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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.

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  • RRID:SCR_022208

    This resource has 1+ mentions.

https://github.com/OSS-Lab/ChemChaste

Software tool for simulating spatially inhomogenous biochemical reaction diffusion systems for modelling cell environment feedbacks. Simulation software for spatially organised biochemical systems.

Proper citation: ChemChaste (RRID:SCR_022208) Copy   


  • RRID:SCR_022207

    This resource has 1+ mentions.

https://github.com/rajewsky-lab/spacemake

Software pipeline for processing and analysis of large scale spatial transcriptomics data. Enables reproducible data processing from raw sequencing data to automatically generated downstream analysis reports.

Proper citation: Spacemake (RRID:SCR_022207) Copy   


  • RRID:SCR_001704

http://www.nitrc.org/projects/vutools/

VUIIS (Vanderbilt University Institute of Imaging Science) Image and Data Analysis Core's data processing tools written for MATLAB and, unless stated otherwise, capable of processing 2D/3D images (matrices). These tools are written for ease of use from within MATLAB.

Proper citation: vuTools (RRID:SCR_001704) Copy   


  • RRID:SCR_000058

http://dissect-trans.sourceforge.net/Home

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on July 31,2025. Software transcriptome-to-genome alignment tool, which can identify and characterize transcriptomic events such as duplications, inversions, rearrangements and fusions.

Proper citation: Dissect (RRID:SCR_000058) Copy   


  • RRID:SCR_001937

    This resource has 100+ mentions.

http://burgundy.cmmt.ubc.ca/cgi-bin/RAVEN/a?rm=home

Tool to search for putative regulatory genetic variation in your favorite gene. Single nucleotide polymorphisms (SNPs) (from dbSNP and user defined) are analyzed for overlap with potential transcription factor binding sites (TFBS) and phylogenetic footprinting using UCSC phastCons scores from multiple alignments of 8 vertebrate genomes., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: RAVEN (RRID:SCR_001937) Copy   


  • RRID:SCR_001775

    This resource has 1000+ mentions.

http://www.mbfbioscience.com/neurolucida

Neurolucida is advanced scientific software for brain mapping, neuron reconstruction, anatomical mapping, and morphometry. Since its debut more than 20 years ago, Neurolucida has continued to evolve and has become the worldwide gold-standard for neuron reconstruction and 3D mapping. Neurolucida has the flexibility to handle data in many formats: using live images from digital or video cameras; stored image sets from confocal microscopes, electron microscopes, and scanning tomographic sources, or through the microscope oculars using the patented LucividTM. Neurolucida controls a motorized XYZ stage for integrated navigation through tissue sections, allowing for sophisticated analysis from many fields-of-view. Neurolucidas Serial Section Manager integrates unlimited sections into a single data file, maintaining each section in aligned 3D space for full quantitative analysis. Neurolucidas neuron tracing capabilities include 3D measurement and reconstruction of branching processes. Neurolucida also features sophisticated tools for mapping delineate and map anatomical regions for detailed morphometric analyses. Neurolucida uses advanced computer-controlled microscopy techniques to obtain accurate results and speed your work. Plug-in modules are available for confocal and MRI analysis, 3D solid modeling, and virtual slide creation. The user-friendly interface gives you rapid results, allowing you to acquire data and capture the full 3D extent of neurons and brain regions. You can reconstruct neurons or create 3D serial reconstructions directly from slides or acquired images, and Neurolucida offers full microscope control for brightfield, fluorescent, and confocal microscopes. Its added compatibility with 64-bit Microsoft Vista enables reconstructions with even larger images, image stacks, and virtual slides. Adding the Solid Modeling Module allows you to rotate and view your reconstructions in real time. Neurolucida is available in two separate versions Standard and Workstation. The Standard version enables control of microscope hardware, whereas the Workstation version is used for offline analysis away from the microscope. Neurolucida provides quantitative analysis with results presented in graphical or spreadsheet format exportable to Microsoft Excel. Overall, features include: - Tracing Neurons - Anatomical Mapping - Image Processing and Analysis Features - Editing - Morphometric Analysis - Hardware Integration - Cell Analysis - Visualization Features Sponsors: Neurolucida is supported by MBF Bioscience.

Proper citation: Neurolucida (RRID:SCR_001775) Copy   


http://pennadc.org

A national Alzhiemer's disease research center funded by the National Institute on Aging, and the research arm of the Penn Memory Center.

Proper citation: Penn Alzheimer's Disease Center (RRID:SCR_004444) Copy   


https://www.ncbi.nlm.nih.gov/geo/

Functional genomics data repository supporting MIAME-compliant data submissions. Includes microarray-based experiments measuring the abundance of mRNA, genomic DNA, and protein molecules, as well as non-array-based technologies such as serial analysis of gene expression (SAGE) and mass spectrometry proteomic technology. Array- and sequence-based data are accepted. Collection of curated gene expression DataSets, as well as original Series and Platform records. The database can be searched using keywords, organism, DataSet type and authors. DataSet records contain additional resources including cluster tools and differential expression queries.

