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http://worldbiobank.net/

Founded by the physician partners of ACORN, Inc. (Accelerated Community Oncology Research Network), World BioBank embraces forward-thinking technology and a strong commitment to the advancement of bioscience. The World BioBank collects cancer samples, normal samples, and other non-neoplastic diseases. Data available include sample-specific data, patient-specific data, and study-related data. * SOLID TISSUES (snap frozen and matched formalin-fixed paraffin embedded diseased and normal internal controls) from: Surgical resections, Image-guided biopsies, Bone marrow biopsies, Endoscopic biopsies * LIQUID TISSUES: Peripheral blood, Genomic DNA (from buffy coat), Plasma, Serum World BioBank is committed to marrying samples to a wealth of longitudinal medical data and tissue-specific data.

Proper citation: World BioBank (RRID:SCR_004958) Copy   

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http://www.tumorbank.unibe.ch/

Tumorbank Bern - TBB collects high quality clinical samples since 2003 for translational research selected by expert pathologists under controlled conditions of normal and diseased tissue from different origin. The Tumor Bank is approved by the Ethical Commission of Bern, we only collect samples with written informed patient consent. Origin of Tissue: Thoracic Surgery, Gynecology, Urology, Visceral Surgery, Orthopedic Surgery, Head and Neck Surgery, Neurosurgery Tumorbank Bern TBB holds 12,000 samples from 3600 Patients. Please contact us to check if we have samples for your field of research.

Proper citation: Tumorbank Bern (RRID:SCR_004611) Copy   

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http://www.bumc.bu.edu/busm-pathology/pathology-core-services/biospecimen-archive-research-core-barc/

Biospecimen repository of normal and diseased human material from a variety of tissues and conditions along with clinical annotation. Both frozen aliquots and paraffin embedded tissue are available. Biospecimens are available to qualified researchers with IRB approval. * Preliminary inquires please contact Cheryl Spencer at cheryl.spencer (at) bmc.org

Proper citation: Boston University Biospecimen Archive Research Core (RRID:SCR_005363) Copy   

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http://cmrm.med.jhmi.edu/cmrm/atlas/human_data/file/JHUtemplate_newuser.html

DTI white matter atlases with different data sources and different image processing. These include single-subject, group-averaged, B0 correction, processed atlases (White Matter Parcellation Map, Tract-probability maps, Conceptual difference between the WMPM and tract-probability maps), and linear or non-linear transformation for automated white matter segmentation. # Adam single-subject white matter atlas (old version): These are electronic versions of atlases published in Wakana et al, Radiology, 230, 77-87 (2004) and MRI Atlas of Human White Matter, Elsevier. ## Original Adam Atlas: 256 x 256 x 55 (FOV = 246 x 246 mm / 2.2 mm slices) (The original matrix is 96x96x55 (2.2 mm isotropic) which is zerofilled to 256 x 256 ## Re-sliced Adam Atlas: 246 x 246 x 121 (1 mm isotropic) ## Talairach Adam: 246 x 246 x 121 (1 mm isotropic) # New Eve single-subject white matter atlas: The new version of the single-subject white matter atlas with comprehensive white matter parcellation. ## MNI coordinate: 181 x 217 x 181 (1 mm isotropic) ## Talairach coordinate: 181 x 217 x 181 (1 mm isotropic) # Group-averaged atlases: This atlas was created from their normal DTI database (n = 28). The template was MNI-ICBM-152 and the data from the normal subjects were normalized by affine transformation. Image dimensions are 181x217x181, 1 mm isotropic. There are two types of maps. The first one is the averaged tensor map and the second one is probabilistic maps of 11 white matter tracts reconstructed by FACT. # ICBM Group-averaged atlases: This atlas was created from ICBM database. All templates follow Radiology convention. You may need to flip right and left when you use image registration software that follows the Neurology convention.

Proper citation: DTI White Matter Atlas (RRID:SCR_005279) Copy   

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http://biobankireland.com/

Biobank Ireland Trust promotes the development of an Irish Hospital Biobank Network to coordinate collection of small samples of cancer and normal tissue and coded patient data from those having a cancer operation. This will facilitate international molecular research collaborations, which may help identify the best treatment for each individual patient - personalized medicine. Biobank Ireland is promoting the development of a Hospital Biobank Network throughout the island of Ireland as a bridge between cancer research and care. This new infrastructure will facilitate large national and international translational research collaborations that will raise Ireland''s research profile and benefit those with cancer. Researchers will have online access to samples and to restricted patient data from participating hospitals and an equitable withdrawal process for scientifically and ethically approved projects. Important research results will be explained to the public. Other Objectives: * To facilitate (inter)national translational research collaborations that may lead to new tests and better, less toxic treatments for those with cancer * To enable molecular research on cancer tissue from clinical trials patients identify the best treatment for each individual patient ������??personalized medicine������?? * Researchers will have online access to samples and restricted patient data from participating hospitals, and a fair release process for scientifically and ethically approved projects * Biobank Ireland recognizes the need to have harmonization in biobanking around the world * Important research results will be explained to the public * Biobank Ireland will seek to have the hospital-based Biobank Network funded by government as standard of care

