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on page 1 showing 6 out of 6 results


Cite this (BraVa, RRID:SCR_001407)


Resource Type: Resource, data or information resource, database

A database of digital reconstructions of the human brain arterial arborizations from 61 healthy adult subjects along with extracted morphological measurements. The arterial arborizations include the six major trees stemming from the circle of Willis, namely: the left and right Anterior Cerebral Arteries (ACAs), Middle Cerebral Arteries (MCAs), and Posterior Cerebral Arteries (PCAs).

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Cite this (Cardiovascular Model Repository, RRID:SCR_002679)


Resource Type: Resource, image collection, data set, service resource, storage service resource, data repository, data or information resource

Repository of geometric models collected from on-going and past research projects in the Cardiovascular Biomechanics Research Laboratory at Stanford University. The geometric models are mostly built from imaging data of healthy and diseased individuals. For each of the models, a short description is given with a reference. The geometric models are in VTK PolyData XML .vtp format. * Audience: Biomechanical and computational researchers interested in complex models of cardiovascular applications * Long Term Goals and Related Uses: Allow users to download geometric models for cardiovascular applications. These geometric models can be used for research purposes, such as meshing and scientific visualization. Users are welcome to contact the project administrator, join the project and contribute additional models.

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Cite this (HipSci, RRID:SCR_003909)


Resource Type: Resource, production service resource, biomaterial supply resource, material service resource, data set, service resource, cell repository, material resource, biomaterial manufacture, data or information resource

A UK national induced pluripotent stem (iPS) cell resource that will create and characterize more than 1000 human iPSCs from healthy and diseased tissue for use in cellular genetic studies. Between 2013 and 2016 they aim to generate iPS cells from over 500 healthy individuals and 500 individuals with genetic disease. They will then use these cells to discover how genomic variation impacts on cellular phenotype and identify new disease mechanisms. Strong links with NHS investigators will ensure that studies on the disease-associated cell lines will be linked to extensive clinical information. Further key features of the project are an open access model of data sharing; engagement of the wider clinical genetics community in selecting patient samples; and provision of dedicated laboratory space for collaborative cell phenotyping and differentiation.

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Cite this (Nephromine, RRID:SCR_003813)


Resource Type: Resource, data or information resource, database

A growing database of publicly available renal gene expression profiles, a sophisticated analysis engine, and a powerful web application designed for data mining and visualization of gene expression. It provides unique access to datasets from the Personalized Molecular Nephrology Research Laboratory incorporating clinical data which is often difficult to collect from public sources and mouse data.

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Cite this (Physiobank, RRID:SCR_006949)


Resource Type: Resource, database, catalog, service resource, storage service resource, data repository, data or information resource

Archive of well-characterized digital recordings of physiologic signals and related data for use by the biomedical research community. PhysioBank currently includes databases of multi-parameter cardiopulmonary, neural, and other biomedical signals from healthy subjects and patients with a variety of conditions with major public health implications, including sudden cardiac death, congestive heart failure, epilepsy, gait disorders, sleep apnea, and aging. The PhysioBank Archives now contain over 700 gigabytes of data that may be freely downloaded. PhysioNet is seeking contributions of data sets that can be made freely available in PhysioBank. Contributions of digitized and anonymized (deidentified) physiologic signals and time series of all types are welcome. If you have a data set that may be suitable, please review PhysioNet''s guidelines for contributors and contact them.

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Cite this (Scripps Wellderly Genome Reference, RRID:SCR_010250)


Resource Type: Resource, data set, data or information resource

Whole genome sequencing data for 454 unrelated Scripps Wellderly Study participants with European ancestry from a project that is studying the genetic architecture of exceptional healthspan from a cohort comprised of more than 1300 healthy individuals over the age of 80 years. SWGR_v1.0 includes chromosome-specific VCF4.1 bgzipped and tabix indexed files. Annotations for each variant can be found at Scripps Genome ADVISER (SG-ADVISER, Additional data releases are expected.

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