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http://krasnow1.gmu.edu/cn3/index3.html

Multidisciplinary research team devoted to the study of basic neuroscience with a specific interest in the description and generation of dendritic morphology, and in its effect on neuronal electrophysiology. In the long term, they seek to create large-scale, anatomically plausible neural networks to model entire portions of a mammalian brain (such as a hippocampal slice, or a cortical column). Achievements by the CNG include the development of software for the quantitative analysis of dendritic morphology, the implementation of computational models to simulate neuronal structure, and the synthesis of anatomically accurate, large scale neuronal assemblies in virtual reality. Based on biologically plausible rules and biophysical determinants, they have designed stochastic models that can generate realistic virtual neurons. Quantitative morphological analysis indicates that virtual neurons are statistically compatible with the real data that the model parameters are measured from. Virtual neurons can be generated within an appropriate anatomical context if a system level description of the surrounding tissue is included in the model. In order to simulate anatomically realistic neural networks, axons must be grown as well as dendrites. They have developed a navigation strategy for virtual axons in a voxel substrate.

Proper citation: Computational Neuroanatomy Group (RRID:SCR_007150) Copy   

•   Source: SciCrunch Registry

http://senselab.med.yale.edu/modeldb/

Curated database of published models so that they can be openly accessed, downloaded, and tested to support computational neuroscience. Provides accessible location for storing and efficiently retrieving computational neuroscience models.Coupled with NeuronDB. Models can be coded in any language for any environment. Model code can be viewed before downloading and browsers can be set to auto-launch the models. The model source code has to be available from publicly accessible online repository or WWW site. Original source code is used to generate simulation results from which authors derived their published insights and conclusions.

Proper citation: ModelDB (RRID:SCR_007271) Copy   

•   Source: SciCrunch Registry

http://brainml.org/goto.do?page=.home

Set of standards and practices for using XML to facilitate information exchange between user application software and neuroscience data repositories. It allows for common shared library routines to handle most of the data processing, but also supports use of structures specialized to the needs of particular neuroscience communities. This site also serves as a repository for BrainML models. (A BrainML model is an XML Schema and optional vocabulary files describing a data model for electronic representation of neuroscience data, including data types, formats, and controlled vocabulary. ) It focuses on layered definitions built over a common core in order to support community-driven extension. One such extension is provided by the new NIH-supported neuroinformatics initiative of the Society for Neuroscience, which supports the development of expert-derived terminology sets for several areas of neuroscience. Under a cooperative agreement, these term lists will be made available Open Source on this site.
The repository function of this site includes the following features:
* BrainML models are published in searchable, browsable form.
* Registered users may submit new models or new versions of existing models to accommodate data of interest. * BrainML model schema and vocabulary files are made available at fixed URLs to allow software applications to reference them.
* Users can check models and/or instance documents for correct format before submitting them using an online validation service.
To complement the BrainML modeling language, a set of protocols have been developed for BrainML document exchange between repositories and clients, for indexing of repositories, and for data query.

Proper citation: BrainML (RRID:SCR_007087) Copy   

•   Source: SciCrunch Registry

http://trans.nih.gov/CEHP/

Trans-NIH project to assess the state of longitudinal and epidemiological research on demographic, social and biologic determinants of cognitive and emotional health in aging adults and the pathways by which cognitive and emotional health may reciprocally influence each other. A database of large scale longitudinal study relevant to healthy aging in 4 domains was created based on responses of investigators conducting these studies and is available for query. The four domains are: * Cognitive Health * Emotional Health * Demographic and Social Factors * Biomedical and Physiologic Factors

Proper citation: Cognitive and Emotional Health Project: The Healthy Brain (RRID:SCR_007390) Copy   

•   Source: SciCrunch Registry

http://www.nntc.org/

Collects, stores, and distributes samples of nervous tissue, cerebrospinal fluid, blood, and other tissue from HIV-infected individuals. The NNTC mission is to bolster research on the effects of HIV infection on human brain by providing high-quality, well-characterized tissue samples from patients who died with HIV, and for whom comprehensive neuromedical and neuropsychiatric data were gathered antemortem. Researchers can request tissues from patients who have been characterized by: * degree of neurobehavioral impairment * neurological and other clinical diagnoses * history of drug use * antiretroviral treatments * blood and CSF viral load * neuropathological diagnosis The NNTC encourages external researchers to submit tissue requests for ancillary studies. The Specimen Query Tool is a web-based utility that allows researchers to quickly sort and identify appropriate NNTC specimens to support their research projects. The results generated by the tool reflect the inventory at a previous time. Actual availability at the local repositories may vary as specimens are added or distributed to other investigators.

