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http://www.callisto-science.org/NSI/Neuroscience_Image_Database/Images%20of%20the%20Human%20Nervous%20System%20-%20Disease%20&%20Injury.html

A collection of images of the human nervous system focusing on disease and injury.

Proper citation: Human Nervous System Disease and Injury (RRID:SCR_006370) Copy   

•   Source: SciCrunch Registry

http://www.shanoir.org/

An open source data sharing and visualization platform for neuroimaging data, that uses the OntoNeuroLOG ontology. Shanoir (Sharing NeurOImaging Resources) is an open source neuroinformatics platform designed to share, archive, search and visualize neuroimaging data. It provides a user-friendly secure web access and offers an intuitive workflow to facilitate the collecting and retrieving of neuroimaging data from multiple sources and a wizard to make the completion of metadata easy. Shanoir comes with many features such as anonymization of data, support for multicenter clinical studies on subjects or group of subjects. Shanoir offers an ontology-based data organization (OntoNeuroLOG). Among other things, this facilitates the reuse of data and metadata, the integration of processed data and provides traceability trough an evolutionary approach. Shanoir allows researchers, clinicians, PhD students and engineers to undertake quality research projects with an emphasis on remote collaboration. As a secured J2EE web application, it therefore allows you safely store and archive, with no more requirements than a computer with an internet connection. Furthermore, Shanoir is not only a web application: it is also a complete neuroinformatics platform in which you can easily integrate your existing processing tools or develop your own ones: see ShanoirTk. Shanoir is a project carried out by the VisAGeS Team, based at IRISA (INRIA Rennes - Bretagne Atlantique Research Centre). This software is released under QPL 1.0 license.

Proper citation: Shanoir (RRID:SCR_006286) Copy   

•   Source: SciCrunch Registry

http://aws.amazon.com/datasets

A multidisciplinary repository of public data sets such as the Human Genome and US Census data that can be seamlessly integrated into AWS cloud-based applications. AWS is hosting the public data sets at no charge for the community. Anyone can access these data sets from their Amazon Elastic Compute Cloud (Amazon EC2) instances and start computing on the data within minutes. Users can also leverage the entire AWS ecosystem and easily collaborate with other AWS users. If you have a public domain or non-proprietary data set that you think is useful and interesting to the AWS community, please submit a request and the AWS team will review your submission and get back to you. Typically the data sets in the repository are between 1 GB to 1 TB in size (based on the Amazon EBS volume limit), but they can work with you to host larger data sets as well. You must have the right to make the data freely available.

Proper citation: Amazon Web Services Public Data Sets (RRID:SCR_006318) Copy   

•   Source: SciCrunch Registry

http://www.hopkinsguides.com/

Authoritative, need-to-know information from Johns Hopkins available for mobile devices and the web. Guides provide up to date information and break down details of diagnosis, drug indications, dosing, pharmacokinetics, side effects and interactions, pathogens, management, and vaccines into frequently-updated, quick-read entries. Available for infectious disease (ABX), diabetes, and HIV.

Proper citation: Johns Hopkins Point of Care Guides (RRID:SCR_006314) Copy   

•   Source: SciCrunch Registry

http://www.patientcrossroads.com/

A trusted third-party gatekeeper of patient data from participants in a rare disease ecosystem, collecting and managing the information in a scalable, cost-effective manner. Each patient registry provides critical disease knowledge which makes that disease easier to study, increasing the probability a treatment can be developed. PatientCrossroads takes a network approach to patient registry programs. Unlike companies that merely sell registry software, we offer a full range of administration, management, and genetic curation services. What does this consolidated, patient-centric approach to patient registries mean? * Patients can more easily find registries and provide their valuable data (including locations of blood and tissue samples as well as reports of diagnoses, disease symptoms, treatment usage, and lifestyle activities) * Patients can be confident in the privacy of their de-identified data and the knowledge that PatientCrossroads does not sell patient data * Researchers and pharmaceutical companies have a larger, more easily accessible pool of potential patients for research studies and clinical trials targeting specific rare diseases * Pharmaceutical companies can collect post-market surveillance data in a more scalable and cost-effective manner * Rare disease advocacy and research foundations can more easily organize their global patient populations for inclusion in trials and studies

Proper citation: PatientCrossroads (RRID:SCR_006279) Copy   

•   Source: SciCrunch Registry

http://univ.cns.org/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on August 19,2021.Designed with the neurosurgeon in mind, this portal contains everything you need to acquire new skills and techniques, including courses, an image database, and the world''s largest neurosurgical wiki reference - NeuroWiki. The new University of Neurosurgery includes: * More than 40 new online courses - in all neurosurgical subspecialties. * Archived webinars. * Lectures from the CNS Annual Meetings. * Neurosurgical image database. We are continuing to add new content - check back often.