Proper citation: Biobank Ireland Trust (RRID:SCR_006430) Copy   

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http://www.loni.usc.edu/BIRN/Projects/Mouse/

Animal model data primarily focused on mice including high resolution MRI, light and electron microscopic data from normal and genetically modified mice. It also has atlases, and the Mouse BIRN Atlasing Toolkit (MBAT) which provides a 3D visual interface to spatially registered distributed brain data acquired across scales. The goal of the Mouse BIRN is to help scientists utilize model organism databases for analyzing experimental data. Mouse BIRN has ended. The next phase of this project is the Mouse Connectome Project (https://www.nitrc.org/projects/mcp/). The Mouse BIRN testbeds initially focused on mouse models of neurodegenerative diseases. Mouse BIRN testbed partners provide multi-modal, multi-scale reference image data of the mouse brain as well as genetic and genomic information linking genotype and brain phenotype. Researchers across six groups are pooling and analyzing multi-scale structural and functional data and integrating it with genomic and gene expression data acquired from the mouse brain. These correlated multi-scale analyses of data are providing a comprehensive basis upon which to interpret signals from the whole brain relative to the tissue and cellular alterations characteristic of the modeled disorder. BIRN's infrastructure is providing the collaborative tools to enable researchers with unique expertise and knowledge of the mouse an opportunity to work together on research relevant to pre-clinical mouse models of neurological disease. The Mouse BIRN also maintains a collaborative Web Wiki, which contains announcements, an FAQ, and much more.

Proper citation: Mouse Biomedical Informatics Research Network (RRID:SCR_003392) Copy   

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http://www.cvrgrid.org/

Infrastructure for sharing cardiovascular data and data analysis tools. Human ExVivo heart data set and canine ExVivo normal and failing heart data sets are available. Canine hearts atlas and human InVivo atlases are available.

Proper citation: CardioVascular Research Grid (CVRG) (RRID:SCR_004472) Copy   

•   Source: SciCrunch Registry

http://stemcellcommons.org/

Open source environment for sharing, processing and analyzing stem cell data bringing together stem cell data sets with tools for curation, dissemination and analysis. Standardization of the analytical approaches will enable researchers to directly compare and integrate their results with experiments and disease models in the Commons. Key features of the Stem Cell Commons * Contains stem cell related experiments * Includes microarray and Next-Generation Sequencing (NGS) data from human, mouse, rat and zebrafish * Data from multiple cell types and disease models * Carefully curated experimental metadata using controlled vocabularies * Export in the Investigation-Study-Assay tabular format (ISA-Tab) that is used by over 30 organizations worldwide * A community oriented resource with public data sets and freely available code in public code repositories such as GitHub Currently in development * Development of Refinery, a novel analysis platform that links Commons data to the Galaxy analytical engine * ChIP-seq analysis pipeline (additional pipelines in development) * Integration of experimental metadata and data files with Galaxy to guide users to choose workflows, parameters, and data sources Stem Cell Commons is based on open source software and is available for download and development.

Proper citation: Stem Cell Commons (RRID:SCR_004415) 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://sumsdb.wustl.edu/sums/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on May 11, 2016. Repository of brain-mapping data (surfaces and volumes; structural and functional data) derived from studies including fMRI and MRI from many laboratories, providing convenient access to a growing body of neuroimaging and related data. WebCaret is an online visualization tool for viewing SumsDB datasets. SumsDB includes: * data on cerebral cortex and cerebellar cortex * individual subject data and population data mapped to atlases * data from FreeSurfer and other brainmapping software besides Caret SumsDB provides multiple levels of data access and security: * Free (public) access (e.g., for data associated with published studies) * Data access restricted to collaborators in different laboratories * Owner-only access for work in progress Data can be downloaded from SumsDB as individual files or as bundles archived for offline visualization and analysis in Caret WebCaret provides online Caret-style visualization while circumventing software and data downloads. It is a server-side application running on a linux cluster at Washington University. WebCaret "scenes" facilitate rapid visualization of complex combinations of data Bi-directional links between online publications and WebCaret/SumsDB provide: * Links from figures in online journal article to corresponding scenes in WebCaret * Links from metadata in WebCaret directly to relevant online publications and figures