Proper citation: National NeuroAIDS Tissue Consortium (RRID:SCR_007323) Copy   

•   Source: SciCrunch Registry

http://senselab.med.yale.edu/ordb/

Database of vertebrate olfactory receptors genes and proteins. It supports sequencing and analysis of these receptors by providing a comprehensive archive with search tools for this expanding family. The database also incorporates a broad range of chemosensory genes and proteins, including the taste papilla receptors (TPRs), vomeronasal organ receptors (VNRs), insect olfaction receptors (IORs), Caenorhabditis elegans chemosensory receptors (CeCRs), and fungal pheromone receptors (FPRs). ORDB currently houses chemosensory receptors for more than 50 organisms. ORDB contains public and private sections which provide tools for investigators to analyze the functions of these very large gene families of G protein-coupled receptors. It also provides links to a local cluster of databases of related information in SenseLab, and to other relevant databases worldwide. The database aims to house all of the known olfactory receptor and chemoreceptor sequences in both nucleotide and amino acid form and serves four main purposes: * It is a repository of olfactory receptor sequences. * It provides tools for sequence analysis. * It supports similarity searches (screens) which reduces duplicate work. * It provides links to other types of receptor information, e.g. 3D models. The database is accessible to two classes of users: * General public www users have full access to all the public sequences, models and resources in the database. * Source laboratories are the laboratories that clone olfactory receptors and submit sequences in the private or public database. They can search any sequence they deposited to the database against any private or public sequence in the database. This user level is suited for laboratories that are actively cloning olfactory receptors.

Proper citation: Olfactory Receptor DataBase (RRID:SCR_007830) Copy   

•   Source: SciCrunch Registry

https://www.med.unc.edu/neuroscience/core-facilities/neuro-microscopy/

Microscopy Core for high resolution imaging and aims to make this technology accessible to neuroscientists and other scientific researchers.Provides advanced systems for cellular and molecular imaging of in vitro and in vivo samples, implements new imaging technologies, particularly related to real time and tissue clearing based imaging of neurodevelopment and neural functions, offers training, consultation, data analysis, image processing, and centralized technical expertise.

Proper citation: University of North Carolina at Chapel Hill School of Medicine Neuroscience Microscopy Core Facility (RRID:SCR_019060) Copy   

•   Source: SciCrunch Registry

http://www.salk.edu/science/core-facilities/gene-transfer-targeting-and-therapeutics-core/

Core facility that provides consultation on the use of viral vector technologies as well as custom design and production services for multiple vector types. The GT3 facilitates the use of these research tools by Salk researchers and others across diverse fields of study such as systems neuroscience, stem cell biology, metabolism, ageing, cancer biology and gene therapy. The GT3 core is a designated Cancer Center Council (C3) core facility. Cancer Center members from participating C3 institutes have preferential rates.

Proper citation: Salk Institute Gene Transfer Targeting and Therapeutics Viral Vector Core Facility (RRID:SCR_014847) Copy   

•   Source: SciCrunch Registry

http://www.biac.duke.edu/

BIAC strives for excellence in its dual mission of research and service. BIAC faculty members are leaders in imaging methodology development, in analysis techniques, as well as in their application in cognitive and clinical neurosciences. In addition, BIAC offers imaging service to other imaging faculty members on campus and at the University of North Carolina in Chapel Hill.

