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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://github.com/kstreet13/slingshot

Software R package for identifying and characterizing continuous developmental trajectories in single cell data. Cell lineage and pseudotime inference for single-cell transcriptomics.

Proper citation: Slingshot (RRID:SCR_017012) Copy   

•   Source: SciCrunch Registry

https://openwetware.org/wiki/HughesLab:JTK_Cycle

Software R package for Detecting Rhythmic Components in Genome-Scale Data Sets. Non-parametric algorithm to identify rhythmic components in large datasets. Identifies and characterizes cycling variables in large datasets.

Proper citation: JTK_CYCLE (RRID:SCR_017962) Copy   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

http://www.ccnmd.pitt.edu/

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   

•   Source: SciCrunch Registry

http://proteomics.ucsd.edu/Software/NeuroPedia/index.html

A neuropeptide encyclopedia of peptide sequences (including genomic and taxonomic information) and spectral libraries of identified MS/MS spectra of homolog neuropeptides from multiple species.

Proper citation: NeuroPedia (RRID:SCR_001551) Copy   

•   Source: SciCrunch Registry

http://www.epmba.org/

The Electronic Prenatal Mouse Brain Atlas, EPMBA, at present consists of two sets of annotated images of coronal sections from Gestational Day (GD) 12 heads and GD 16 brains of C57BL/6J mice. Ten micron thick sections were stained with hematoxylin and eosin. Images were prepared at various resolutions for annotations and for high resolution presentation. A subset of sections were annotated and linked to anatomical terms. Additionally, horizontal sections of a GD 12 head were aligned and re-assembled into a 3D volume for digital sectioning in arbitrarily oblique planes. These images were captured using a Nikon E800 stereomicroscope with a 10X objective. The resolution is 1.35 pixels/micrometer. The PC program used to grab the images, Microbrightfield's Neurolucida (version 6), stitched together a mosaic of between 10 and 50 high-res images for each tissue slice, while the user focused the scope for each mosaic tile. Since the nature of optic lenses is to focus on one central point, it was difficult to obtain a uniformly-focused field of vision; as such, small areas of these images are blurred. Images were then transferred to a Macintosh and processed in Adobe Photoshop (version 7). Color levels were adjusted for maximum clarity of the tissue, and areas surrounding the tissue were cleared of artifacts. Each image is approximately 3350 pixels wide by 2650 pixels high. A scale bar with a length of 1350 pixels/mm is visible in the lower right-hand corner of each image. The annotations have been completed for the Atlas of Developing Mouse Brain Gestational (Embryonic) Day 12 (7/5/07) as well as the Atlas of Developing Mouse Brain Embryonic Day 16 (4/26/07). The 3D EPMBA data set has been mounted on a NeuroTerrain Atlas Server (NtAS). (6/27/07).

Proper citation: EPMBA.ORG: Electronic Prenatal Mouse Brain Atlas (RRID:SCR_001882) Copy   

•   Source: SciCrunch Registry

http://hbatlas.org

A data repository containing transcriptome and associated metadata for the developing and adult human brain. It provides genome-wide, exon-level transcriptome data from both sexes and multiple ethnicities.

Proper citation: Human Brain Transcriptome (RRID:SCR_013742) Copy   

•   Source: SciCrunch Registry

http://kimlab.io/brain-map/atlas/

Website to visualize and share anatomical labels. Franklin and Paxinos (FP) based anatomical labels in Allen Common Coordinate Framework (CCF). Cell type specific transgenic mice and MRI atlas were used to adjust and further segment labels. New segmentations were created in dorsal striatum using cortico-striatal connectivity data. Anatomical labels were digitized based on Allen ontology, and web-interface was created for easy visualization. These labels provide resource to isolate and identify mouse brain anatomical structures. Open source data sharing will facilitate further refinement of anatomical labels and integration of data interpretation within single anatomical platform.

Proper citation: Enhanced and Unified Anatomical Labeling for Common Mouse Brain Atlas (RRID:SCR_019267) Copy   

•   Source: SciCrunch Registry

http://kim.bio.upenn.edu/software/pivot.shtml

Software R package for interactive analysis and visualization of transcriptomics data. Operating systems are macOS, Linux, Windows.

Proper citation: PIVOT software (RRID:SCR_017210) Copy   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

https://bossdb.org/

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

https://umgear.org/

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   

•   Source: SciCrunch Registry

https://github.com/PriceLab/TReNA

Methods for reconstructing transcriptional regulatory networks.

Proper citation: TReNA (RRID:SCR_017458) Copy   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

http://HIVBrainSeqDB.org

The HIV Brain Sequence Database (HIVBrainSeqDB) is a public database of HIV envelope sequences, directly sequenced from brain and other tissues from the same patients. For inclusion in the database, sequences must: (i) be deposited in Genbank; (ii) include some portion of the HIV env region; (iii) be clonal, amplified directly from tissue; and (iv) be sampled from the brain, or sampled from a patient for which the database already contains brain sequence. Sequences are annotated with clinical data including viral load, CD4 count, antiretroviral status, neurocognitive impairment, and neuropathological diagnosis, all curated from the original publication. Tissue source is coded using an anatomical ontology, the Foundational Model of Anatomy, to capture the maximum level of detail available, while maintaining ontological relationships between tissues and their subparts. 44 tissue types are represented within the database, grouped into 4 categories: (i) brain, brainstem, and spinal cord; (ii) meninges, choroid plexus, and CSF; (iii) blood and lymphoid; and (iv) other (bone marrow, colon, lung, liver, etc). Currently, the database contains 2517 envelope sequences from 90 patients, obtained from 22 published studies. 1272 sequences are from brain; the remaining 1245 are from blood, lymph node, spleen, bone marrow, colon, lung and other non-brain tissues. The database interface utilizes a faceted interface, allowing real-time combination of multiple search parameters to assemble a meta-dataset, which can be downloaded for further analysis. This online resource will greatly facilitate analysis of the genetic aspects of HIV macrophage tropism, HIV compartmentalization and evolution within the brain and other tissue reservoirs, and the relationship of these findings to HIV-associated neurological disorders and other clinical consequences of HIV infection.

Proper citation: HIV Brain Sequence Database (RRID:SCR_008819) Copy   

•   Source: SciCrunch Registry

http://neuromorphometrics.com/?page_id=23

Collection of neuroanatomically labeled MRI brain scans, created by neuroanatomical experts. Regions of interest include the sub-cortical structures (thalamus, caudate, putamen, hippocampus, etc), along with ventricles, brain stem, cerebellum, and gray and white matter and sub-divided cortex into parcellation units that are defined by gyral and sulcal landmarks.

Proper citation: Manually Labeled MRI Brain Scan Database (RRID:SCR_009604) Copy   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

http://www.nimh.nih.gov/funding/clinical-trials-for-researchers/datasets/nimh-procedures-for-requesting-data-sets.shtml

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   

•   Source: SciCrunch Registry