Proper citation: SumsDB (RRID:SCR_002759) Copy   

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http://cgap.nci.nih.gov/

Project to determine the gene expression profiles of normal, precancer, and cancer cells, whose generated resources are available to the cancer community. Interconnected modules provide access to all CGAP data, bioinformatic analysis tools, and biological resources allowing the user to find in silico answers to biological questions in a fraction of the time it once took in the laboratory. * Genes * Tissues * Pathways * RNAi * Chromosomes * SAGE Genie * Tools

Proper citation: Cancer Genome Anatomy Project (RRID:SCR_003072) Copy   

•   Source: SciCrunch Registry

http://www.med.umkc.edu/psychiatry/nbtb/

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 31, 2016. The UMKC Neuroscience Brain Tissue Bank and Research Laboratory has been established to obtain, process, and distribute human brain tissue to qualified scientists and clinicians dedicated to neuroscience research. No other living organ approaches the human brain in complexity or capacity. Healthy, it astounds and inspires miracles. Diseased, it confounds and diminishes hope. The use of human brain tissue for research will provide insight into the anatomical and neurochemical aspects of diseased and non-diseased brains. While animal models are helpful and necessary in understanding disease, certain disorders can be more efficiently studied using human brain tissue. Also, modern research techniques are often best applied to human tissue. We also need samples of brain tissue that have not been affected by disease. They help us to compare a 'normal' brain with a diseased one. Also, we have a critical need for brain donations from relatives who have genetically inherited disorders. Tissue preparation consists of fresh quick-frozen tissue blocks or coronal slices (nitrogen vapor frozen; custom dissection of specific anatomic regions) or formalin-fixed coronal slices (custom dissection of specific anatomic regions).

Proper citation: UMKC Neuroscience Brain Tissue Bank and Research Laboratory (RRID:SCR_005148) Copy   

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http://en.wikibooks.org/wiki/MINC/Atlases

A linear average model atlas produced by the International Consortium for Brain Mapping (ICBM) project. A set of full- brain volumetric images from a normative population specifically for the purposes of generating a model were collected by the Montreal Neurological Institute (MNI), UCLA, and University of Texas Health Science Center at San Antonio Research Imaging Center (RIC). 152 new subjects were scanned using T1, T2 and PD sequences using a specific protocol. These images were acquired at a higher resolution than the original average 305 data and exhibit improved contrast due predominately to advances in imaging technology. Each individual was linearly registered to the average 305 and a new model was formed. In total, three models were created at the MNI, the ICBM152_T1, ICBM152_T2 and ICBM152_PD from 152 normal subjects. This resulting model is now known as the ICBM152 (although the model itself has not been published). One advantage of this model is that it exhibits better contrast and better definition of the top of the brain and the bottom of the cerebellum due to the increased coverage during acquisition. The entirely automatic analysis pipeline of this data also included grey/white matter segmentation via spatial priors. The averaged results of these segmentations formed the first MNI parametric maps of grey and white matter. The maps were never made publicly available in isolation but have formed parts of other packages for some time including SPM, FSL AIR and as models of grey matter for EEG source location in VARETTA and BRAINWAVE. Again, as these models are an approximation of Talairach space, there are differences in varying areas, to continue our use of origin shift as an example, the ICBM models are approximately 152: +3.5mm in Z and +-co-ordinate -3.5mm and 2.0mm in Y as compared to the original Talairach origin. In addition to the standard analysis performed on the ICBM data, 64 of the subjects data were segmented using model based segmentation. 64 of the original 305 were manually outlined and a resulting parametric VOI atlas built. The native data from these acquisitions was 256x256 with 1mm slices. The final image resolution of this data was 181x217x181 with 1mm isotropic voxels. Refer to the ICBM152 NonLinear if you are fitting an individual to model and do not care about left/right comparisons. A short history of the various atlases that have been produced at the BIC (McConnell Brain Imaging Center, Montreal Neurological Institute) is provided.

Proper citation: MINC/Atlases (RRID:SCR_005281) Copy   

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http://headit.ucsd.edu

Platform for sharing, download, and re-analysis or meta-analysis of sophisticated, fully annotated, human electrophysiological data sets. It uses EEG Study Schema (ESS) files to provide task, data collection, and subject metadata, including Hierarchical Event Descriptor (HED) tag descriptions of all identified experimental events. Visospatial task data also available from, http://sccn.ucsd.edu/eeglab/data/headit.html: A 238-channel, single-subject EEG data set recorded at the Swartz Center, UCSD, by Arnaud Delorme, Julie Onton, and Scott Makeig is al.

Proper citation: HeadIT (RRID:SCR_005657) Copy   

•   Source: SciCrunch Registry

http://umcd.humanconnectomeproject.org

Web-based repository and analysis site for connectivity matrices that have been derived from neuroimaging data including different imaging modalities, subject groups, and studies. Users can analyze connectivity matrices that have been shared publicly and upload their own matrices to share or analyze privately.

