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

OdorDb is a database of odorant molecules, which can be searched in a few different ways. One can see odorant molecules in the OdorDB, and the olfactory receptors in ORDB that they experimentally shown to bind. You can search for odorant molecules based on their attributes or identities: Molecular Formula, Chemical Abstracts Service (CAS) Number and Chemical Class. Functional studies of olfactory receptors involve their interactions with odor molecules. OdorDB contains a list of odors that have been identified as binding to olfactory receptors.

Proper citation: Odor Molecules DataBase (RRID:SCR_007286) Copy   

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http://www.stanford.edu/group/exonarray/cgi-bin/plot_selector.pl

Transcriptome database of acutely isolated purified astrocytes, neurons, and oligodendrocytes. Provides improved cell-type-specific markers for better understanding of neural development, function, and disease.

Proper citation: Exon Array Browser (RRID:SCR_008712) Copy   

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http://stemcelldb.nih.gov/public.do

Database characterizing and comparing pluripotent human stem cells. The growth and culture conditions of all 21 human embryonic stem cell lines approved under the August 2001 Presidential Executive Order have been analyzed. Available to the scientific community are the results of our rigorous characterization of these cell lines at a more advanced level.

Proper citation: StemCellDB (RRID:SCR_006305) Copy   

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http://www.wwpdb.org/

Public global Protein Data Bank archive of macromolecular structural data overseen by organizations that act as deposition, data processing and distribution centers for PDB data. Members are: RCSB PDB (USA), PDBe (Europe) and PDBj (Japan), and BMRB (USA). This site provides information about services provided by individual member organizations and about projects undertaken by wwPDB. Data available via websites of its member organizations.

Proper citation: Worldwide Protein Data Bank (wwPDB) (RRID:SCR_006555) Copy   

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https://www.bci2000.org/

BCI2000 is a general-purpose system for brain-computer interface (BCI) and adaptive neurotechnology research. It can also be used for data acquisition, stimulus presentation, and brain monitoring applications. The mission of the BCI2000 project is to facilitate research and applications in the areas described. Their vision is that BCI2000 will become a widely used software tool for diverse areas of real-time biosignal processing. In order to achieve this vision, BCI2000 system is available for free for non-profit research and educational purposes. BCI2000 supports a variety of data acquisition systems, brain signals, and study/feedback paradigms. During operation, BCI2000 stores data in a common format (BCI2000 native or GDF), along with all relevant event markers and information about system configuration. BCI2000 also includes several tools for data import/conversion (e.g., a routine to load BCI2000 data files directly into Matlab) and export facilities into ASCII. BCI2000 also facilitates interactions with other software. For example, Matlab scripts can be executed in real-time from within BCI2000, or BCI2000 filters can be compiled to execute as stand-alone programs. Furthermore, a simple network-based interface allows for interactions with external programs written in any programming language. For example, a robotic arm application that is external to BCI2000 may be controlled in real time based on brain signals processed by BCI2000, or BCI2000 may use and store along with brain signals behavioral-based inputs such as eye-tracker coordinates. Because it is based on a framework whose services can support any BCI implementation, the use of BCI2000 provides maximum benefit to comprehensive research programs that operate multiple BCI2000 installations to collect data for a variety of studies. The most important benefits of the system in such situations are: - A Proven Solution - Facilitates Operation of Research Programs - Facilitates Deployment in Multiple Sites - Cross-Platform and Cross-Compiler Compatibility - Open Resource Sponsors: BCI2000 development is sponsored by NIH/NIBIB R01 and NIH/NINDS U24 grants. Keywords: General, Purpose, Systems, Brain, Computer, Interface, Research, Application, Brain, Diverse, Educational, Laboratory, Software, Network, Signals, Behavioral, Eye, Tracker,

Proper citation: Brain Computer Interface 2000 Software Package (RRID:SCR_007346) Copy   

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http://surfer.nmr.mgh.harvard.edu/fswiki/Tracula

