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http://www.bic.mni.mcgill.ca/ServicesAtlases/NIHPD-obj1

An unbiased standard magnetic resonance imaging template brain volume for pediatric data from the 4.5 to 18.5y age range. These volumes were created using data from 324 children enrolled in the NIH-funded MRI study of normal brain development (Almli et al., 2007, Evans and Group 2006). Tools for using these atlases can be found in the Software section. To view the atlases online, click on the appropriate JIV2 link in the Download section. You can download templates constructed for different age ranges. For each age range you will get an average T1w, T2w, PDw maps normalized between 0 and 100 and tissue probability maps, with values between 0 and 1. Also each age range includes a binary brain mask.

Proper citation: NIHPD Objective 1 atlases (4.5 - 18.5y) (RRID:SCR_008794) Copy   

•   Source: SciCrunch Registry

http://www.neuroethics.ubc.ca/

It is an interdisciplinary research group dedicated to tackling the ethical, legal, policy and social implications of frontier technological developments in the neurosciences. Our objective is to align innovations in the brain sciences with societal, cultural and individual human values through high impact research, education and outreach. The Core''s major research projects are focused on high impact, high visibility areas including the use of drugs and devices for neuroenhancement, ethics in neurodegenerative disease and regenerative medicine research, international and cross-cultural challenges in brain research, neuroimaging in the private sector, and the ethics of personalized medicine, among others. Members of the Core also lead initiatives aside from their research projects. Sponsors: This Core is supported by the University of Brititsh Columbia.

Proper citation: UBC National Core for Neuroethics (RRID:SCR_008063) Copy   

•   Source: SciCrunch Registry

http://icmic.rad.jhmi.edu/

The vision of the JHU ICMIC is to combine state-of-the-art imaging capabilities with powerful molecular biology techniques to define strategies with intent to cure. It has drawn upon its human resources at JHU to create a center consisting of a multidisciplinary group of premier individuals with diverse skills focused on translating molecular capabilities into imaging possibilities with the single purpose of understanding and curing cancer. Nearly all of the investigators participating in this ICMIC have interactive collaborative projects with one or more of the other investigators. The synergism generated by the collective skills of this unique group of individuals will lead to significant advances in the understanding of cancer and its treatment. The JHU ICMIC structure consists of four interactive and closely related research components focused on hypoxia, HIF-1, and exploiting the hypoxia response element to target cancer cells through choline kinase inhibition. These research components are anchored by the participation of world renowned expertise in HIF-1. The research components utilize MR, PET and Optical Imaging technology to understand cancer vascularization, invasion and metastasis, to achieve effective cancer therapy. The center has selected developmental projects which are highly relevant to the goals of the ICMIC and interactive with the research components. Five resources devoted to adminstration, molecular biology, imaging, probes, and translational application provide the infrastructure to support the research activities of the ICMIC. Research Components in the JHU ICMIC: - Combining Anti-angiogenic therapy with siRNA targeting of choline kinase. - Imaging the Role of HIF-1 in Breast Cancer Progression - Imaging and Targeting Hypoxia in Solid Tumors - Molecular and Functional Imaging of the HER-2/neu Receptor The following are developmental projects currently taking place in ICMIC 1. Receptor imaging using nonparamagnetic MRI contrast agents (2003) 2. New imaging agents for prostate cancer (2003) 3. Non-invasive monitoring of therapeutic effect of siRNA-mediated radiation sensitization in human prostate cancer xenografts (2003) 4. Imaging of the endothelin receptor in cancer (2003) 5. Imaging studies of c-myc regulation of tumor metabolism (2003) 6. Imaging studies of anti-tumorigenic effects of anti-oxidants in vivo (2005) 7. Molecular Imaging with Magnetic Resonance Microsystems (2005) 8. Endogenous angiogenesis inhibitors (2005) 9. MR imaging and spectroscopy in detection and localization of prostate cancer: a prospective trial in patients undergoing cystoprostatectomy and radical prostatectomy. (2005) 10. A versatile visualization system for the analysis of multi-modality and multidimensional cancer imaging (2007) 11. Non-invasive imaging of CXCR4 expression in breast cancer (2007)

