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http://brain-development.org/

brain-development.org hosts data and resources used in computational analysis of brain development, including MRI data sets of developing human, software tools, atlases, protocols and software. Several different atlas datasets are available including: * Adult * Pediatric * Neonatal (T2 Templates, Probability Maps) * Neonatal (High-definition, T1 and T2 Templates, Probability Maps) * Fetal (High-definition, T2 Templates, Probability Maps) * Atlas software Anatomical segmentation protocols are available, as well as an Image Registration Toolkit.

Proper citation: brain-development.org (RRID:SCR_005838) Copy   

•   Source: SciCrunch Registry

http://brain-development.org/ixi-dataset/

Data set of nearly 600 MR images from normal, healthy subjects, along with demographic characteristics, collected as part of the Information eXtraction from Images (IXI) project available for download. Tar files containing T1, T2, PD, MRA and DTI (15 directions) scans from these subjects are available. The data has been collected at three different hospitals in London: * Hammersmith Hospital using a Philips 3T system * Guy''s Hospital using a Philips 1.5T system * Institute of Psychiatry using a GE 1.5T system

Proper citation: IXI dataset (RRID:SCR_005839) Copy   

•   Source: SciCrunch Registry

http://hadvwg.gmu.edu/

The Human Adenovirus Type Classification coordinates the naming of candidate new types, prior to manuscript submission for peer review. This resource contains a method of submitting candidate HAdV, criteria for a new HAdV type, and a Serotyping tool, which displays all potential types corresponding to the query serotype entered by a user. The criteria are based on discussions at the International Adenovirus Meeting (Dobog��k, Hungary; 26-30 April, 2009) and the NIH Human Adenovirus Working Group Workshop (Bethesda, MD. USA; 3 February 2011), which are summarized in a Letter to the Editor.

Proper citation: Human Adenovirus Type Classification (RRID:SCR_005753) Copy   

•   Source: SciCrunch Registry

http://en.opasnet.org

Opasnet is a wiki-based website and workspace for helping societal decision making. The website collects, synthesizes, and distributes people''s values and scientific information. Opasnet welcomes anyone who wants to promote science-based decision-making in any field. The specialty is that the information is structured for both scientific scrutiny and for policy use at the same time. In practice, you can do original research, store data, make models, and perform policy assessments and discuss all of that work in one workspace. Originally, the developers of Opasnet came from the environmental health, i.e. a research field that studies the impacts of environment on human health. We are actively working, among other things, on climate change and air pollution, but you can also start a new assessment about a decision of your own interest, or participate in an existing assessment. Opasnet is a website that has basically two parts. One part is a wiki site (called Opasnet wiki or simply Opasnet) that has descriptive pages with text, figures, and tables; it also contains files. The other part is a database called Opasnet Base that contains quantitative estimates about anything that is described in Opasnet. The majority of information is openly available. However, both Opasnet wiki and Opasnet Base have a protected area for working with material that is non-public for some reason.

Proper citation: Opasnet (RRID:SCR_005751) Copy   

•   Source: SciCrunch Registry

http://www.learnaboutsma.org/

Learn About SMA is a resource for spinal muscular atrophy (SMA) patients, families and researchers. The site includes stories of living with SMA and recent advances in the understanding and potential treatment of SMA. Learn About SMA is divided into five sections with video interviews, animations, and narrative. What is SMA? includes interviews with doctors and patients, plus an animation explaining the cause, inheritance and diagnosis of SMA. SMA Science provides an introduction to the genes and mechanisms involved with SMA, including 2-D and 3-D animations and interviews with Nobel Laureates. * In SMA Therapies doctors discuss current and potential treatments for SMA and a father describes the daily routine of physical therapies for his daughter, who has SMA. Antisense Therapy for SMA includes videos and animations to explain antisense therapy for SMA. In Living with SMA four SMA families describe daily routines, disease progression, children''s understanding of SMA, and grieving.