Proper citation: Congress of Neurological Surgeons University of Neurosurgery (RRID:SCR_006309) Copy   

•   Source: SciCrunch Registry

https://github.com/AndreMacedo88/VEnCode

Software tool to perform intersectional genetics-related operations to find VEnCodes using databases provided by FANTOM5 consortium, namely CAGE enhancer and transcription start site (TSS) databases.

Proper citation: VEnCode (RRID:SCR_018024) Copy   

•   Source: SciCrunch Registry

http://circadb.hogeneschlab.org/

Database of mammalian circadian gene expression profiles. Works with link outs to Wikipedia, HomoloGene, Refseq, etc.. Open source database of circadian transcriptional profiles from time course expression experiments from mice and humans.

Proper citation: CircaDB (RRID:SCR_018078) Copy   

•   Source: SciCrunch Registry

http://www.opencolleges.edu.au/informed/learning-strategies/

Interactive infographic of a brain exploring more than 100,000 chemical reactions, highlighted by areas and explanations of what that area is known to do.

Proper citation: Open Colleges Interactive Brain (RRID:SCR_001427) Copy   

•   Source: SciCrunch Registry

https://codr.c-path.org/

A repository of de-identified control arm data of patients from clinical studies of Alzheimer's disease and Mild Cognitive Impairment. It provides the ability to analyze the data online with the R statistical analysis program, create and download standard reports, run complex queries, or download data to a desktop for further analysis. Additional data will be added to the database over time. Critical Path Institute consortia members and qualified researchers may upload and work on scientific data relevant to biomarkers of drug toxicity, neurodegenerative diseases, and patient-reported outcomes.

Proper citation: CODR: C PATH On Line Data Repository (RRID:SCR_001388) Copy   

•   Source: SciCrunch Registry

https://repository.niddk.nih.gov/study/67

Clinical trial under the Urinary Incontinence Treatment Network to compare the treatment success for two surgical procedures that are frequently used and have similar cure rates, yet have not been compared directly to each other in a large, rigorously conducted randomized trial. The secondary aims of the trial are to compare other outcomes for the two surgical procedures, including quality of life, sexual function, satisfaction with treatment outcomes, complications, and need for other treatment(s) after surgery. Follow-up will be a minimum of two years and up to four years.

Proper citation: SISTEr (RRID:SCR_001542) Copy   

•   Source: SciCrunch Registry

https://github.com/vital-ai/vital-documentation/wiki/Vital-AI-Ontology

Ontology for the four consensus human vital signs: blood pressure, body temperature, respiration rate, pulse rate. It provides a controlled structured vocabulary for describing vital signs measurement data, the various processes of measuring vital signs, and the various devices and anatomical entities participating in such measurements.

Proper citation: Vital Signs Ontology (RRID:SCR_001422) Copy   

•   Source: SciCrunch Registry

http://talasso.cnb.csic.es/

Tool for quantification of human miRNA-mRNA Interactions. TaLasso is also available as Matlab or R code.

Proper citation: TaLasso (RRID:SCR_001726) Copy   

•   Source: SciCrunch Registry

https://github.com/Ensembl

Public database that stores areas of genome that differ between individual genomes (variants) and, where available, associated disease and phenotype information. Different types of variants for several species: single nucleotide polymorphisms (SNPs), short nucleotide insertions and/or deletions, and longer variants classified as structural variants (including CNVs). Effects of variants on the Ensembl transcripts and regulatory features for each species are predicted. You can run same analysis on your own data using Variant Effect Predictor. These data are integrated with other data sources in Ensembl, and can be accessed using the API or website. For several different species in Ensembl, they import variation data (SNPs, CNVs, allele frequencies, genotypes, etc) from a variety of sources (e.g. dbSNP). Imported variants and alleles are subjected to quality control process to flag suspect data. In human, they calculate linkage disequilibrium for each variant, by population.

Proper citation: Ensembl Variation (RRID:SCR_001630) Copy   

•   Source: SciCrunch Registry

http://ancora.genereg.net/

Web resource that provides data and tools for exploring genomic organization of highly conserved noncoding elements (HCNEs) for multiple genomes. It includes a genome browser that shows HCNE locations and features novel HCNE density plots as a powerful tool to discover developmental regulatory genes and distinguish their regulatory elements and domains. They identify HCNEs as non-exonic regions of high similarity between genome sequences from distantly related organisms, such as human and fish, and provide tools for studying the distribution of HCNEs along chromosomes. Major peaks of HCNE density along chromosomes most often coincide with developmental regulatory genes. Their aim with this site is to aid discovery of developmental regulatory genes, their regulatory domains and their fundamental regulatory elements.