Proper citation: USC Multimodal Connectivity Database (RRID:SCR_012809) Copy   

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

Data set of manually-guided expert segmentation results along with magnetic resonance brain image data. Its purpose is to encourage the development and evaluation of segmentation methods by providing raw test and image data, human expert segmentation results, and methods for comparing segmentation results. Please see the MediaWiki for more information. This repository is meant to contain standard test image data sets which will permit a standardized mechanism for evaluation of the sensitivity of a given analysis method to signal to noise ratio, contrast to noise ratio, shape complexity, degree of partial volume effect, etc. This capability is felt to be essential to further development in the field since many published algorithms tend to only operate successfully under a narrow range of conditions which may not extend to those experienced under the typical clinical imaging setting. This repository is also meant to describe and discuss methods for the comparison of results.

Proper citation: Internet Brain Segmentation Repository (RRID:SCR_001994) Copy   

•   Source: SciCrunch Registry

https://www.upf.edu/web/ntsa/downloads/-/asset_publisher/xvT6E4pczrBw/content/2001-indications-of-nonlinear-deterministic-and-finite-dimensional-structures-in-time-series-of-brain-electrical-activity-dependence-on-recording-regi?p_r_p_assetEntryId=229569389&_com_liferay_asset_publisher_web_portlet_AssetPublisherPortlet_INSTANCE_xvT6E4pczrBw_type=content&_com_liferay_asset_publisher_web_portlet_AssetPublisherPortlet_INSTANCE_xvT6E4pczrBw_urlTitle=2001-indications-of-nonlinear-deterministic-and-finite-dimensional-structures-in-time-series-of-brain-electrical-activity-dependence-on-recording-regi&_com_liferay_asset_publisher_web_portlet_AssetPublisherPortlet_INSTANCE_xvT6E4pczrBw_redirect=https%3A%2F%2Fwww.upf.edu%3A443%2Fweb%2Fntsa%2Fdownloads%3Fp_p_id%3Dcom_liferay_asset_publisher_web_portlet_AssetPublisherPortlet_INSTANCE_xvT6E4pczrBw%26p_p_lifecycle%3D0%26p_p_state%3Dnormal%26p_p_mode%3Dview%26p_r_p_assetEntryId%3D229569389%26_com_liferay_asset_publisher_web_portlet_AssetPublisherPortlet_INSTANCE_xvT6E4pczrBw_cur%3D0%26p_r_p_resetCur%3Dfalse#229569389

Five data sets containing quasi-stationary, artifact-free EEG signals both in normal subjects and epileptic patients were put in the web by Ralph Andrzejak from the Epilepsy center in Bonn, Germany. Each data set contains 100 single channel EEG segments of 23.6 sec duration.

Proper citation: EEG time series Data Sets (RRID:SCR_001579) Copy   

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http://fcon_1000.projects.nitrc.org/indi/abide/

Resting state functional magnetic resonance imaging (R-fMRI) datasets from 539 individuals with autism spectrum disorder (ASD) and 573 typical controls. This initiative involved 16 international sites, sharing 20 samples yielding 1112 datasets composed of both MRI data and an extensive array of phenotypic information common across nearly all sites. This effort is expected to facilitate discovery science and comparisons across samples. All datasets are anonymous, with no protected health information included.

Proper citation: ABIDE (RRID:SCR_003612) Copy   

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https://neuinfo.org/mynif/search.php?q=nlx_144644&t=indexable&list=cover&nif=nlx_144509-1

Dataset from an investigation of biochemical evidence of myocardial strain, oxidative stress, and cardiomyocyte injury in 55 acute KD subjects (30 with paired convalescent samples), 54 febrile control (FC), and 50 healthy control (HC) children by measuring concentrations of cardiovascular biomarkers. NT-proBNP and sST2 were elevated in acute KD subjects and correlated with impaired myocardial relaxation. These findings, combined with elevated levels of cTnI, suggest that both cardiomyocyte stress and cell death are associated with myocardial inflammation in acute KD.

Proper citation: Kawasaki Disease Dataset2 (RRID:SCR_008839) Copy   

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https://www.epfl.ch/labs/mmspg/research/page-58317-en-html/bci-2/bci_datasets/

A portal containing EEG datasets (in MATLAB format) and the MATLAB software that were used to produce the results in the paper named in the title of this resource. The files published can also be used as a basis for individual research on P300-based brain-computer interfaces. The system is based on the P300 evoked potential and is tested with five severely disabled and four able-bodied subjects. For four of the disabled subjects classification accuracies of 100% are obtained. The bitrates obtained for the disabled subjects range between 10 and 25 bits/min. The effect of different electrode configurations and machine learning algorithms on classification accuracy is tested.

Proper citation: An efficient P300-based brain-computer interface for disabled subjects (RRID:SCR_001584) Copy   

•   Source: SciCrunch Registry