Welcome to the CBIIT Speaker Series Wiki
PhenoDB is a web-based tool developed for the collection, storage and analysis of phenotype data, as well as interpretation of exome and genome data in the context of phenotype data. It has it own taxonomy and links to OMIM for disease terms. There is a single center version that allow identifiers and includes only the phenotype and analysis module (http://phenodb.org) and a tool for larger studies that also includes a sample module and an ELSI module for storage and review of consents (http://researchphenodb.net). Both are freely available for download; http://phenodb.org can be used by individual users to try it out (it is toggled to have only deidentified data). PhenoDB has been in use for the Baylor-Hopkins Center for Mendelian Genomics since March 2012 and holds information on over 5000 individuals from ~3000 families. It has proved efficient and effective in novel disease gene discovery. It can also be used for a laboratory or clinic.
This presentation will cover current status of the SEER program and review opportunities for use of the data in support of cancer research as it currently exists. It will identify and discuss challenges in more comprehensive data collection and how these are being addressed through new initiatives that will enhance the capacity of the registries to support research in a contemporary research setting.
This talk will describe how science is changing as a result of the vast amounts of data we are collecting from gene sequencers to telescopes and supercomputers. This “Fourth Paradigm of Science,” predicted by Jim Gray, is moving at full speed, and is transforming one scientific area after another. The talk will present various examples on the similarities of the emerging new challenges and how Jim Gray’s vision is realized by the scientific community. Scientists are increasingly limited by their ability to analyze the large amounts of complex data available. These data sets are generated not only by instruments but also computational experiments; the sizes of the largest numerical simulations are on par with data collected by instruments, crossing the petabyte threshold this year. The importance of large synthetic data sets is increasingly important, as scientists compare their experiments to reference simulations. All disciplines need a new “instrument for data” that can deal not only with large data sets but the cross product of large and diverse data sets. There are several multi-faceted challenges related to this conversion, e.g., how to move, visualize, analyze, and in general interact with petabytes of data.
The HUBzero platform offers unique features to support collaboration among researchers, among them the deployment of computational tools and the dissemination of scientific resources. A fundamental need for collaborative research projects is the collection, sharing and exploration of data. This presentation describes the Hub-based "data technologies" which are designed to provide interactive, web-based data sharing and have been used to create more than 40 medical and scientific research databases across 10 Hubs. We will present examples that demonstrate how Hub databases connect and serve communities across the globe – with data contribution facilities to store and preserve valuable research data, and powerful feature-rich data exploration facilities to search, navigate, drill-down, link, filter, export and analyze data. Research communities are well served by HUBzero, which unites data, tools and collaborative technologies on a single web-based platform.
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