Proper citation: John Hopkins University, In-Vivo Cellular Molecular Imaging Center (RRID:SCR_013198) Copy   

•   Source: SciCrunch Registry

https://www.broadinstitute.org/ccle/

A collaborative project between the Broad Institute and the Novartis Institutes for Biomedical Research and its Genomics Institute of the Novartis Research Foundation, with the goal of conducting a detailed genetic and pharmacologic characterization of a large panel of human cancer models. The CCLE also works to develop integrated computational analyses that link distinct pharmacologic vulnerabilities to genomic patterns and to translate cell line integrative genomics into cancer patient stratification. The CCLE provides public access to genomic data, analysis and visualization for about 1000 cell lines.

Proper citation: Cancer Cell Line Encyclopedia (RRID:SCR_013836) Copy   

•   Source: SciCrunch Registry

http://lincs.hms.harvard.edu/

Center that is part of the NIH Library of Integrated Network-based Cellular Signatures (LINCS) Program. Its goals are to collect and disseminate data and analytical tools needed to understand how human cells respond to perturbation by drugs, the environment, and mutation.

Proper citation: HMS LINCS Center (RRID:SCR_016370) Copy   

•   Source: SciCrunch Registry

https://community.brain-map.org/t/allen-human-reference-atlas-3d-2020-new/405

Parcellation of adult human brain in 3D, labeling every voxel with brain structure spanning 141 structures. These parcellations were drawn and adapted from prior 2D version of adult human brain atlas.

Proper citation: Allen Human Reference Atlas, 3D, 2020 (RRID:SCR_017764) Copy   

•   Source: SciCrunch Registry

https://edspace.american.edu/openbehavior/project/deepbehavior/

Project related to behavior tracking and analysis. Provides deep learning toolbox that automates taking high speed quality video to track behavior in rodents and humans.

Proper citation: DeepBehavior project (RRID:SCR_021387) Copy   

•   Source: SciCrunch Registry

https://gillisweb.cshl.edu/Primate_MTG_coexp/

We aligned single-nucleus atlases of middle temporal gyrus (MTG) of 5 primates (human, chimp, gorilla, macaque and marmoset) and identified 57 consensus cell types common to all species. We provide this resource for users to: 1) explore conservation of gene expression across primates at single cell resolution; 2) compare with conservation of gene coexpression across metazoa, and 3) identify genes with changes in expression or connectivity that drive rapid evolution of human brain.

Proper citation: Gene functional conservation across cell types and species (RRID:SCR_023292) Copy   

•   Source: SciCrunch Registry

http://www.loni.usc.edu/

Biomedical technology resource center specializing in novel approaches and tools for neuroimaging. It develops novel strategies to investigate brain structure and function in their full multidimensional complexity. There is a rapidly growing need for brain models comprehensive enough to represent brain structure and function as they change across time in large populations, in different disease states, across imaging modalities, across age and sex, and even across species. International networks of collaborators are provided with a diverse array of tools to create, analyze, visualize, and interact with models of the brain. A major focus of these collaborations is to develop four-dimensional brain models that track and analyze complex patterns of dynamically changing brain structure in development and disease, expanding investigations of brain structure-function relations to four dimensions.

Proper citation: Laboratory of Neuro Imaging (RRID:SCR_001922) Copy   

•   Source: SciCrunch Registry

http://www.cs.tau.ac.il/~shlomito/tissue-net/

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 23, 2016. Network visualizations in which the expression and predicted flux data are projected over the global human network. These network visualizations are accessible through the supplemental website using the publicly available Cytoscape software (Cline, Smoot et al. 2007). Since many high degree nodes exist in the network, special layouts are required to produce network visualizations that are readily interpretable. To this end we produced network visualizations in which hub nodes are repeated multiple times and hence layouts with a small number of edge crossings can be generated. Contains entries for brain compartments and brain pathways.

