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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.
Seattle based independent, nonprofit medical research organization dedicated to accelerating the understanding of how human brain works. Provides free data and tools to researchers and educators and variety of unique online public resources for exploring the nervous system. Integrates gene expression data and neuroanatomy, along with data search and viewing tools, these resources are openly accessible via the Allen Brain Atlas data portal. Provides Allen Mouse Brain, Allen Spinal Cord Atlas, Allen Developing Mouse Brain Atlas, Allen Human Brain Atlas,Allen Mouse Brain Connectivity Atlas, Allen Cell Type Database, The Ivy Glioblastoma Atlas Project (Ivy GAP), The BrainSpan Atlas of the Developing Human Brain.
Proper citation: Allen Institute for Brain Science (RRID:SCR_006491) Copy
Python-based software for experimental neurophysiology. It includes support for patch-clamp electrophysiology, multiphoton imaging, scanning laser photostimulation, and many other experimental techniques.
Proper citation: ACQ4 (RRID:SCR_016444) Copy
Consortium for the cell census in the brain. Integrated network of data generating centers, data archives, and data standards developers, with the goal of systematic multimodal brain cell type profiling and characterization. Emphasis of the BICCN is on the whole mouse brain with demonstration of prototype feasibility for human and nonhuman primate brains.
Proper citation: BICCN (RRID:SCR_015820) Copy
http://www.nitrc.org/projects/nutil/
Software toolbox to simplify and streamline mechanism of pre and post processing 2D brain image data. Neuroscience image processing and analysis utilities. Stand alone application that runs on all operating systems. Nutil is part of the QUINT workflow.
Proper citation: Nutil - Neuroimaging utilities (RRID:SCR_017183) Copy
http://www.linked-neuron-data.org/
Neuroscience data and knowledge from multiple scales and multiple data sources that has been extracted, linked, and organized to support comprehensive understanding of the brain. The core is the CAS Brain Knowledge base, a very large scale brain knowledge base based on automatic knowledge extraction and integration from various data and knowledge sources. The LND platform provides services for neuron data and knowledge extraction, representation, integration, visualization, semantic search and reasoning over the linked neuron data. Currently, LND extracts and integrates semantic data and knowledge from the following resources: PubMed, INCF-CUMBO, Allen Reference Atlas, NIF, NeuroLex, MeSH, DBPedia/Wikipedia, etc.
Proper citation: Linked Neuron Data (RRID:SCR_003658) Copy
http://neuromorpho.org/index.jsp
Centrally curated inventory of digitally reconstructed neurons associated with peer-reviewed publications that contains some of the most complete axonal arborizations digitally available in the community. Each neuron is represented by a unique identifier, general information (metadata), the original and standardized ASCII files of the digital morphological reconstruction, and a set of morphometric features. It contains contributions from over 100 laboratories worldwide and is continuously updated as new morphological reconstructions are collected, published, and shared. Users may browse by species, brain region, cell type or lab name. Users can also download morphological reconstructions for research and analysis. Deposition and distribution of reconstruction files ultimately prevents data loss. Centralized curation and annotation aims at minimizing the effort required by data owners while ensuring a unified format. It also provides a one-stop entry point for all available reconstructions, thus maximizing data visibility and impact.
Proper citation: NeuroMorpho.Org (RRID:SCR_002145) Copy
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
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Welcome to the Neuroscience Information Framework Project, designed to serve the biomedical research community. NIF maintains the largest searchable collection of neuroscience data, the largest catalog of biomedical resources, and the largest ontology for neuroscience on the web. We welcome all feedback and suggestions and are actively looking for resource providers to make their resources accessible through NIF. Learn about the tools available to help you share your data and discover a dynamic inventory of Web-based neuroscience resources.