Software tool developed for automatically reconstructing a set of major white matter pathways in the brain from diffusion weighted images using probabilistic tractography. This method utilizes prior information on the anatomy of the pathways from a set of training subjects. By incorporating this prior knowledge in the reconstruction procedure, our method obviates the need for manual intervention with the tract solutions at a later stage and thus facilitates the application of tractography to large studies. The trac-all script is used to preprocess raw diffusion data (correcting for eddy current distortion and B0 field inhomogenities), register them to common spaces, model and reconstruct major white matter pathways (included in the atlas) without any manual intervention. trac-all may be used to execute all the above steps or parts of it depending on the dataset and user''''s preference for analyzing diffusion data. Alternatively, scripts exist to execute chunks of each processing pipeline, and individual commands may be run to execute a single processing step. To explore all the options in running trac-all please refer to the trac-all wiki. In order to use this script to reconstruct tracts in Diffusion images, all the subjects in the dataset must have Freesurfer Recons.

Proper citation: TRACULA (RRID:SCR_013152) Copy   

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https://github.com/flatironinstitute/mountainsort

Neurophysiological spike sorting software.

Proper citation: MountainSort (RRID:SCR_017446) Copy   

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http://ibvd.virtualbrain.org/

A database of brain neuroanatomic volumetric observations spanning various species, diagnoses, and structures for both individual and group results. A major thrust effort is to enable electronic access to the results that exist in the published literature. Currently, there is quite limited electronic or searchable methods for the data observations that are contained in publications. This effort will facilitate the dissemination of volumetric observations by making a more complete corpus of volumetric observations findable to the neuroscience researcher. This also enhances the ability to perform comparative and integrative studies, as well as metaanalysis. Extensions that permit pre-published, non-published and other representation are planned, again to facilitate comparative analyses. Design strategy: The principle organizing data structure is the "publication". Publications report on "groups" of subjects. These groups have "demographic" information as well as "volume" information for the group as a whole. Groups are comprised of "individuals", which also have demographic and volume information for each of the individuals. The finest-grained data structure is the "individual volume record" which contains a volume observation, the units for the observation, and a pointer to the demographic record for individual upon which the observation is derived. A collection of individual volumes can be grouped into a "group volume" observation; the group can be demographically characterized by the distribution of individual demographic observations for the members of the group.

Proper citation: Internet Brain Volume Database (RRID:SCR_002060) Copy   

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http://www.mitomap.org/

Database of polymorphisms and mutations of the human mitochondrial DNA. It reports published and unpublished data on human mitochondrial DNA variation. All data is curated by hand. If you would like to submit published articles to be included in mitomap, please send them the citation and a pdf.

Proper citation: MITOMAP - A human mitochondrial genome database (RRID:SCR_002996) Copy   

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http://www.gensat.org/daily_showcase.jsp

THIS RESOURCE IS NO LONGER IN SERVICE, documented on March 19, 2012. Due to budgetary constraints, the National Center for Biotechnology Information (NCBI) has discontinued support for the NCBI GENSAT database, and it has been removed from the Entrez System. The Gene Expression Nervous System Atlas (GENSAT) project involves the large-scale creation of transgenic mouse lines expressing green fluorescent protein (GFP) reporter or Cre recombinase under control of the BAC promoter in specific neural and glial cell populations. BAC expression data for all the lines generated (over 1300 lines) are available in online, searchable databases (www.gensat.org and the Database of GENSAT BAC-Cre driver lines). If you have any specific questions, please feel free to contact us at info_at_ncbi.nlm.nih.gov The GENSAT project aims to map the expression of genes in the central nervous system of the mouse, using both in situ hybridization and transgenic mouse techniques. Search criteria include gene names, gene symbols, gene aliases and synonyms, mouse ages, and imaging protocols. Mouse ages are restricted to E10.5 (embryonic day 10.5), E15.5 (embryonic day 15.5), P7 (postnatal day 7), and Adult (adult). The project focuses on two techniques * Evaluation of unmodified mice lines for expression of a given gene using radiolabelled riboprobes and in-situ hybridization. * Creation of transgenic mice lines containing a BAC construct that expresses a marker gene in the same environment as the native gene

Proper citation: GENSAT at NCBI - Gene Expression Nervous System Atlas (RRID:SCR_003923) Copy   