Proper citation: Network-based Prediction of Human Tissue-specific Metabolism (RRID:SCR_007392) Copy   

•   Source: SciCrunch Registry

http://www.emcdda.europa.eu/eib

The EIB provides assessment tests for substance disorder related clinical instruments that are freely available. Details regarding copyright and/or possible use restrictions are specified for each instrument. Instruments are generally classed according to the intervention field they are designed to be used in (treatment, prevention, or harm reduction), though some instruments may be usable in more than one field.

Proper citation: Evaluation Instruments Bank (RRID:SCR_013246) Copy   

•   Source: SciCrunch Registry

https://github.com/dorianps/LESYMAP

Software R package to conduct lesion-to-symptom mapping from human MRI data.Takes lesion maps and cognitive performance scores from patients with stroke, and maps brain areas responsible for cognitive deficit.

Proper citation: LESYMAP (RRID:SCR_017967) Copy   

•   Source: SciCrunch Registry

http://aws.amazon.com/1000genomes/

A dataset containing the full genomic sequence of 1,700 individuals, freely available for research use. The 1000 Genomes Project is an international research effort coordinated by a consortium of 75 companies and organizations to establish the most detailed catalogue of human genetic variation. The project has grown to 200 terabytes of genomic data including DNA sequenced from more than 1,700 individuals that researchers can now access on AWS for use in disease research free of charge. The dataset containing the full genomic sequence of 1,700 individuals is now available to all via Amazon S3. The data can be found at: http://s3.amazonaws.com/1000genomes The 1000 Genomes Project aims to include the genomes of more than 2,662 individuals from 26 populations around the world, and the NIH will continue to add the remaining genome samples to the data collection this year. Public Data Sets on AWS provide a centralized repository of public data hosted on Amazon Simple Storage Service (Amazon S3). The data can be seamlessly accessed from AWS services such Amazon Elastic Compute Cloud (Amazon EC2) and Amazon Elastic MapReduce (Amazon EMR), which provide organizations with the highly scalable compute resources needed to take advantage of these large data collections. AWS is storing the public data sets at no charge to the community. Researchers pay only for the additional AWS resources they need for further processing or analysis of the data. All 200 TB of the latest 1000 Genomes Project data is available in a publicly available Amazon S3 bucket. You can access the data via simple HTTP requests, or take advantage of the AWS SDKs in languages such as Ruby, Java, Python, .NET and PHP. Researchers can use the Amazon EC2 utility computing service to dive into this data without the usual capital investment required to work with data at this scale. AWS also provides a number of orchestration and automation services to help teams make their research available to others to remix and reuse. Making the data available via a bucket in Amazon S3 also means that customers can crunch the information using Hadoop via Amazon Elastic MapReduce, and take advantage of the growing collection of tools for running bioinformatics job flows, such as CloudBurst and Crossbow.

Proper citation: 1000 Genomes Project and AWS (RRID:SCR_008801) Copy   

•   Source: SciCrunch Registry

https://confluence.crbs.ucsd.edu/display/NIF/StemCellInfo

Data tables providing an overview of information about stem cells that have been derived from mice and humans. The tables summarize published research that characterizes cells that are capable of developing into cells of multiple germ layers (i.e., multipotent or pluripotent) or that can generate the differentiated cell types of another tissue (i.e., plasticity) such as a bone marrow cell becoming a neuronal cell. The tables do not include information about cells considered progenitor or precursor cells or those that can proliferate without the demonstrated ability to generate cell types of other tissues. The tables list the tissue from which the cells were derived, the types of cells that developed, the conditions under which differentiation occurred, the methods by which the cells were characterized, and the primary references for the information.