Proper citation: Learn about SMA website (RRID:SCR_005592) Copy   

•   Source: SciCrunch Registry

http://www.sociopatterns.org/

SocioPatterns is an interdisciplinary research collaboration that adopts data-driven methodology with the aim of uncovering fundamental patterns in social dynamics and coordinated human activity. To achieve its scientific goals, the SocioPatterns collaboration also contributes to the development of new technologies for collecting relevant data. In particular, the collaboration supports the development of the SocioPatterns sensing platform, which uses wireless wearable sensors to gather longitudinal data on human mobility and face-to-face proximity in real-world environments. The SocioPatterns team also works on developing tools and techniques to represent, analyze and visualize the collected data. We increasingly use digital media and computational devices in our daily activities, and leave behind a sizable amount of digital traces while doing so. The proliferation of mobile devices, and the incorporation of various sensing technologies in these devices, will further add to this growing trail of data. The possibility to mine and analyze these data, and the scale at which this can be done on contemporary computer systems, affords a novel, data-driven approach in the investigation of various aspects of human behavior. The following collection of datasets obtained through the SocioPatterns sensing platform are available: * Infectious SocioPatterns dynamic contact networks * Hypertext 2009 dynamic contact network * Primary school cumulative networks * Infectious SocioPatterns

Proper citation: SocioPatterns (RRID:SCR_005739) Copy   

•   Source: SciCrunch Registry

http://riodb.ibase.aist.go.jp/brain/index.php?LANG=ENG

Atlas of magnetic resonance images and histological sections of a Japanese monkey brain, Rhesus monkey and human. The Brain Explorer allows for display, magnification, and comparison these images. Other formats include a collection of .jpg images, Quicktime VR (allow user to zoom in), and EmonV, a voxel viewer for MacOS X.

Proper citation: Brain Atlas Database of Japanese Monkey for WWW (RRID:SCR_006104) Copy   

•   Source: SciCrunch Registry

http://afni.nimh.nih.gov/afni/

Set of (mostly) C programs that run on X11+Unix-based platforms (Linux, Mac OS X, Solaris, etc.) for processing, analyzing, and displaying functional MRI (FMRI) data defined over 3D volumes and over 2D cortical surface meshes. AFNI is freely distributed as source code plus some precompiled binaries.

Proper citation: Analysis of Functional NeuroImages (RRID:SCR_005927) Copy   

•   Source: SciCrunch Registry

http://www.isrctn.com

A primary clinical trial registry which houses proposed, ongoing, and completed clinical research studies. An ISRCTN is a simple numeric system for the unique identification of randomized controlled trials worldwide. The registry provides content validation and curation and the unique identification number necessary for publication. Submitted studies range from cancer to urological diseases.

Proper citation: ISRCTN Registry (RRID:SCR_006087) Copy   

•   Source: SciCrunch Registry

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

EPI-images of 25 participants gathered during rest as well as anonymized anatomical images of the same participants. The resting-state fMRI images were collected on several occasions: # the first resting-state scan in a scan session # 5-11 months after the first resting-state scan # about 30 (< 45) minutes after 2. Each scan occasion is released as a new version release of the resource. ---Caution: Participants here are part of the NewYork_a contribution to the 1000 Functional Connectomes Project. DO NOT combine datasets.

Proper citation: NYU CSC TestRetest (RRID:SCR_005975) Copy   

•   Source: SciCrunch Registry

http://www.dartmouth.edu/~rswenson/NeuroSci/index.html

On line textbook of basic clinical and functional neuroscience, developed by Rand S. Swenson, D.C., M.D., Ph.D., Dartmouth Medical School Chapter Index * Introduction * Cellular organization * Peripheral nervous system * Development * Spinal cord * Brain stem organization * Sensory systems * Motor systems * Limbic system * Thalamic organization * Cerebral cortical organization * Nutrition of the brain * Conclusions

Proper citation: Review of Clinical and Functional Neuroscience (RRID:SCR_005964) Copy   

•   Source: SciCrunch Registry

http://www.human-phenotype-ontology.org/

Provides standardized vocabulary of phenotypic abnormalities encountered in human disease. Structured and controlled vocabulary for phenotypic features encountered in human hereditary and other disease. HPO is being developed in collaboration with members of OBO Foundry (Open Biological and Biomedical Ontologies), and logical definitions for HPO terms are being developed using PATO and a number of other ontologies including FMA, GO, ChEBI, and MPATH.