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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   

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http://www.cise.ufl.edu/~abarmpou/lab/fanDTasia/

A Java applet tool for DT-MRI processing. It opens Diffusion-Weighted MRI datasets from user's computer and performs very efficient tensor field estimation using parallel threaded processing on user's browser. No installation is required. It runs on any operating system that supports Java (Windows, Mac, Linux,...). The estimated tensor field is guaranteed to be positive definite second order or higher order and is saved in user's local disc. MATLAB functions are also provided to open the tensor fields for your convenience in case you need to perform further processing. The fanDTasia Java applet provides also vector field visualization for 2nd and 4th-order tensors, as well as calculation of various anisotropic maps. Another useful feature is 3D fiber tracking (DTI-based) which is also shown using 3d graphics on the user's browser.

Proper citation: fanDTasia Java Applet: DT-MRI Processing (RRID:SCR_009624) Copy   

•   Source: SciCrunch Registry

http://www.regardsstudy.org/

The REasons for Geographic and Racial Differences in Stroke (REGARDS) project, sponsored by the National Institutes of Health (NIH), is a national study focusing on learning more about the factors that increase a person''s risk of having a stroke. REGARDS is an observational study of risk factors for stroke in adults 45 years or older. 30,239 participants were recruited between January 2003 and October 2007. They completed a telephone interview followed by an in-home physical exam. Measurements included traditional risk factors such as blood pressure and cholesterol levels, and an echocardiogram of the heart. At six month intervals, participants are contacted by phone to ask about stroke symptoms, hospitalizations and general health status. The study is ongoing and will follow participants for many years. The purpose of the REGARDS project is to understand why people in some parts of the country develop more strokes than people in other parts of the country, and why blacks develop more strokes than whites. We hope to learn how to reduce the number of people having strokes.

Proper citation: REGARDS - REasons for Geographic and Racial Differences in Stroke (RRID:SCR_007228) Copy   

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http://hbatlas.org/pages/publications

A research paper with supplementary materials reporting the generation and analysis of exon-level transcriptome and associated genotyping data. The experiment represented both males and females of multiple ethnicities and examines gene regulation and expression in different areas of the brain. A data set on the human brain transcriptome as well as insights into the transcriptional foundations of human neurodevelopment is provided.

Proper citation: Spatio-temporal transcriptome of the human brain (RRID:SCR_013743) Copy   

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https://neurophysics.ucsd.edu/software.php

Matlab-based routines for the detection and clustering of putative single units from a multi-unit time series, along with quality metrics. This sofwtare was developed by the David Kleinfeld Laboratory at UC San Diego.

Proper citation: UltraMegaSort 2000 (RRID:SCR_015857) Copy   

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https://datascience.uth.edu/medcis

NIH funded center to provide system for sharing multimodal epilepsy data for Sudden Unexpected Death in Epilepsy. Modality Epilepsy Data Capture and Integration System (MEDCIS) is cross cohort query interface for SUDEP (Sudden Unexpected Death in EPilepsy) research.

Proper citation: University of Texas Health Science at Houston Center for SUDEP Research (RRID:SCR_024700) Copy   

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http://neuromab.ucdavis.edu/

A national mouse monoclonal antibody generating resource for biochemical and immunohistochemical applications in mammalian brain. NeuroMabs are generated from mice immunized with synthetic and recombinant immunogens corresponding to components of the neuronal proteome as predicted from genomic and other large-scale cloning efforts. Comprehensive biochemical and immunohistochemical analyses of human, primate and non-primate mammalian brain are incorporated into the initial NeuroMab screening procedure. This yields a subset of mouse mAbs that are optimized for use in brain (i.e. NeuroMabs): for immunocytochemical-based imaging studies of protein localization in adult, developing and pathological brain samples, for biochemical analyses of subunit composition and post-translational modifications of native brain proteins, and for proteomic analyses of native brain protein networks. The NeuroMab facility was initially funded with a five-year U24 cooperative grant from NINDS and NIMH. The initial goal of the facility for this funding period is to generate a library of novel NeuroMabs against neuronal proteins, initially focusing on membrane proteins (receptors/channels/transporters), synaptic proteins, other neuronal signaling molecules, and proteins with established links to disease states. The scope of the facility was expanded with supplements from the NIH Blueprint for Neuroscience Research to include neurodevelopmental targets, the NIH Roadmap for Medical Research to include epigenetics targets, and NIH Office of Rare Diseases Research to include rare disease targets. These NeuroMabs will then be produced on a large scale and made available to the neuroscience research community on an inexpensive basis as tissue culture supernatants or purified immunoglobulin by Antibodies Inc. The UC Davis/NIH NeuroMab Facility makes NeuroMabs available directly to end users and is unable to accommodate sales to distributors for third party distribution. Note, NeuroMab antibodies are now offered through antibodiesinc.

