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http://mindboggle.info

Mindboggle (http://mindboggle.info) is open source software for analyzing the shapes of brain structures from human MRI data. The following publication in PLoS Computational Biology documents and evaluates the software: Klein A, Ghosh SS, Bao FS, Giard J, Hame Y, Stavsky E, Lee N, Rossa B, Reuter M, Neto EC, Keshavan A. (2017) Mindboggling morphometry of human brains. PLoS Computational Biology 13(3): e1005350. doi:10.1371/journal.pcbi.1005350

Proper citation: Mindboggle (RRID:SCR_002438) Copy   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

http://krasnow1.gmu.edu/CENlab/software.html

Stochastic reaction-diffusion simulator in Java which is used for simulating neuronal signaling pathways.

Proper citation: NeuroRD (RRID:SCR_014769) Copy   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

http://www.armystarrs.org/

Study of mental health risk and resilience factors ever conducted among military personnel. The purpose of Army STARRS is to identify as quickly as possible factors that protect or pose risks to Soldiers'' emotional well-being and overall mental health so that the Army may apply the knowledge to its ongoing health promotion, risk reduction, and suicide prevention efforts. Army STARRS investigators will use four separate study components the Historical Data Study, New Soldier Study, All Army Study, and Soldier Health Outcomes Study to identify factors that help protect a Soldier''s mental health and factors that put a Soldier''s mental health at risk. Army STARRS is a five-year study that will run through 2014. Findings will be reported as they become available, so that the Army may apply them to its ongoing health promotion, risk reduction, and suicide prevention efforts. Given its length and scope, Army STARRS will generate a vast amount of information and will allow investigators to focus on periods in a military career that are known to be high risk for psychological problems. The information gathered from volunteer participants throughout the study will help researchers identify not only potentially relevant risk factors, but potential protective factors as well. Because promoting mental health and reducing suicide risk are important for all Americans, the findings from Army STARRS will benefit not only servicemembers but the nation as a whole. NIMH has assembled a group of renowned experts to carry out this research including teams from the Uniformed Services University of the Health Sciences (USUHS), the University of California, San Diego, University of Michigan, Harvard Medical School, and NIMH. Additional Army and NIMH program staff will contribute to the oversight and implementation of the study. This research team brings together international leaders in military health, health and behavior surveys, epidemiology, suicide, and genetic and neurobiological factors involved in psychological health.

Proper citation: Army STARRS (RRID:SCR_006708) Copy   

•   Source: SciCrunch Registry

https://github.com/SciCrunch/NIF-Ontology/tree/neurons/ttl

An ontology for describing the complex phenotypes of neurons.

Proper citation: Neuron Phenotype Ontology (RRID:SCR_017403) Copy   

•   Source: SciCrunch Registry

https://umgear.org/

Portal for visualization and analysis of multi omic data in public and private domains. Enables upload, visualization and analysis of scRNA-seq data.

Proper citation: gene Expression Analysis Resource (RRID:SCR_017467) Copy   

•   Source: SciCrunch Registry

https://github.com/PriceLab/TReNA

Methods for reconstructing transcriptional regulatory networks.

Proper citation: TReNA (RRID:SCR_017458) Copy   

•   Source: SciCrunch Registry

http://www.brainimagelibrary.org

Repository for confocal microscopy brain imaging data. Data archives that have been established by BRAIN Initiative Data Sharing. National public resource enabling researchers to deposit, analyze, mine, share and interact with large brain image datasets. Operated as partnership between Biomedical Applications Group at Pittsburgh Supercomputing Center, Center for Biological Imaging at University of Pittsburgh and Molecular Biosensor and Imaging Center at Carnegie Mellon University. Provides persistent centralized repository for brain microscopy data.

Proper citation: Brain Image Library (RRID:SCR_017272) Copy   

•   Source: SciCrunch Registry

https://bossdb.org/

BossDB (Brain Observatory Storage Service and Database) is a cloud-based ecosystem for the storage and management of public large-scale volumetric neuroimaging and connectomics datasets. This includes volumetric Electron Microscopy and X-Ray Micro/Nanotomography data with support for multi-channel image data, segmentations, annotations, meshes, and connectomes. BossDB integrates with community resources for data access, processing, visualization, and analysis, and includes an API that enables metadata management, rendering, datatype conversions, and ingest.