Proper citation: Gene Expression Omnibus (GEO) (RRID:SCR_005012) Copy   


  • RRID:SCR_002420

http://cobre.mrn.org/megsim/

Realistic simulated MEG datasets ranging from basic sensory to oscillatory sets that mimic functional connectivity; as well as basic visual, auditory, and somatosensory empirical sets. The simulated sets were created for the purpose of testing analysis algorithms across the different MEG systems when the truth is known. MEG baseline recordings were obtained from 5 healthy participants, using three MEG systems: VSM/CTF Omega, Elekta Neuromag Vectorview, 4-D Magnes 3600. Simulated signals were embedded within the CTF and Neuromag 306 baseline recordings (4-D to be added). Participant MRIs are available. Averaged simulation files are available as netcdf files. Neuromag 306 averaged simulations are also available in fif format. Also available: single trials of data where the simulated signal is jittered about a mean value, continuous fif files where the simulated signal is marked by a trigger, and simulations with oscillations added to mimic functional connectivity.

Proper citation: MEGSIM (RRID:SCR_002420) Copy   


  • RRID:SCR_005096

    This resource has 500+ mentions.

http://soybase.org

Professionally curated repository for genetics, genomics and related data resources for soybean that contains the most current genetic, physical and genomic sequence maps integrated with qualitative and quantitative traits. SoyBase includes annotated Williams 82 genomic sequence and associated data mining tools. The genetic and sequence views of the soybean chromosomes and the extensive data on traits and phenotypes are extensively interlinked. This allows entry to the database using almost any kind of available information, such as genetic map symbols, soybean gene names or phenotypic traits. The repository maintains controlled vocabularies for soybean growth, development, and traits that are linked to more general plant ontologies. Contributions to SoyBase or the Breeder''s Toolbox are welcome.

Proper citation: SoyBase (RRID:SCR_005096) Copy   


  • RRID:SCR_005091

    This resource has 50+ mentions.

http://snpeffect.vib.be/

A database for phenotyping human single nucleotide polymorphisms (SNPs)that primarily focuses on the molecular characterization and annotation of disease and polymorphism variants in the human proteome. They provide a detailed variant analysis using their tools such as: * TANGO to predict aggregation prone regions * WALTZ to predict amylogenic regions * LIMBO to predict hsp70 chaperone binding sites * FoldX to analyse the effect on structure stability Further, SNPeffect holds per-variant annotations on functional sites, structural features and post-translational modification. The meta-analysis tool enables scientists to carry out a large scale mining of SNPeffect data and visualize the results in a graph. It is now possible to submit custom single protein variants for a detailed phenotypic analysis., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: SNPeffect (RRID:SCR_005091) Copy   


  • RRID:SCR_002416

    This resource has 10+ mentions.

http://www.udel.edu/Biology/Wags/histopage/colorpage/cne/cne.htm

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 13,2026. An image collection of tissue from the central nervous system and peripheral nervous system.

Proper citation: Nervous Tissue Color Images (RRID:SCR_002416) Copy   


  • RRID:SCR_005407

    This resource has 1+ mentions.

http://jilab.biostat.jhsph.edu/database/cgi-bin/hmChIP.pl

A database of genome-wide chromatin immunoprecipitation (ChIP) data in human and mouse. Currently, the database contains >2000 samples from >500 ChIP-seq and ChIP-chip experiments, representing a total of >170 proteins and >10,000,000 protein-DNA interactions (March 2014). A web server provides an interface for database query. Protein-DNA binding intensities can be retrieved from individual samples for user-provided genomic regions. The retrieved intensities can be used to cluster samples and genomic regions to facilitate exploration of combinatorial patterns, cell type dependencies, and cross-sample variability of protein-DNA interactions.

Proper citation: hmChIP (RRID:SCR_005407) Copy   


http://pharmacology.mc.duke.edu/

Department of Pharmacology and Cancer Biology spans two overlapping and broad disciplines, one exploring how chemical agents impact living cells and one seeking to understand how inappropriate responses to environmental molecules and internal cellular cues can lead to development of Cancer. Occupying Levine Science Research Center, Pharmacology and Cancer Biology department is dedicated to mentoring and training of graduate students and postdoctoral fellows.Innovative undergraduate program also allows students majoring in Biology or Chemistry at Duke to complete area specialization in Pharmacology, as well as offering courses in Pharmacology and Neuropharmacology for undergraduates. Department trains also students working towards Ph.D.s in Molecular Cancer Biology. Moreover, students enter our department through several university-wide multi-disciplinary programs including the Toxicology, Cell and Molecular Biology Program and the University Program in Genetics and Genomics. Our 23 faculty members are remarkably diverse and use all of the tools available to biomedical scientists to address questions critical to fundamental biology and human health. The faculty members share the common goal of exploiting cellular signaling pathways to address a myriad of important scientific questions relevant to cancer, metabolism, nervous system function, drugs of abuse and environmental toxicants.

