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SciCrunch Registry is a curated repository of scientific resources, with a focus on biomedical resources, including tools, databases, and core facilities - visit SciCrunch to register your resource.
http://brainandsociety.org/the-brain-observatory
Formerly a topical portal studying the brain which collected and imaged 1000 human brains, the Brain Observatory has partnered with the Institute for Brain and Society to build virtual laboratories that will feed directly into the database of images and knowledge created in the context of the Human Brain Library. The Brain Observatory will also host exhibits, conferences, and events aimed at promoting a heightened awareness of brain research and how its results can benefit personal brain fitness and mental health.
Proper citation: Brain Observatory (RRID:SCR_010641) Copy
http://fcon_1000.projects.nitrc.org/indi/pro/nyu.html
Datasets including a collection of scans from 49 psychiatrically evaluated neurotypical adults, ranging in age from 6 to 55 years old, with age, gender and intelligence quotient (IQ) information provided. Future releases will include more comprehensive phenotypic information, and child and adolescent datasets, as well as individuals from clinical populations. The following data are released for every participant: * At least one 6-minute resting state fMRI scan (R-fMRI) * * One high-resolution T1-weighted mprage, defaced to protect patient confidentiality * Two 64-direction diffusion tensor imaging scans * Demographic information (age, gender) and IQ-measures (Verbal, Performance, and Composite; Weschler Abbreviated Scale of Intelligence - WASI) * Most participants have 2 R-fMRI scans, collected less than 1 hour apart in the same scanning session. Rest_1 is always collected first.
Proper citation: NYU Institute for Pediatric Neuroscience Sample (RRID:SCR_010458) Copy
Web based tool to visualize gene expression and metadata annotation distribution throughout single cell dataset or multiple datasets. Interactive viewer for single cell expression. You can click on and hover over cells to get meta information, search for genes to color on and click clusters to show cluster specific marker genes.
Proper citation: UCSC Cell Browser (RRID:SCR_023293) Copy
https://cloudreg.neurodata.io/
Software automated, terascale, cloud based image analysis pipeline for preprocessing and cross modal, nonlinear registration between volumetric datasets with artifacts. Automatic terabyte scale cross modal brain volume registration.
Proper citation: CloudReg (RRID:SCR_022795) Copy
THIS RESOURCE IS NO LONGER IN SERVICE. Documented on August 16,2023. Conte Center for the Neuroscience of Mental Disorders (CCNMD) at the University of Pittsburgh offers a highly interactive scientific environment for the study of the neurobiology of schizophrenia. Integrates the laboratory and clinical research activities of investigators from the University of Pittsburgh Schools of Medicine and Arts and Sciences and the adjacent Carnegie Mellon University.
Proper citation: University of Pittsburgh Conte Center for the Neuroscience of Mental Disorders (RRID:SCR_000014) Copy
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
A listing of data sets from NIMH-supported clinical trials. Limited Access Datasets are available from numerous NIMH studies. NIMH requires all investigators seeking access to data from NIMH-supported trials held by NIMH to execute and submit as their request the appropriate Data Use Certification pertaining to the trial. The datasets distributed by NIMH are referred to as limited access datasets because access is limited to qualified researchers who complete Data Use Certifications.
Proper citation: Limited Access Datasets From NIMH Clinical Trials (RRID:SCR_005614) Copy
http://mialab.mrn.org/data/index.html
An MRI data set that demonstrates the utility of a mega-analytic approach by identifying the effects of age and gender on the resting-state networks (RSNs) of 603 healthy adolescents and adults (mean age: 23.4 years, range: 12-71 years). Data were collected on the same scanner, preprocessed using an automated analysis pipeline based in SPM, and studied using group independent component analysis. RSNs were identified and evaluated in terms of three primary outcome measures: time course spectral power, spatial map intensity, and functional network connectivity. Results revealed robust effects of age on all three outcome measures, largely indicating decreases in network coherence and connectivity with increasing age. Gender effects were of smaller magnitude but suggested stronger intra-network connectivity in females and more inter-network connectivity in males, particularly with regard to sensorimotor networks. These findings, along with the analysis approach and statistical framework described, provide a useful baseline for future investigations of brain networks in health and disease.
