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http://www.mri-resource.kennedykrieger.org/
Biomedical technology research center that provides expertise for the design of quantitative magnetic resonance imaging (MRI) and spectroscopy (MRS) data acquisition and processing technologies that facilitate the biomedical research of a large community of clinicians and neuroscientists in Maryland and throughout the USA. These methods allow noninvasive assessment of changes in brain anatomy as well as in tissue metabolite levels, physiology, and brain functioning while the brain is changing size during early development and during neurodegeneration, i.e. the changing brain throughout the life span. The Kirby Center has 3 Tesla and 7 Tesla state of the art scanners equipped with parallel imaging (8, 16, and 32-channel receive coils) and multi-transmit capabilities. CIS has an IBM supercomputer that is part of a national supercomputing infrastructure. Resources fall into the following categories: * MRI facilities, image acquisition, and processing * Computing facilities and image analysis * Novel statistical methods for functional brain imaging * Translating laboratory discoveries to patient treatment
Proper citation: National Resource for Quantitative Functional MRI (RRID:SCR_006716) Copy
http://www.nitrc.org/projects/longitudinal_ms/
The Longitudinal MS Lesion Imaging Archive provides Training data consisting of longitudinal images from five patients and Testing data consisting of 15 patients. Each longitudinal dataset includes T1-weighted, T2-weighted, PD-weighted, and T2-weighted FLAIR MRI with 3-5 time points acquired on a 3T MR scanner. T1-weighted images have approximately a 1mm cubic voxel resolution, while the other scans are 1mm in plane with 3mm sections. Accounting for the multiple time points, this constitutes approximately 80 individual data sets. The Training data contains manual segmentations of the MS lesions from two different raters for each of the time points provided.
Proper citation: Longitudinal MS Lesion Imaging Archive (RRID:SCR_014136) Copy
http://psychiatry.igm.jhmi.edu/SynaptomeDB/
THIS RESOURCE IS NO LONGER IN SERVICE. Documented on July 31,2025. Ontology-based knowledgebase for synaptic genes. These genes encode components of the synapse including neurotransmitters and their receptors, adhesion / cytoskeletal proteins, scaffold proteins, transporters, and others. It integrates various and complex data sources for synaptic genes and proteins., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.
Proper citation: SynaptomeDB (RRID:SCR_000157) Copy
http://www.scienceexchange.com/facilities/deep-sequencing-and-microarray-core
Our aim is to provide cost-effective and time-efficient access to cutting-edge genomic technologies and expert assistance with experimental design and data analysis.
Proper citation: JHU Deep Sequencing and Microarray Core (RRID:SCR_011045) Copy
Established to produce immortalized cell lines from human blood (EBV transformations). Offers genomics applications for single cells, including RNA-seq, gene expression profiling by qPCR and DNA amplification for whole-genome or targeted (exome or PCR-based analysis) through 10x Genomics Chromium platform (similar to Drop Seq). Offers custom genotyping to analyze short tandem repeats, variable number tandem repeats and single nucleotide polymorphisms.
Proper citation: Johns Hopkins University School of Medicine Genetic Resources Core Facility (RRID:SCR_018669) Copy
BRAIN Initiative data archive for multi-modal neurophysiological and behavioral data, supporting the Brain Behavior Quantification and Synchronization (BBQS) Program. Accessible and versatile data archive for storage, processing, and curation of multimodal neurophysiological and behavioral datasets. EMBER extends established BRAIN Initiative data infrastructure, provides new data harmonization and synchronization capabilities, and supports scalable integrations for data coordination and AI driven batch processing to enable the goals of the BBQS program.
Proper citation: Ecosystem for Multi-modal Brain-behavior Experimentation and Research (RRID:SCR_026700) Copy
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The NIDDK Information Network (dkNET) serves the needs of basic and clinical investigators by providing seamless access to large pools of data and research resources relevant to the mission of The National Institute of Diabetes Digestive and Kidney Diseases (NIDDK). dkNET is hosted at University of California San Diego, and is supported by NIH NIDDK grant U24DK097771.
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