The next VBL will have place on the 12th of May at the J. Ellis LT – Royal London Hospital.
The speaker will be Karim Chine and the topic is
“Cloud Computing for Bioinformatics”
“Cloud computing for bioinformatic”
Cloud Computing represents a new way to deploy computing technology in which dynamically scalable and virtualized resources are provided as a service over the Internet. Amazon Elastic Cloud (EC2) is an example of ‘Infrastructure as a Service’ that anyone can use today to access infinite computing capacity on demand within a sustainable environment that enables collaboration, resource sharing and provides the tools for traceable and reproducible computational research. This model of allocating processing power holds the promise of a revolution in scientific and statistical computing. However, bringing new era for research and education still requires new software that bridges the gap between the scientist’s everyday tools and the cloud. The R statistical tool is a case in point, it is a free, application that attracts considerable use and method development in bioinformatics and genetics. It often requires significant memory resources and computing power but it still can’t be used on the cloud except but computer savvies. Elastic–R (http://www.elasticr.net) is a Google docs-like portal and workbench for data analysis that makes using R on the cloud even simpler than using it locally. without requiring dedicated knowledge of the cloud itself, It enables statisticians, computational scientists, educators and students to use cloud resources; to work with R engines and use their full capabilities from within any standard web browser; to collaborate, share and reuse functions, algorithms, spreadsheets, user interfaces, R sessions, servers; and to perform elastic distributed computing with any number of virtual machines to solve compute-intensive problems. Elastic-R is also an applications’ platform which allows anyone to assemble statistical methods and data on the server (remote machine) and to visually create and publish interactive user interfaces and dashboards exposing those methods and data.
The attendees will learn how to:
* run Elastic-R Amazon Machine Images (AMIs), and access them through the portal.
* work with virtual R sessions within the browser; use the Browser-R-Bench’s views and the Elastic-R Plugins Toolset.
* upload/download files to/from an Elastic-R AMI; work with R-Spreadsheets from within the browser.
* share an Elastic-R AMI with other portal users; use the different collaboration capabilities (broadcasted consoles/graphics, interactive graphics annotators, slide viewer, files sharing, etc).
* mirror R-Spreadsheets to Excel spreadsheets; use them collaboratively.
* create User Interfaces for R functions using either the Netbeans GUI Builder or the Elastic-R code-free GUI Designer; make the created GUIs available with simple URLs.
* expose the Elastic-R session as a web service; use the Restful-R API.
* perform parallel computing in R using multiple Elastic-R AMIs.
Project’s web site : http://www.elasticr.net/platform
Map and details on