Proper citation: Human Phenotype Ontology (RRID:SCR_006016) Copy   

•   Source: SciCrunch Registry

http://neuroviisas.med.uni-rostock.de/neuroviisas.html

An open framework for integrative data analysis, visualization and population simulations for the exploration of network dynamics on multiple levels. This generic platform allows the integration of neuroontologies, mapping functions for brain atlas development, and connectivity data administration; all of which are required for the analysis of structurally and neurobiologically realistic simulations of networks. What makes neuroVIISAS unique is the ability to integrate neuroontologies, image stacks, mappings, visualizations, analyzes and simulations to use them for modelling and simulations. Based on the analysis of over 2020 tracing studies, atlas terminologies and registered histological stacks of images, neuroVIISAS permits the definition of neurobiologically realistic networks that are transferred to the simulation engine NEST. The analysis on a local and global level, the visualization of connectivity data and the results of simulations offer new possibilities to study structural and functional relationships of neural networks. neuroVIISAS provide answers to questions like: # How can we assemble data of tracing studies? (Metastudy) # Is it possible to integrate tracing and brainmapping data? (Data Integration) # How does the network of analyzed tracing studies looks like? (Visualization) # Which graph theoretical properties posses such a network? (Analysis) # Can we perform population simulations of a tracing study based network? (Simulation and higher level data integration) neuroVIISAS can be used to organize mapping and connectivity data of central nervous systems of any species. The rat brain project of neuroVIISAS contains 450237 ipsi- and 175654 contralateral connections. A list of evaluated tracing studies are available. PyNEST script generation does work using WINDOWS OS, however, the script must be transferred to a UNIX OS with installed NEST. The results file of the NEST simulation can be visualized and analyzed by neuroVIISAS on a WINDOWS OS.

Proper citation: neuroVIISAS (RRID:SCR_006010) Copy   

•   Source: SciCrunch Registry

http://www.ncbi.nlm.nih.gov/projects/gv/rbc/main.fcgi?cmd=init

The dbRBC database provides an open, publicly accessible platform for DNA and clinical data related to the human Red Blood Cells (RBC). A new bioinformatics resource, dbRBC, has been installed at the National Center of Biotechnology Information (NCBI). This resource combines the well established Blood Group Antigen Gene Mutation Database (BGMUT) with tools and interlinked resources developed at the NCBI. The main task of dbRBC is to provide access to publicly available genomic, protein and structural information linked to the red blood cell antigens. The site offers a number of resources: * BGMUT Database * Alignment Viewer * SBT Tool * Probe/Primer Resource * Typing Kit Interface * Obstacle

Proper citation: NCBI dbRBC (RRID:SCR_005959) Copy   

•   Source: SciCrunch Registry

http://www.icpsr.umich.edu/icpsrweb/NACDA/

Archive of data relevant to gerontological and aging research. Used to advance research on aging. Subjects include demographic, social, economic, and psychological characteristics of older adults, physical health and functioning of older adults, and health care needs of older adults. NACDA staff represents team of professional researchers, archivists and technicians who work together to obtain, process, distribute, and promote data relevant to aging research.

Proper citation: National Archive of Computerized Data on Aging (NACDA) (RRID:SCR_005876) Copy   

•   Source: SciCrunch Registry

http://www.rad.upenn.edu/sbia/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on June 2, 2023. Software package used to simulate brain images with local growth / atrophy within a prescribed spherical region. Specifically, given an input image and its segmented image, the location of the center of the spherical region, and the radius of that sphere, it simulates new images that have tissue growth or shrinkage within that pre-specified brain region according to given rates (atrophy for rates less than one and growth for rates greater than one). The algorithm uses an iterative procedure that tries to achieve the given level of volumetric change for brain tissues within the region, by seeking a smooth deformation field, whose Jacobian determinants match the prescribed volume change rate within the region. Note that in the current software, the simulation of growth or atrophy for brain tissue requires that the input spherical region has to cover some CSF or background regions.