Proper citation: Duke University of North Carolina Brain Imaging and Analysis Center Core Facility (RRID:SCR_001712) Copy   

•   Source: SciCrunch Registry

http://nif.nimh.nih.gov/

Neurophysiology imaging core facility that provides anatomical and functional MRI scanning for researchers in the National Institute of Mental Health (NIMH), the National Eye Institute (NEI), and the National Institute for Neurological Disorders and Stroke (NINDS). The shared intramural resource centers on a cutting-edge 4.7T vertical bore scanner dedicated to imaging of nonhuman primates.

Proper citation: Neurophysiology Imaging Facility (RRID:SCR_004080) Copy   

•   Source: SciCrunch Registry

https://github.com/sccn/labstreaminglayer

System for unified collection of measurement time series in research experiments that handles networking, time synchronization, near real time access as well as optionally centralized collection, viewing and disk recording of data. System for synchronizing streaming data for live analysis or recording.

Proper citation: Lab Streaming Layer (RRID:SCR_017631) Copy   

•   Source: SciCrunch Registry

https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/FIRST

Software model based segmentation and registration tool. Used for segmentation of sub-cortical structures. Introduces basic segmentation and vertex analysis for detecting group differences.

Proper citation: FMRIB’s Integrated Registration and Segmentation Tool (RRID:SCR_024921) Copy   

•   Source: SciCrunch Registry

https://github.com/dattalab/keypoint-moseq

Software application as machine learning-based platform for identifying behavioral modules from keypoint data without human supervision. Package provides tools for fitting MoSeq model to keypoint tracking data. Used to infer pose dynamics with keypoint data in addition to behavioral syllables.

Proper citation: Keypoint MoSeq (RRID:SCR_025032) Copy   

•   Source: SciCrunch Registry

https://github.com/Aharoni-Lab/Ephys-Miniscope

Miniaturized calcium imaging microscope with integrated dense electrode technology for synchronous acquisition of neural activity across distant regions of the brain. Device based off open-sourced UCLA Miniscope to synchronously measure single cell activity at or near spike-time resolution across distant brain regions in freely behaving mice. Used to perform calcium imaging, with dense electrode electrophysiological recording, allowing simultaneous recordings from two remote brain regions in freely behaving mouse.

Proper citation: E-Scope (RRID:SCR_025396) Copy   

•   Source: SciCrunch Registry

https://sea-ad.shinyapps.io/ACEapp/

Web application for comparing cell type assignments and other cell-based annotations (e.g., donor demographics, anatomic locations, batch variables, and quality control metrics). Used for connecting brain cell types across studies of health and Alzheimer's Disease.

Proper citation: Annotation Comparison Explorer (RRID:SCR_026496) Copy   

•   Source: SciCrunch Registry

https://github.com/calico/borzoi

Software package to access the Borzoi models, which are convolutional neural networks trained to predict RNA-seq coverage at 32bp resolution given 524kb input sequences.

Proper citation: Borzoi (RRID:SCR_026619) Copy   

•   Source: SciCrunch Registry

https://github.com/TonnesenLab/Diffusion-Model/

Software code for simulating diffusion in brain extracellular space images.

Proper citation: Diffusion-Model (RRID:SCR_027942) Copy   

•   Source: SciCrunch Registry

https://github.com/NeurodataWithoutBorders/aqnwb

Software C++ API for acquiring neurophysiological data directly into the NWB (Neurodata Without Borders) format. Our goal is to provide a lightweight API to integrate with existing acquisition systems.

Proper citation: AqNWB (RRID:SCR_028050) Copy   

•   Source: SciCrunch Registry

https://github.com/GabrielHoffman/dreamlet

Software R package enables differential expression analysis on multi-sample single cell datasets using linear (mixed) models with precision weights.

Proper citation: dreamlet (RRID:SCR_028168) Copy   

•   Source: SciCrunch Registry

https://github.com/meganhuibregtse/peri-code

Software R code to apply Stages of Reproductive Aging Workshop + 10 stages to prospectively collected vaginal bleeding data among a cohort of Black women aged 40–55 years. Used to apply STRAW+10 stages to prospectively tracked menstrual bleeding data in a longitudinal cohort study of perimenopausal women.

Proper citation: PERI: Prospective Evaluation of Reproductive aging Indicators (RRID:SCR_028698) Copy   

•   Source: SciCrunch Registry