Proper citation: NeuroMab (RRID:SCR_003086) Copy   

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http://senselab.med.yale.edu

The SenseLab Project is a long-term effort to build integrated, multidisciplinary models of neurons and neural systems. It was founded in 1993 as part of the original Human Brain Project, which began the development of neuroinformatics tools in support of neuroscience research. It is now part of the Neuroscience Information Framework (NIF) and the International Neuroinformatics Coordinating Facility (INCF). The SenseLab project involves novel informatics approaches to constructing databases and database tools for collecting and analyzing neuroscience information, using the olfactory system as a model, with extension to other brain systems. SenseLab contains seven related databases that support experimental and theoretical research on the membrane properties: CellPropDB, NeuronDB, ModelDB, ORDB, OdorDB, OdorMapDB, BrainPharmA pilot Web portal that successfully integrates multidisciplinary neurocience data.

Proper citation: SenseLab (RRID:SCR_007276) Copy   

•   Source: SciCrunch Registry

http://www.ini.uzh.ch/~acardona/trakem2.html

An ImageJ plugin for morphological data mining, three-dimensional modeling and image stitching, registration, editing and annotation. Two independent modalities exist: either XML-based projects, working directly with the file system, or database-based projects, working on top of a local or remote PostgreSQL database. What can you do with it? * Semantic segmentation editor: order segmentations in tree hierarchies, whose template is exportable for reuse in other, comparable projects. * Model, visualize and export 3D. * Work from your laptop on your huge, remote image storage. * Work with an endless number of images, limited only by the hard drive capacity. Dozens of formats supported thanks to LOCI Bioformats and ImageJ. * Import stacks and even entire grids (montages) of images, automatically stitch them together and homogenize their histograms for best montaging quality. * Add layers conveniently. A layer represents, for example, one 50 nm section (for TEM) or a confocal section. Each layer has its own Z coordinate and thickness, and contains images, labels, areas, nodes of 3d skeletons, profiles... * Insert layer sets into layers: so your electron microscopy serial sections can live inside your optical microscopy sections. * Run any ImageJ plugin on any image. * Measure everything: areas, volumes, pixel intensities, etc. using both built-in data structures and segmentation types, and standard ImageJ ROIs. And with double dissectors! * Visualize RGB color channels changing the opacity of each on the fly, non-destructively. * Annotate images non-destructively with floating text labels, which you can rotate/scale on the fly and display in any color. * Montage/register/stitch/blend images manually with transparencies, semiautomatically, or fully automatically within and across sections, with translation, rigid, similarity and affine models with automatically extracted SIFT features. * Correct the lens distortion present in the images, like those generated in transmission electron microscopy. * Add alpha masks to images using ROIs, for example to split images in two or more parts, or to remove the borders of an image or collection of images. * Model neuronal arbors with 3D skeletons (with areas or radiuses), and synapses with connectors. * Undo all steps. And much more...

Proper citation: TrakEM2 (RRID:SCR_008954) Copy   

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http://becs.aalto.fi/en/research/bayes/drifter/

Model based Bayesian method for eliminating physiological noise from fMRI data. This algorithm uses image voxel analysis to isolate the cardiac and respiratory noise from the relevant data.

Proper citation: DRIFTER (RRID:SCR_014937) Copy   

•   Source: SciCrunch Registry