Proper citation: Atrophy Simulation Package (RRID:SCR_006046) Copy   

•   Source: SciCrunch Registry

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

ART ''''acpcdetect'''' program for automatic detection of the AC and PC landmarks and the mid-sagittal plane on 3D structural MRI scans. ART ''''brainwash'''' program for automatic multi-atlas skull-stripping of 3D structural MRI scans. ART ''''3dwarper'''' program of non-linear inter-subject registration of 3D structural MRI scans. Software (art2) for linear rigid-body intra-subject inter-modality (MRI-PET) image registration. Data resource: The ART projects makes available corpus callosum segmentations of 316 normal subjects from the OASIS cross-sectional database. ART ''''yuki'''' program for fast, robust, and fully automatic segmentation of the corpus callosum on 3D structural MRI scans.

Proper citation: Automatic Registration Toolbox (RRID:SCR_005993) Copy   

•   Source: SciCrunch Registry

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

An end-to-end application allowing individual regional analysis of cortical thickness. This cross-platform tool can be run within Slicer3 as an external module, or directly as a command line. * Operating System: MacOS, Linux * Programming Language: C++ * Supported Data Format: ANALYZE, Nrrd, Other Format * build requires: Insight Toolkit

Proper citation: ARCTIC (RRID:SCR_005989) Copy   

•   Source: SciCrunch Registry

http://bioinformatics.biol.uoa.gr/human_gpdb/

A publicly accessible, relational database of human G-Proteins and their interactions with human GPCRs and Effectors. Advanced data integration techniques make Human-gpDB very rich in context since all of the bioentities are linked to a rich variety of external data sources. High quality visualization methods make the networks more informative and the extraction of information easier. Human-gpDB is currently a very useful tool for drug targeting investigation. The sequences of G-Proteins and GPCRs are classified according to a hierarchy of different classes, families and sub-families, whereas the Effectors sequences are classified in families, subfamilies and types, based on extensive literature search. The classification of GPCRs follows the IUPHAR classification, while the Effectors classification is a unique feature and is based on their function. The database currently holds information about 713 human GPCRs, 36 human G-Proteins and 99 human Effectors. The collection of the information about the interactions between these molecules was done manually and the current status of Human-gpDB reveals information about 1663 connections between GPCRs and G-Proteins and 1618 connections between G-Proteins and Effectors.

Proper citation: Human-gpDB (RRID:SCR_006223) Copy   

•   Source: SciCrunch Registry

https://www.braintest.org/brain_test/BrainTest

A portal of online studies that encourage community participation to tackle the most challenging problems in neuropsychiatry, including attention-deficit / hyperactivity disorder, schizophrenia, and bipolar disorder. Our approach is to engage the community and try to recruit tens of thousands of people to spend an hour of their time on our site. You folks will provide data in both brain tests and questionnaires, as well as DNA, and in return, we will provide some information about your brain and behavior. You will also be entered to win amazon.com gift cards. While large collaborative efforts were made in genetics in order to discover the secrets of the human genome, there are still many mysteries about the behaviors that are seen in complex neuropsychiatric syndromes and the underlying biology that gives rise to these behaviors. We know that it will require studying tens of thousands of people to begin to answer these questions. Having you, the public, as a research partner is the only way to achieve that kind of investment. This site will try to reach that goal, by combining high-throughput behavioral assessment using questionnaires and game-like cognitive tests. You provide the data and then we will provide information and feedback about why you should help us achieve our goals and how it benefits everyone in the world. We believe that through this online study, we can better understand memory and attention behaviors in the general population and their genetic basis, which will in turn allow us to better characterize how these behaviors go awry in people who suffer from mental illness. In the end, we hope this will provide better, more personalized treatment options, and ultimately prevention of these widespread and extremely debilitating brain diseases. We will use the data we collect to try to identify the genetic basis for memory and impulse control, for example. If we can achieve this goal, maybe we can then do more targeted research to understand how the biology goes awry in people who have problems with cognition, including memory and impulse control, like those diagnosed with ADHD, Schizophrenia, Bipolar Disorder, and Autism Spectrum Disorders. By participating in our research, you can learn about mental illness and health and help researchers tackle these complex problems. We can''t do it without your help.

Proper citation: Brain Test (RRID:SCR_006212) Copy   

•   Source: SciCrunch Registry