Proper citation: Ancora (RRID:SCR_001623) Copy   

•   Source: SciCrunch Registry

https://www.uniklinik-freiburg.de/mr-en/research-groups/diffperf/fibertools.html

Implemented under MATLAB, this DTI image processing toolbox provides import-filters for several MR file standards, a processing unit to calculate the diffusion tensors; several GUI based tools to calculate fiber tracks and to evaluate the DTI dataset. The results can be filed as images with 3D impression or can be logged in formatted ASCII files. Tools and features: * DTI Processing Unit: Calculates the diffusion tensors and their eigenvalues and eigenvectors. Different file formats are supported (like DICOM, Bruker, binary files, Matlab structures). The standard SIEMENS and GE diffusion encoding schemes are supported; other schemes have to be defined in a separate text, .m or .mat file. * FiberTracking: ** Fiber tracking is realized by using the FACT algorithm (Mori et al., Annal. Neurol 1999). ** Probabilistic tracking realized by using the PiCo (Parker et al., JMRI 2003) approach but with DTI data as basis. It is possible to extract pathways between two seeds by combining two maps (Kreher et al., NeuroImage 2008). ** Global Fiber Tracking on basis of HARDI or DTI data. The method is based on the approach reported in (Marco Reisert et al: Global fiber reconstruction becomes practical. NeuroImage 54(2):955-62) * FiberViewer: ** Visualization and Navigation through different data modalities like DTI maps, fiber tracks, diffusion main directions. ** Supports different kinds of DTI maps (e.g. FA, Trace, lambda images ) ** Creation and manipulation of mask based ROIs. ** Selection of streamline fibers ** Visualization of probabilistic fiber tracking results ** Documentation by logging statistics of ROIs and fiber tracks into text files. ** Import/Export from/to ANALYZE or Nifti * 3D Visualizer: Visualization of map slices, ROIs, and fiber tracks with 3D impression. * Batch Editor: Automatic processing of high amounts of data. Possibility to link processing with SPM8 easily.

Proper citation: DTI and Fibertools Software Package (RRID:SCR_001641) Copy   

•   Source: SciCrunch Registry

http://www.oege.org/

Portal for researchers to locate information relevant to interpretation and follow-up of human genetic epidemiological discoveries, including: a range of population and case and family genetic epidemiological studies, relevant gene and sequence databases, genetic variation databases, trait measurement, resource labs, journals, software, general information, disease genes and genetic diversity.

Proper citation: Online Encyclopedia for Genetic Epidemiology studies (RRID:SCR_001825) Copy   

•   Source: SciCrunch Registry

http://www.PDtrials.org

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 23, 2016. A collaborative initiative of Parkinson's organizations dedicated to increasing education and awareness about clinical research. PDtrials provides up-to-date information on Parkinson's disease trials currently enrolling participants in the U.S. and Canada, as well as information about Parkinson's studies for people living with PD, their families and caregivers. Researchers can list their own trials on the PDtrials website. Patients can browse trial listings by type, location, symptom, or keyword.

Proper citation: PDtrials- Parkinsons Disease Clinical Trials (RRID:SCR_002027) Copy   

•   Source: SciCrunch Registry

http://www.worldpdcongress.org

A nonprofit organization dedicated to providing an international forum for the latest scientific discoveries, medical practices and caregiver initiatives related to Parkinson's disease. It hosts the annual World Parkinson Congress, an event which focuses on bringing physicians, scientists, allied health professionals, caregivers and people diagnosed with Parkinson's disease together, in order to create a global dialogue that will help expedite treatment practices and the discovery of a cure .

Proper citation: World Parkinson Congress (RRID:SCR_002034) Copy   

•   Source: SciCrunch Registry

http://www.wpda.org

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 23, 2016. The World Parkinson's Disease Association is an alliance of members from all over the world who have come together to share information about Parkinson's disease. In order to further Parkinson's research and better the condition of those diagnosed with the disease, the Association: establishes computerized connections; takes part in and/or finances research activities; urges pharmaceutical companies and government institutions of the various countries to support the guidelines recommended by the associations of Parkinson's patients; and coordinates and promotes interchange of information among its members with the aim of solving problems of mutual interest.

Proper citation: World Parkinson Disease Association (RRID:SCR_002035) Copy   

•   Source: SciCrunch Registry