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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.
Open source Java based image processing software program designed for scientific multidimensional images. ImageJ has been transformed to ImageJ2 application to improve data engine to be sufficient to analyze modern datasets.
Proper citation: ImageJ (RRID:SCR_003070) Copy
Open-source software package for the analysis of neural data. Chronux routines may be employed in the analysis of both point process and continuous data, ranging from preprocessing, exploratory and confirmatory analysis. The current release is implemented as a MATLAB library. Chronux offers several routines for computing spectra and coherences for both point and continuous processes. In addition, it also offers several general purpose routines that were found useful such as a routine for extracting specified segments from data, or binning spike time data with bins of a specified size. Since the data can be continuous valued, point process times, or point processes that are binned, methods that apply to all these data types are given in routines whose names end with ''''c'''' for continuous, ''''pb'''' for binned point processes, and ''''pt'''' for point process times. Thus, mtspectrumc computes the spectrum of continuous data, mtspectrumpb computes a spectrum for binned point processes, and mtspectrumpt compute spectra for data consisting of point process times. Hybrid routines are also available and similarly named - for instance coherencycpb computes the coherency between continuous and binned point process data.
Proper citation: Chronux (RRID:SCR_005547) Copy
http://www.nimh.nih.gov/labs-at-nimh/research-areas/research-support-services/hbcc/index.shtml
A collection of brain tissue from individuals suffering from schizophrenia, bipolar disorder, depression, anxiety disorders, and substance abuse, as well as healthy individuals. The research mission of the NIMH Brain Bank is to better understand the underlying biological mechanisms and pathways that contribute to schizophrenia and other neuropsychiatric disorders, as well as to study normal human brain development.
Proper citation: NIMH Brain Tissue Collection (RRID:SCR_008726) Copy
http://web.stanford.edu/group/barres_lab/brain_rnaseq.html
Database containing RNA-Seq transcriptome and splicing data from glia, neurons, and vascular cells of cerebral cortex. Collection of RNA-Seq transcriptome and splicing data from glia, neurons, and vascular cells of mouse cerebral cortex. RNA-Seq of cell types isolated from mouse and human brain.
Proper citation: Brain RNA-Seq (RRID:SCR_013736) Copy
Database for hosting and sharing neuroimaging and neuroanatomical datasets for human and primate species. Includes 1) curated, user created Study datasets, extensively analyzed neuroimaging data associated with published figures/manuscripts, 2) Reference datasets mapped to brain atlas surfaces and volumes in human and nonhuman primates for use as general resources (e.g., published cortical parcellations), and 3) ConnectomeDB powered by BALSA for distributing HCP-Young Adult and related HCP-style processed imaging and phenotypic datasets. Datasets in BALSA may include PMID and/or DOI that links them directly to relevant publications.
Proper citation: BALSA (RRID:SCR_022960) Copy
http://pklab.med.harvard.edu/scde/pagoda.links.html
Software tool for analyzing transcriptional heterogeneity to detect statistically significant ways in which measured cells can be classified. Used to resolve multiple, potentially overlapping aspects of transcriptional heterogeneity by testing gene sets for coordinated variability among measured cells.
Proper citation: PAGODA (RRID:SCR_017099) Copy
https://github.com/FeeLab/seqNMF
Software tool for unsupervised discovery of sequential structure. Used to detect sequences in neural data generated by internal behaviors, such as animal thinking or sleeping. Used for unsupervised discovery of temporal sequences in high dimensional datasets in neuroscience without reference to external markers.
Proper citation: seqNMF (RRID:SCR_017068) Copy
https://github.com/epurdom/clusterExperiment
Software open source R package for executing, evaluating and visualizing different clusterings of experimental data, including data from single cell RNA-Seq studies. Software for running and comparing different clusterings of single cell sequencing data.
Proper citation: clusterExperiment (RRID:SCR_017439) Copy
http://neuroproteomics.scs.illinois.edu/microMS.htm
Software Python platform for image guided Mass Spectrometry profiling. Provides graphical user interface for automatic cell finding and point based registration from whole slide images. Simplifies single cell analysis with feature rich image processing.
Proper citation: microMS (RRID:SCR_017443) Copy
https://www.ncbi.nlm.nih.gov/pubmed/28653482
Software tool to facilitate tractography based deep brain stimulation (DBS) electrode targeting within patient specific stereotactic coordinate system used in operating room.
Proper citation: StimVision (RRID:SCR_017457) Copy
https://github.com/YosefLab/FastProject
Software Python tool for low dimensional analysis of single-cell RNA-Seq data. Software package for two dimensional visualization of single cell data. Analyzes gene expression matrix and produces output report in which two-dimensional of data can be explored.
Proper citation: FastProject (RRID:SCR_017462) Copy
Software Java tool for quantitative analysis of behavior. Used to address any theoretical problem that requires complex sequence of actions to be scored by human observer. Runs on microcomputer providing Java Virtual Machine[TM] and has been tested on Windows[TM] and Macintosh[TM] systems. Legacy version (version 0.9) works on older systems (Macintosh OS-9 and Windows-98), while Version 1.0 works well on Macintosh OS-X and Windows XP systems. JWatcher Video works best on Windows XP systems and has reduced functionality running in Macintosh OS-X. JWatcher-Palm can be used to acquire data on Palm OS[TM] equipped device and analyze it on your main computer.