Proper citation: MIALAB - Resting State Data (RRID:SCR_008914) Copy
Data repository specifically focused on storage and dissemination of omic data generated from BRAIN Initiative and related brain research projects. Data repository and archive for BCDC and BICCN project, among others. NeMO data include genomic regions associated with brain abnormalities and disease, transcription factor binding sites and other regulatory elements, transcription activity, levels of cytosine modification, histone modification profiles and chromatin accessibility.
Proper citation: NeMOarchive (RRID:SCR_016152) Copy
http://www.nitrc.org/projects/psc/
Data analysis software that can simultaneously characterize a large number of white matter bundles within and across different subjects for group analysis. It has three major components: construction of the structural connectome for the whole brain, low-dimensional representation of streamlines in each connection, and multi-level connectome analysis.
Proper citation: Mapping Population-based Structural Connectomes (RRID:SCR_016232) Copy
https://github.com/SciCrunch/NIF-Ontology/tree/neurons/ttl
An ontology for describing the complex phenotypes of neurons.
Proper citation: Neuron Phenotype Ontology (RRID:SCR_017403) Copy
Portal for visualization and analysis of multi omic data in public and private domains. Enables upload, visualization and analysis of scRNA-seq data.
Proper citation: gene Expression Analysis Resource (RRID:SCR_017467) Copy
https://github.com/PriceLab/TReNA
Methods for reconstructing transcriptional regulatory networks.
Proper citation: TReNA (RRID:SCR_017458) Copy
http://www.brainimagelibrary.org
Public, NIH-funded repository and analysis ecosystem for brain microscopy data, designed to store, share, and process massive volumetric datasets. It enables researchers to access whole-brain images, neuron morphologies, and spatial data without needing to download, fostering collaborative discovery. Used to deposit, analyze, mine, share and interact with large brain image datasets.
Proper citation: Brain Image Library (RRID:SCR_017272) Copy
BossDB (Brain Observatory Storage Service and Database) is a cloud-based ecosystem for the storage and management of public large-scale volumetric neuroimaging and connectomics datasets. This includes volumetric Electron Microscopy and X-Ray Micro/Nanotomography data with support for multi-channel image data, segmentations, annotations, meshes, and connectomes. BossDB integrates with community resources for data access, processing, visualization, and analysis, and includes an API that enables metadata management, rendering, datatype conversions, and ingest.
Proper citation: Brain Observatory Storage Service and Database (BossDB) (RRID:SCR_017273) Copy
http://compbio.mit.edu/ChromHMM/
Software tool for chromatin state discovery and characterization. Used for chromatin state discovery and genome annotation of non coding genome using epigenomic information across one or multiple cell types. Combines multiple genome wide epigenomic maps, and uses combinatorial and spatial mark patterns to infer complete annotation for each cell type. Provides automated enrichment analysis of resulting annotations.
Proper citation: ChromHMM (RRID:SCR_018141) Copy
https://health.uconn.edu/worm-lab/track-a-worm/
Open source system for quantitative assessment of C. Elegans locomotory and bending behavior. Used for quantitative behavioral analyses to understand circuit and gene bases of behavior. Constantly records and analyzes position and body shape of freely moving worm at high magnification.
Proper citation: Track-A-Worm (RRID:SCR_018299) Copy
Software R package for mathematical modeling of infectious disease over networks. Provides tools for simulating and analyzing mathematical models of infectious disease dynamics. Mathematical Modeling of Infectious Disease Dynamics.
Proper citation: EpiModel (RRID:SCR_018539) Copy
Web platform for downstream analysis and visualization of proteomics data. Server that facilitates integrated annotation, analysis and visualization of quantitative proteomics data, with emphasis on PTM networks and integration with LINCS library of chemical and genetic perturbation signatures in order to provide further mechanistic and functional insights. Primary input for server consists of set of peptides or proteins, optionally with PTM sites, and their corresponding abundance values.
Proper citation: piNET (RRID:SCR_018693) Copy
https://github.com/aplbrain/saber
Library of containerized tools and workflow deployment system for enabling processing of large neuroimaging datasets. Provides canonical neuroimaging workflows specified in standard workflow language (CWL), integration with workflow execution engine (Airflow), imaging database (bossDB), and parameter database (Datajoint) to deploy workflows at scale, and tools to automate deployment and optimization of neuroimaging pipelines.
Proper citation: Scalable Analytics for Brain Exploration Research (RRID:SCR_018812) Copy
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