Proper citation: Duke University, Pharmacology and Cancer Biology (RRID:SCR_003342) Copy   


  • RRID:SCR_004830

    This resource has 50+ mentions.

http://humanconnectome.org/connectome/connectomeDB.html

Data management platform that houses all data generated by the Human Connectome Project - image data, clinical evaluations, behavioral data and more. ConnectomeDB stores raw image data, as well as results of analysis and processing pipelines. Using the ConnectomeDB infrastructure, research centers will be also able to manage Connectome-like projects, including data upload and entry, quality control, processing pipelines, and data distribution. ConnectomeDB is designed to be a data-mining tool, that allows users to generate and test hypotheses based on groups of subjects. Using the ConnectomeDB interface, users can easily search, browse and filter large amounts of subject data, and download necessary files for many kinds of analysis. ConnectomeDB is designed to work seamlessly with Connectome Workbench, an interactive, multidimensional visualization platform designed specifically for handling connectivity data. De-identified data within ConnectomeDB is publicly accessible. Access to additional data may be available to qualified research investigators. ConnectomeDB is being hosted on a BlueArc storage platform housed at Washington University through the year 2020. This data platform is based on XNAT, an open-source image informatics software toolkit developed by the NRG at Washington University. ConnectomeDB itself is fully open source.

Proper citation: ConnectomeDB (RRID:SCR_004830) Copy   


  • RRID:SCR_005403

    This resource has 100+ mentions.

http://amp.pharm.mssm.edu/lib/chea.jsp

Data analysis service for gene-list enrichment analysis against a manual database. It allows users to input lists of mammalian gene symbols for which the program computes over-representation of transcription factor targets from the ChIP-X database. The database integrates interaction data from ChIP-chip, ChIP-seq, ChIP-PET and DamID studies and contains 189,933 interactions, manually extracted from 87 publications, describing the binding of 92 transcription factors to 31,932 target genes.

Proper citation: ChEA (RRID:SCR_005403) Copy   


http://www.patricbrc.org/portal/portal/patric/Home

A Bioinformatics Resource Center bacterial bioinformatics database and analysis resource that provides researchers with an online resource that stores and integrates a variety of data types (e.g. genomics, transcriptomics, protein-protein interactions (PPIs), three-dimensional protein structures and sequence typing data) and associated metadata. Datatypes are summarized for individual genomes and across taxonomic levels. All genomes, currently more than 10 000, are consistently annotated using RAST, the Rapid Annotations using Subsystems Technology. Summaries of different data types are also provided for individual genes, where comparisons of different annotations are available, and also include available transcriptomic data. PATRIC provides a variety of ways for researchers to find data of interest and a private workspace where they can store both genomic and gene associations, and their own private data. Both private and public data can be analyzed together using a suite of tools to perform comparative genomic or transcriptomic analysis. PATRIC also includes integrated information related to disease and PPIs. The PATRIC project includes three primary collaborators: the University of Chicago, the University of Manchester, and New City Media. The University of Chicago is providing genome annotations and a PATRIC end-user genome annotation service using their Rapid Annotation using Subsystem Technology (RAST) system. The National Centre for Text Mining (NaCTeM) at the University of Manchester is providing literature-based text mining capability and service. New City Media is providing assistance in website interface development. An FTP server and download tool are available.

Proper citation: Pathosystems Resource Integration Center (RRID:SCR_004154) Copy   


http://neurobureau.projects.nitrc.org/BrainArt/Competition.html

An annual Brain-Art Competition to recognize the beauty and creativity of artistic renderings emerging from the neuroimaging community. Submission deadline: June 1st, 2012. Awards will be announced on June 11th during the OHBM conference in Beijing. (You need not be present to win) Countless hours are devoted to creation of informative visualizations for communicating neuroscientific findings. This competition once again aims to recognize the artistic creativity of our community that often goes underappreciated in the publication process. We are inviting researchers to submit their favorite unpublished works for entry. Both team and single-person entries are welcomed. The competition will have five award categories: # Best Representation of the Human Connectome # Best Abstract Brain Illustration # Best Educational Brain Illustration # Best Humorous Brain Illustration # Best Video Illustration of the Brain Submissions will be evaluated based on their aesthetic merit

Proper citation: Brain-Art Competition (RRID:SCR_005360) Copy   


http://www.med.unc.edu/bric/ideagroup/free-softwares/intergroup-image-registration

Software package that provides solutions for registering two groups of images, which are the necessary steps for many brain-related applications.

Proper citation: Inter-Group Registration Toolbox (RRID:SCR_002404) Copy   


  • RRID:SCR_002523

    This resource has 1+ mentions.

http://arrowsmith.psych.uic.edu/arrowsmith_uic/

Portal for documenting the Arrowsmith project and developing text mining tools for scientific, and specifically neuroscience, literature. It also contains a search functions that identifies similar concepts between two articles.

Proper citation: Arrowsmith (RRID:SCR_002523) Copy   



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