Proper citation: National Institutes of Health Stem Cell Tables (RRID:SCR_008359) Copy   

•   Source: SciCrunch Registry

http://harvard.eagle-i.net/i/0000012a-2518-fb6c-5617-794280000000

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on October 27, 2023. Core provides services: RT PCR service, Gene expression profiling service, Proteomics analysis service, Bioinformatics and Systems Biology analyses, Next Generation Sequencing Service, Affymetrix Human and Mouse Gene 2.0 ST Arrays and 2.1 ST Arrayplates. Core proteomics facility for the Dana-Farber/Harvard Cancer Center. Workflows and algorithms for analysis of next-generation sequencing data including RNA-Seq, ChIP-Seq, Epigenetics-Seq and DNA seq, Comprehensive workflow for analysis of Microbiome sequencing data, Integrated systems biology analysis of transcriptome, miRNA, epigenome, metabolomics and proteomics data. Pipelines: MALDI Tissue imaging and targeted quantitative proteomics.

Proper citation: Beth Israel Deaconess Medical Center Genomics Proteomics Bioinformatics and Systems Biology Center (RRID:SCR_009668) Copy   

•   Source: SciCrunch Registry

http://www.tmslab.org/tmscore.php

At the Berenson-Allen Center for Noninvasive Brain Stimulation (CNBS) at Beth Israel Deaconess Medical Center and Harvard Medical School we have three distinct missions: Research, Education and Patient Care. Our research explores brain-behavior relations, brain plasticity and its modulation, employing different noninvasive brain stimulation techniques combined with careful task design, electroencephalography, and functional brain imaging. Educational efforts feature several Continuing Medical Education Courses including a week long intensive course in noninvasive brain stimulation offered 3 times per year. Our clinical program offers noninvasive brain stimulation for treatment of neuropsychiatric disorders such as depression and schizophrenia, epilepsy, and chronic pain. Clinical work also includes studies of central motor conduction time, cortical excitability, and noninvasive cortical mapping.

Proper citation: BIDMC Transcranial Magnetic Stimulation Core (RRID:SCR_011022) Copy   

•   Source: SciCrunch Registry

https://www.umassmed.edu/shrna/

Facility houses complete collections of human and mouse lentiviral short hairpin RNA (shRNA) libraries from Open Biosystems/GE Dharmacon, Mammalian Gene Collection (MGC) cDNA Library, and human and mouse CRISPR/Cas9 GeCKO v2 libraries from Addgene.

Proper citation: Massachusetts University Medical School RNAi Core Facility (RRID:SCR_017727) Copy   

•   Source: SciCrunch Registry

https://sdrc.stanford.edu/sdrc-research-cores/dimc/home/

Core facility that provides immune monitoring assays at the RNA, protein, and cellular level, as well as archiving, reporting, and data mining support for clinical and translational studies related to Diabetes. The DIMC is a specialized subcore of the Human Immune Monitoring Center (HIMC) at Stanford.

Proper citation: Stanford Diabetes Research Center Diabetes Immune Monitoring Core (RRID:SCR_016210) Copy   

•   Source: SciCrunch Registry

http://www.lgfus.ca

Provides system for Splicing isoform Annotation. This LISA platform allows high throughput annotation and functional analysis of Alternate Splicing in humans.

Proper citation: Quebeck Sherbrooke University Genomic Core Facility (RRID:SCR_017785) Copy   

•   Source: SciCrunch Registry

https://ipsc.bsd.uchicago.edu/

Core provides training to use latest episomal techniques to reprogram, expand and characterize human and mice iPS cells from skin or blood tissues of healthy subjects and diseased patients. Develops capability to differentiate iPS cells into specific somatic cells, such as neutrons, cardiomyocytes, and hepatocytes.

Proper citation: Chicago University iPSC Core Facility (RRID:SCR_017918) Copy   

•   Source: SciCrunch Registry