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http://openconnectomeproject.org/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 9, 2023. Connectomes repository to facilitate the analysis of connectome data by providing a unified front for connectomics research. With a focus on Electron Microscopy (EM) data and various forms of Magnetic Resonance (MR) data, the project aims to make state-of-the-art neuroscience open to anybody with computer access, regardless of knowledge, training, background, etc. Open science means open to view, play, analyze, contribute, anything. Access to high resolution neuroanatomical images that can be used to explore connectomes and programmatic access to this data for human and machine annotation are provided, with a long-term goal of reconstructing the neural circuits comprising an entire brain. This project aims to bring the most state-of-the-art scientific data in the world to the hands of anybody with internet access, so collectively, we can begin to unravel connectomes. Services: * Data Hosting - Their Bruster (brain-cluster) is large enough to store nearly any modern connectome data set. Contact them to make your data available to others for any purpose, including gaining access to state-of-the-art analysis and machine vision pipelines. * Web Viewing - Collaborative Annotation Toolkit for Massive Amounts of Image Data (CATMAID) is designed to navigate, share and collaboratively annotate massive image data sets of biological specimens. The interface is inspired by Google Maps, enhanced to allow the exploration of 3D image data. View the fork of the code or go directly to view the data. * Volume Cutout Service - RESTful API that enables you to select any arbitrary volume of the 3d database (3ddb), and receive a link to download an HDF5 file (for matlab, C, C++, or C#) or a NumPy pickle (for python). Use some other programming language? Just let them know. * Annotation Database - Spatially co-registered volumetric annotations are compactly stored for efficient queries such as: find all synapses, or which neurons synapse onto this one. Create your own annotations or browse others. *Sample Downloads - In addition to being able to select arbitrary downloads from the datasets, they have also collected a few choice volumes of interest. * Volume Viewer - A web and GPU enabled stand-alone app for viewing volumes at arbitrary cutting planes and zoom levels. The code and program can be downloaded. * Machine Vision Pipeline - They are building a machine vision pipeline that pulls volumes from the 3ddb and outputs neural circuits. - a work in progress. As soon as we have a stable version, it will be released. * Mr. Cap - The Magnetic Resonance Connectome Automated Pipeline (Mr. Cap) is built on JIST/MIPAV for high-throughput estimation of connectomes from diffusion and structural imaging data. * Graph Invariant Computation - Upload your graphs or streamlines, and download some invariants. * iPad App - WholeSlide is an iPad app that accesses utilizes our open data and API to serve images on the go.

Proper citation: Open Connectome Project (RRID:SCR_004232) Copy   

•   Source: SciCrunch Registry

http://www.cori.org/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on December 5, 2022. Endoscopic Reporting Software, aggregated and individual research data and tailor-made services aimed to advance the overall practice of endoscopy. It was developed to study outcomes of gastrointestinal (GI) endoscopic procedures in real life settings, using data obtained from the CORI Endoscopic Reporting Software or from other endoscopic reporting software. Practice sites include hospitals, ambulatory care centers, private practices, universities, and Veteran''''s hospitals (VA''''s). The CORI v4 Endoscopic Reporting Software is a specialty Electronic Health Record used to document endoscopic procedures and provide reporting services to your practice. Data from participating providers is also sent to a central data repository to become part of the National Endoscopic Database (NED), which now contains data from over 2.7 million GI procedures. The CORI v4 Endoscopic Reporting Software offers significant benefits for participating practices, providers and patients, as well as for everyone who benefits from CORI''''s research efforts. You may actively participate in research with CORI. If you have ideas for research using the NED, their research team can help you evaluate those ideas, collect and analyze the data. In addition, you may choose to participate in one of the prospective research projects conducted by CORI research staff.

Proper citation: Clinical Outcomes Research Initiative (RRID:SCR_009010) Copy   

•   Source: SciCrunch Registry

http://rgd.mcw.edu/rgdCuration/?module=portal&func=show&name=renal

An integrated resource for information on genes, QTLs and strains associated with a variety of kidney and renal system conditions such as Renal Hypertension, Polycystic Kidney Disease and Renal Insufficiency, as well as Kidney Neoplasms.