Proper citation: Brain Observatory Storage Service and Database (BossDB) (RRID:SCR_017273) Copy   

•   Source: SciCrunch Registry

http://pinet-server.org

Web platform for downstream analysis and visualization of proteomics data. Server that facilitates integrated annotation, analysis and visualization of quantitative proteomics data, with emphasis on PTM networks and integration with LINCS library of chemical and genetic perturbation signatures in order to provide further mechanistic and functional insights. Primary input for server consists of set of peptides or proteins, optionally with PTM sites, and their corresponding abundance values.

Proper citation: piNET (RRID:SCR_018693) Copy   

•   Source: SciCrunch Registry

https://www.epimodel.org/

Software R package for mathematical modeling of infectious disease over networks. Provides tools for simulating and analyzing mathematical models of infectious disease dynamics. Mathematical Modeling of Infectious Disease Dynamics.

Proper citation: EpiModel (RRID:SCR_018539) Copy   

•   Source: SciCrunch Registry

https://github.com/aplbrain/saber

Library of containerized tools and workflow deployment system for enabling processing of large neuroimaging datasets. Provides canonical neuroimaging workflows specified in standard workflow language (CWL), integration with workflow execution engine (Airflow), imaging database (bossDB), and parameter database (Datajoint) to deploy workflows at scale, and tools to automate deployment and optimization of neuroimaging pipelines.

Proper citation: Scalable Analytics for Brain Exploration Research (RRID:SCR_018812) Copy   

•   Source: SciCrunch Registry

https://openwetware.org/wiki/RAVE

Open source software tool for reproducible analysis and visualization of intracranial EEG data. Used for analysis of intracranial electroencephalogram data, including data collected using strips and grids (electrocorticography, ECoG) and depth electrodes (stereotactic EEG).

Proper citation: RAVE (RRID:SCR_019040) Copy   

•   Source: SciCrunch Registry

https://github.com/r3fang/SnapATAC

Software package for analyzing scATAC-seq datasets.Used to dissects cellular heterogeneity in unbiased manner and map trajectories of cellular states. Can process data from up to million cells. Incorporates existing tools into comprehensive package for analyzing single cell ATAC-seq dataset.

Proper citation: SnapATAC (RRID:SCR_020981) Copy   

•   Source: SciCrunch Registry

https://github.com/DeNardoLab/BehaviorDEPOT

Software tool for automated behavioral detection based on markerless pose tracking. Behavioral analysis tool to first compile and clean point-tracking output from DeepLabCut, and then classify behavioral epochs using custom behavior classifiers. Used to detect frame by frame behavior from video time series and can analyze results of common experimental assays, including fear conditioning, decision-making in T-maze, open field, elevated plus maze, and novel object exploration. Calculates kinematic and postural statistics from keypoint tracking data from pose estimation software outputs.

Proper citation: BehaviorDEPOT (RRID:SCR_023602) Copy   

•   Source: SciCrunch Registry

https://github.com/TADA-A/TADA-A/tree/master

Software statistical framework for mapping risk genes from de novo mutations in whole genome sequencing studies.

Proper citation: TADA-A (RRID:SCR_024538) Copy   

•   Source: SciCrunch Registry

http://www.bios.unc.edu/research/genomic_software/Matrix_eQTL/

Software tool for ultra fast eQTL analysis via large matrix operations.

Proper citation: MatrixEQTL (RRID:SCR_025513) Copy   

•   Source: SciCrunch Registry

https://brainlife.io/docs/using_ezBIDS/

Web-based BIDS conversion tool to convert neuroimaging data and associated metadata to BIDS standard. Guided standardization of neuroimaging data interoperable with major data archives and platforms.

Proper citation: ezBIDS (RRID:SCR_025563) Copy   

•   Source: SciCrunch Registry

https://kimlab.io/brain-map/DevATLAS/

Whole brain developmental map of neuronal circuit maturation. Generated by whole brain spatiotemporal mapping of circuit maturation during early postnatal development. Standard reference for normative developmental trajectory of neuronal circuit maturation, as well as high throughput platform to pinpoint when and where circuit maturation is disrupted in mouse models of neurodevelopmental disorders, such as fragile X syndrome.

Proper citation: DevATLAS (RRID:SCR_025718) Copy   

•   Source: SciCrunch Registry