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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://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   

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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   

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http://oligogenome.stanford.edu/

The Stanford Human OligoGenome Project hosts a database of capture oligonucleotides for conducting high-throughput targeted resequencing of the human genome. This set of capture oligonucleotides covers over 92% of the human genome for build 37 / hg19 and over 99% of the coding regions defined by the Consensus Coding Sequence (CCDS). The capture reaction uses a highly multiplexed approach for selectively circularizing and capturing multiple genomic regions using the in-solution method developed in Natsoulis et al, PLoS One 2011. Combined pools of capture oligonucleotides selectively circularize the genomic DNA target, followed by specific PCR amplification of regions of interest using a universal primer pair common to all of the capture oligonucleotides. Unlike multiplexed PCR methods, selective genomic circularization is capable of efficiently amplifying hundreds of genomic regions simultaneously in multiplex without requiring extensive PCR optimization or producing unwanted side reaction products. Benefits of the selective genomic circularization method are the relative robustness of the technique and low costs of synthesizing standard capture oligonucleotide for selecting genomic targets.

Proper citation: OligoGenome (RRID:SCR_006025) Copy   

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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   

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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://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://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://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://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.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://www.dystonia-parkinsons.org

A nonprofit organization whose goal is to find better treatments and cures for the movement disorders dystonia and Parkinson's disease. Funding opportunities are available through the collaborative research program between BSDPF and the Michael J. Fox Foundation.

Proper citation: BSDPF (RRID:SCR_001162) Copy   

•   Source: SciCrunch Registry

https://services.healthtech.dtu.dk/services/NetNGlyc-1.0/

Server that predicts N-Glycosylation sites in human proteins using artificial neural networks that examine the sequence context of Asn-Xaa-Ser/Thr sequons. NetNGlyc 1.0 is also available as a stand-alone software package, with the same functionality as the service above. Ready-to-ship packages exist for the most common UNIX platforms.

Proper citation: NetNGlyc (RRID:SCR_001570) Copy   

•   Source: SciCrunch Registry

http://cellfinder.de/about/ontology/

Structured vocabulary to organize cell-associated data and to place these data in clearly defined semantic relations to other biological facts. It describes cell types, their properties and origin and links this information to other existing ontologies like the Cell Ontology (CL), Foundational Model of Anatomy (FMA), Gene Ontology (GO), Mouse Anatomy and others using the top-level ontology BioTop.

Proper citation: CELDA Ontology (RRID:SCR_001601) Copy   

•   Source: SciCrunch Registry

http://tvmouse.ucdavis.edu/anatomy/

Access to Quicktime movies of histologic mouse anatomy including heart / lung, kidney, mammary gland, lymph node, prostate, spleen, liver, salivary glands, and 3-D wire model based on MRI sections; a Quicktime mouse radiographic atlas of skeletal anatomy containing a series of radiographic images with color overlays and labels; and a table containing a comparison between mouse and human anatomy. Special topics include the virtual necroscopy. Anatomic systems cover the central nervous system, male genital-urinary tract, female genital-urinary tract, mammary, kidney, skeletal, cardiovascular, gastrointestinal, and respiratory systems. The pathology and imaging section includes anatomy, histology, comparative imaging, physiology, pathology, comparative mammary, comparative prostate, GEM, and an image archive. These pages were put together as a pilot demonstration by Dr. Robert Cardiff, UCD Center for Comparative Medicine with the collaboration of Dr. Michael Paulus, Oak Ridge National Laboratories,MicroCat Group, Dr. Allan Johnson, Duke University Center for In Vivo Microscopy, and Drs. Steve Griffey, Gary Henderson and Tom Jue, University of California, Davis. This is a work in progress and for demonstration purposes.

Proper citation: Visible Mouse Anatomy (RRID:SCR_001603) Copy   

•   Source: SciCrunch Registry

https://ftp.bigbrainproject.org/

Ultrahigh resolution 3D human brain model at nearly cellular resolution of 20 micrometers, based on reconstruction of histological sections. Provides considerable neuroanatomical insight into human brain, thereby allowing extraction of microscopic data for modeling and simulation. Enables testing of hypotheses on optimal path lengths between interconnected cortical regions or on spatial organization of genetic patterning, redefining traditional neuroanatomy maps such as those of Brodmann and von Economo.

Proper citation: BigBrain (RRID:SCR_001593) Copy   

•   Source: SciCrunch Registry

http://library.med.utah.edu/kw/hyperbrain/

An online tutorial for human neuroanatomy designed as a supplement to textbook and class learning or as a lab substitute when human specimens, slides and models are not available. HyperBrain includes thousand of images and hundreds of linked illustrated glossary terms, as well as movies, quizzes and interactive animations. Last updated 2012.

Proper citation: HyperBrain (RRID:SCR_001595) Copy   

•   Source: SciCrunch Registry

https://dpcpsi.nih.gov/onr/nrcc

Coordinates nutritional sciences-related research and research training across the National Institutes of Health (NIH) and among Federal Agencies by providing mechanisms to communicate research, research training, policy, and education initiatives. The DNRC facilitates the exchange of information, coordinates workshops and seminars on critical issues, encourages national and international research collaborations, and serves as the NIH primary point of contact for the Department of Health and Human Services (DHHS) and other agencies, departments, and organizations in matters pertaining to nutritional sciences and physical activity. Through its dedicated efforts to promote scientific policy reviews, innovative research, interagency collaboration, and technical advancements, the DNRC strives to define the increasing roles of nutritional sciences and physical activity in health promotion and disease prevention and treatment.

Proper citation: NIH Division of Nutrition Research Coordination (RRID:SCR_001469) Copy   

•   Source: SciCrunch Registry