Proper citation: Renal Disease Portal (RRID:SCR_009030) Copy   

•   Source: SciCrunch Registry

https://portal.dbmi.hms.harvard.edu/projects/GRDR/

Data repository of de-identified patient data, aggregated in a standardized manner, to enable analyses across many rare diseases and to facilitate various research projects, clinical studies, and clinical trials. The aim is to facilitate drug and therapeutics development, and to improve the quality of life for the many millions of people who are suffering from rare diseases. The goal of GRDR is to enable analyses of data across many rare diseases and to facilitate clinical trials and other studies. During the two-year pilot program, a web-based template will be developed to allow any patient organization to establish a rare disease patient registry. At the conclusion of the program, guidance will be available to patient groups to establish a registry and to contribute de-identified patient data to the GRDR repository. A Request for Information (RFI) was released on February 10, 2012 requesting information from patient groups about their interest in participating in a GRDR pilot project. ORDR selected 30 patient organizations to participate in this pilot program to test the different functionalities of the GRDR. Fifteen (15) organizations with established registries and 15 organizations that do not have patient registry. The 15 patient groups, each without a registry, were selected to assist in testing the implementation of the ORDR Common Data Elements (CDEs) in the newly developed registry infrastructure. These organizations will participate in the development and promotion of a new patient registry for their rare disease. The GRDR program will fund the development and hosting of the registry during the pilot program. Thereafter, the patient registry is expected to be self-sustaining.The 15 established patient registries were selected to integrate their de-identified data into the GRDR to evaluate the data mapping and data import/export processes. The GRDR team will assist these organizations in mapping their existing registry data to the CDEs. Participating registries must have a means to export their de-identified registry data into a specified data format that will facilitate loading the data into the GRDR repository on a regular basis. The GRDR will also develop the capability to link patients'''' data and medical information to donated biospecimens by using a Voluntary Global Unique Patient Identifier (GUID). The identifier will enable the creation of an interface between the patient registries that are linked to biorepositories and the Rare Disease Human Biospecimens/Biorepositories (RD-HUB) http://biospecimens.ordr.info.nih.gov/.

Proper citation: GRDR (RRID:SCR_008978) Copy   

•   Source: SciCrunch Registry

http://invizian.loni.usc.edu

A visualization environment that enables you, via your computer, to display and interact with hundreds of neuroimaging data sets at once ?bringing together brain image data from some of the world?s best neuroscience research teams. INVIZIAN empowers both researchers and students of neuroscience to explore and understand the human brain using a simple yet powerful user interface for neuroimaging data exploration and discovery. See a beautiful example of a cloud of individual brains tumbling around in the INVIZIAN interface in Vimeo (http://vimeo.com/67984681). Visit often to see how we are making continuing progress to make Invizian even more amazing.

Proper citation: INVIZIAN (RRID:SCR_009549) Copy   

•   Source: SciCrunch Registry

http://www.jst.go.jp/csc/virtual/find/mindlab/english/base.html

Interactive laboratory of the mind composed of 4 themed sessions housing four short introductory movies and sixteen trials with those you can experience visual phenomena and illusions used for study in psychological experiments.

Proper citation: Mind Lab (RRID:SCR_009025) Copy   

•   Source: SciCrunch Registry

http://ageing-map.org/

Database of age-related changes covering different biological levels, including molecular, physiological, psychological and pathological age-related data, to create an interactive portal that serves as a centralized collection of human aging changes and pathologies. To facilitate integrative, system-level studies of aging, the DAA provides a centralized source for aging-related data as well as basic tools to query and visualize the data, including anatomical models. Data in the DAA is manually curated from the literature and retrieved from public databases. For more detailed analyses users are able to download the entire database. More information on how to use the DAA is available on the help page. The DAA primarily focuses on human aging, but also includes supplementary mouse data, in particular gene expression data, to enhance and expand the information on human aging. If you would like to contribute to the database yourself, for instance if you have new data on aging, please use the contribute page to submit your data.

Proper citation: Digital Ageing Atlas (RRID:SCR_009020) Copy   

•   Source: SciCrunch Registry

http://purl.bioontology.org/ontology/BNO

Ontology that relates concepts and terminologies used for human nutrition in a clinical and biomedical setting.

Proper citation: Bionutrition Ontology (RRID:SCR_010272) Copy   

•   Source: SciCrunch Registry

http://purl.bioontology.org/ontology/ONSTR

Application ontology covering the domain of newborn screening, follow-up and translational research pertaining to patients diagnosed with inheritable and congenital diseases mainly identified through newborn dried blood spot screening. ONSTR is a central component of the project Newborn Screening Follow-up Data Integration Collaborative (NBSDC), https://nbsdc.org. ONSTR uses the Basic Formal Ontology v2 (BFO2, v2012-07-20) as top-level ontology and extends the classes imported from OBO Foundry ontologies and candidate ontologies.

Proper citation: Ontology for Newborn Screening Follow-up and Translational Research (RRID:SCR_010389) Copy   

•   Source: SciCrunch Registry

http://purl.bioontology.org/ontology/PEDTERM

Terms associated with pediatrics, representing information related to child health and development from pre-birth through 21 years of age; contributed by the National Institute of Child Health and Human Development.

Proper citation: Pediatric Terminology (RRID:SCR_010395) Copy   

•   Source: SciCrunch Registry

http://purl.bioontology.org/ontology/TM-CONST

Ontology of the value set for the constitution property of the International Classification of Traditional Medicine (ICTM).

