina. UNC cases were acquired on Siemens 3T Allegra MRI scanner with slice thickness of 1mm and in-plane resolution of 0.5mm. To ease the segmentation process all data has been rigidly registered to a common reference frame and resliced to isotrophic voxel spacing using b-spline based interpolation. Pre-processed data is stored in NRRD format containing an ASCII readable header and a separate uncompressed raw image data file. This format is ITK compatible. If you want to join the competition, you can download data set from links here, and submit your segmentation results at http://www.ia.unc.edu/MSseg after registering your team. They require team name, password, and email address for future contact. Once experiment is completed, you can submit the segmentation data in a zip file format. Please refer submission page for uploading data format.

Proper citation: MS lesion segmentation challenge 2008 (RRID:SCR_002425) Copy   

•   Source: SciCrunch Registry

http://bioweb.ensam.inra.fr/esther

Database and tools for analysis of protein and nucleic acid sequences belonging to superfamily of alpha/beta hydrolases homologous to cholinesterases. Covers multiple species, including human, mouse caenorhabditis and drosophila., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: ESTHER (RRID:SCR_002621) Copy   

•   Source: SciCrunch Registry

https://pdbp.ninds.nih.gov

Common data management resource and web portal to promote discovery of Parkinson's Disease diagnostic and progression biomarker candidates for early detection and measurement of disease progression. PDBP will serve as multi-faceted platform for integrating existing biomarker efforts, standardizing data collection and management across these efforts, accelerating discovery of new biomarkers, and fostering and expanding collaborative opportunities for all stakeholders.

Proper citation: Parkinson’s Disease Biomarkers Program Data Management Resource (PDBP DMR) (RRID:SCR_002517) Copy   

•   Source: SciCrunch Registry

http://toc.lbg.ac.at/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on July 31,2025. The projected cluster includes the LBIs for Applied Cancer Research, Clinical Oncology and Photodynamic Therapy, Gynecology and Gynecologic Oncology, Stem Cell Transplantation and Surgical Oncology. The aim of the projected cluster Translational Oncology is the cooperative investigation of genetic and molecular biological characteristics of the tumor cells involved in minimal residual disease (MRD) in vitro and translation of the experimental and diagnostic results into the clinical practice involving therapeutic modalities with the newest generation of antitumoral drugs. Minimal residual disease is the designation for the occurrence of a low number of tumor cells remaining clinically undetected following curative therapy that give rise to tumor relapses. MRD is a central question in cancer therapy, since a major subpopulation of patients which underwent curative resection and therapy ultimately relapse and would have received more aggressive adjuvant therapy, provided that residual disease had been clearly proven. Otherwise low-risk patients would have not been treated aggressively in an adjuvant setting. MRD can be detected by methods in bone marrow or by extremely sensitive PCR (polymerase-chain-reaction)-based methods in peripheral blood. PCR-based methods allow for the characterization of tumor-specific gene expression in circulating tumor cells and thereby provide additional information in regard to malignity of cells and prognosis. The different participating institutions have extensive experience in patient care, organization of clinical studies and laboratory investigation. In particular, expert knowledge in stem cell transplantation and histological detection of MRD, multicentric clinical testing of new anticancer drugs, specialized treatment of various selected tumor entities such as neuroendocrine tumors, gene expression analysis of circulating tumor cells and tumor signatures, and in vitro characterization of chemosensitivity as well as tumor cell biology have been acquired at the individual LBIs in the past and are complementary to each other to be combined in a larger cluster structure. The detection of circulating tumor cells will be supported by ongoing EU (OVCAD OVarian CAncer Diagnosis) and GenAU projects aiming at identification of ovarian cancer cells in the blood. The assessment of methylated DNA sequences (suppressor genes) in peripheral blood as an indicator of MRD can be performed with the help of OncoLab Diagnostics GmbH. Cooperative action in this cluster, using a common tumor bank/clinical data collection and the combined clinical and experimental efforts are the base for the execution of the presented MRD project.

Proper citation: Ludwig Boltzmann Cluster Translationale Onkologie (RRID:SCR_000020) 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.opencolleges.edu.au/

A resource for online accredited courses in a wide variety of areas, including accounting, animal care, beauty, building and construction, business, education, design and writing. This resource is based in Australia.

Proper citation: Open Colleges (RRID:SCR_000418) 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