Proper citation: JWatcher (RRID:SCR_017595) Copy
https://brain-specimenportal.org/
Web application that tracks the status of the BICAN consortium tissue samples and related data.NIMP is developed under NIH BRAIN Initiative's BICAN U24MH130988 award as a part of the coordinating unit for biostatistics, informatics, and engagement (CUBIE) for the BRAIN Initiative Cell Atlas Network (BICAN) program.NIMP consists of two portals for BICAN collaborative data generation: the Specimen Portal and the Sequence Library (SeqLib) Portal. The Specimen Portal focuses on tissue management from donors to brain slabs and annotated brain samples. The SeqLib Portal manages the workflow starting from tissue, all the way downstream to track data deposition to assay-dependent, data-modality-specific archives. Both portals work in tandem to generate multimodal genomic data that can be traced back to their anatomical origins using the Allen Brain Atlas. The portals provide multiple types of data interfaces through dashboards, APIs, faceted queries, and batch data ingestion and exporting. All of the underlying functionalities are achieved through a robust agile development strategy using NHash resource identifiers, metadata standardization, active combinatorial dashboarding, resource provenance linkage and rendering (e.g. Sankey diagrams), and dedicated interfaces with NIH Neuro Biobank, sequencing centers, NeMO, and the larger BICAN data ecosystem.
Proper citation: NIMP: Neuroanatomy-anchored Information Management Platform for Collaborative BICAN Data Generation (RRID:SCR_024684) Copy
THIS RESOURCE IS NO LONGER IN SERVICE. Documented on July 7th, 2019. BAMS is an online resource for information about neural circuitry. The BAMS Nested Regions view focuses on the major brain regions and their relationships.
Proper citation: BAMS Nested Regions (RRID:SCR_000238) Copy
http://gbrowse.csbio.unc.edu/cgi-bin/gb2/gbrowse/slep/
THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 23,2022. Database of genetic and gene expression data from the published literature on psychiatric disorders. Users can search the accumulated data to find the evidence in support of the involvement of a particular genomic region with a set of important psychiatric disorders, ADHD, autism, bipolar disorder, eating disorder, major depressive disorder, schizophrenia, and smoking behavior. It contains findings from manual reviews of 144 papers in psychiatric genetics, 136 primary reports and 8 meta-analyses. Disorders covered include schizophrenia (44 papers), autism (24 papers), bipolar disorder (24 papers), smoking behavior (24 papers), major depressive disorder and neuroticism (14 papers), ADHD (8 papers), eating disorders (3 papers), and a combined schizophrenia-bipolar phenotype (3 papers). The unbiased searches integrated into SLEP include genomewide linkage (117 papers), genomewide association (15 papers), copy number variation (9 papers), and gene expression studies of post-mortem brain tissue (3 meta-analyses courtesy of the Stanley Foundation). In total, SLEP captures 3,741 findings from these 144 papers. SLEP also contains over 70,000 SignPosts. These annotations derive from many different sources and are designed to try to capture current state of knowledge about disease associations in the human genome. SignPosts can be searched simultaneously with the psychiatric genetics literature in order to integrate these two bodies of knowledge. The SignPosts include: accumulated GWAS findings from the human genetics literature, the OMIM database, candidate gene association study literature, CNV location and frequency data, SNPs that influence gene expression in brain, genes expressed in brain, genes with evidence of imprinting and random monoalleleic expression, genes mutated in breast or colorectal cancer, and pathway data from BioCyc.
Proper citation: Sullivan Lab Evidence Project (RRID:SCR_000753) Copy
A database of neuroscience-related concepts that utilizes visualization tools for the purpose of research, education and knowledge discovery. The data comes from PubMed abstracts and an algorithm that assumes related terms will appear together. The topics can include computational modeling, behavioral functions and neurological degeneration.
Proper citation: brainSCANr (RRID:SCR_000500) Copy
A database of digital reconstructions of the human brain arterial arborizations from 61 healthy adult subjects along with extracted morphological measurements. The arterial arborizations include the six major trees stemming from the circle of Willis, namely: the left and right Anterior Cerebral Arteries (ACAs), Middle Cerebral Arteries (MCAs), and Posterior Cerebral Arteries (PCAs).
Proper citation: BraVa (RRID:SCR_001407) Copy
http://mus.well.ox.ac.uk/gscandb/
THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 23,2022. Database / display tool of genome scans, with a web interface that lets the user view the data. It does not perform any analyses - these must be done by other software, and the results uploaded into it. The basic features of GSCANDB are: * Parallel viewing of scans for multiple phenotypes. * Parallel analyses of the same scan data. * Genome-wide views of genome scans * Chromosomal region views, with zooming * Gene and SNP Annotation is shown at high zoom levels * Haplotype block structure viewing * The positions of known Trait Loci can be overlayed and queried. * Links to Ensembl, MGI, NCBI, UCSC and other genome data browsers. In GSCANDB, a genome scan has a wide definition, including not only the usual statistical genetic measures of association between genetic variation at a series of loci and variation in a phenotype, but any quantitative measure that varies along the genome. This includes for example competitive genome hybridization data and some kinds of gene expression measurements.
Proper citation: WTCHG Genome Scan Viewer (RRID:SCR_001635) Copy
Database that collects and provides all known physical microbial interactions. Currently, 24,295 experimentally determined interactions among proteins of 250 bacterial species/strains can be browsed and downloaded. These microbial interactions have been manually curated from the literature or imported from other databases (IntAct, DIP, BIND, MINT) and are linked to 26,578 experimental evidences (PubMed ID, PSI-MI methods). In contrast to these databases, interactions in MPIDB are further supported by 68,346 additional evidences based on interaction conservation, co-purification, and 3D domain contacts (iPfam, 3did). (spoke/matrix) binary interactions inferred from pull-down experiments are not included.
Proper citation: MPIDB (RRID:SCR_001898) Copy
THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 6, 2023.BAMS is an online resource for information about neural circuitry. The BAMS Cell view focuses on the major brain regions and which cells are contained therein.
Proper citation: BAMS Cells (RRID:SCR_003531) Copy
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