Proper citation: Traditional Medicine Constitution Value Set (RRID:SCR_010435) Copy   

•   Source: SciCrunch Registry

http://www.mssm.edu/research/programs/manhattan-hiv-brain-bank/

Biorepository of tissues and fluids relevant for the neurologic, neuropsychologic, psychiatric and neuropathologic manifestations of HIV infection, linked to medical records and an on-going clinical trial for research use by the scientific community. The MHBB conducts a longitudinal, observational study that follows a group of HIV-infected individuals who have agreed to be fluid and organ donors for the purposes of AIDS research. They are currently the largest, multidisciplinary neuroAIDS cohort in New York City, the epicenter of the US HIV epidemic. Research participants undergo regular neurologic, neuropsychologic, and psychiatric evaluations, and provide body fluid samples that are linked to clinical information. Upon their demise, study participants become organ donors. This program has supplied clinical information, tissue, and fluid samples to over 70 qualified AIDS researchers across America, Europe and Australia. In fulfilling its resource mission, the MHBB functions as part of the National NeuroAIDS Tissue Consortium (NNTC). MHBB provides a means by which people living with HIV can be engaged in the struggle to improve our knowledge about HIV infection and the damage it causes to the body.

Proper citation: Manhattan HIV Brain Bank (RRID:SCR_010520) Copy   

•   Source: SciCrunch Registry

http://purl.bioontology.org/ontology/PDO

An ontology for describing both human infectious disease caused by bacteria and the disease that is related to bacterial infection.

Proper citation: Pathogenic Disease Ontology (RRID:SCR_010405) Copy   

•   Source: SciCrunch Registry

http://purl.bioontology.org/ontology/OMIT

Ontology to establish data exchange standards and common data elements in the microRNA (miR) domain. Biologists (cell biologists in particular) and bioinformaticians can make use of OMIT to leverage emerging semantic technologies in knowledge acquisition and discovery for more effective identification of important roles performed by miRs in humans'' various diseases and biological processes (usually through miRs'' respective target genes). OMIT has reused and extended a set of well-established concepts from existing bio-ontologies, e.g., Gene Ontology, Sequence Ontology, Protein Ontology, NCBI Organism Taxonomy, Human Disease Ontology, Foundational Model of Anatomy, and so forth.

Proper citation: Ontology for MicroRNA Target Prediction (RRID:SCR_010387) Copy   

•   Source: SciCrunch Registry

http://databrary.org/

Project aims to promote data sharing, archiving, and reuse among researchers who study human development. Focuses on creating tools for scientists to store, manage, preserve, analyze and share video and related data.

Proper citation: Databrary (RRID:SCR_010471) Copy   

•   Source: SciCrunch Registry

http://purl.bioontology.org/ontology/MHC

Ontology that contains terms necessary for describing and categorizing concepts related to Major Histocompatibility Complex, in general, for a number of model species, and also for humans.

Proper citation: Major Histocompatibility Complex Ontology (RRID:SCR_010354) Copy   

•   Source: SciCrunch Registry

http://www.bu.edu/alzresearch/index.html

The goal of the Alzheimers Disease Center is to help reduce the human and economic costs associated with Alzheimers disease through the advancement of knowledge. The primary missions of the Center are to: conduct and facilitate cutting-edge Alzheimers disease research; enhance clinical care for Alzheimers disease patients and their families; and provide education regarding Alzheimers disease to both professional and lay audiences. The Center is made up of a multidisciplinary group of professionals dedicated to research, clinical care, and education.

Proper citation: Boston University Alzheimer's Disease Center (RRID:SCR_010692) Copy   

•   Source: SciCrunch Registry

http://mirtar.mbc.nctu.edu.tw/human/

An integrated web server for identifying miRNA-target interactions in human. The tool enables biologists easily to identify the biological functions and regulatory relationships between a group of known/putative miRNAs and protein coding genes. It also provides perspective of information on the miRNA targets on alternatively spliced transcripts.

Proper citation: miRTar (RRID:SCR_010851) Copy   

•   Source: SciCrunch Registry

http://uberon.org

An integrated cross-species anatomy ontology representing a variety of entities classified according to traditional anatomical criteria such as structure, function and developmental lineage. The ontology includes comprehensive relationships to taxon-specific anatomical ontologies, allowing integration of functional, phenotype and expression data. Uberon consists of over 10000 classes (March 2014) representing structures that are shared across a variety of metazoans. The majority of these classes are chordate specific, and there is large bias towards model organisms and human.

Proper citation: UBERON (RRID:SCR_010668) Copy   

•   Source: SciCrunch Registry

http://compgenomics.utsa.edu/gene/gene_1.php

A Bayesian decision fusion algorithm for microRNA target prediction that combines the prediction of TargetScan, miRanda, PicTar, mirTarget, PITA, and DianamicroT. Users enter a Ref_seq ID for a query target gene and select a miRNA, which BCmicrO will use in its predictive algorithm. The prediction results can then be downloaded.

Proper citation: BCmicrO (RRID:SCR_010838) Copy   

•   Source: SciCrunch Registry