Navigation Links
Petascale computational tools could revolutionize understanding of genomic evolution
Date:11/17/2009

Technological advances in DNA sequencing make determining how living things are related possible by analyzing the ways in which their genes have been rearranged on chromosomes. However, inferring these evolutionary relationships from rearrangement events requires massive computing impossible even on the most advanced computing systems available today.

A four-year $1 million project, funded by the National Science Foundation's PetaApps program, aims to develop computational tools that will use next-generation petascale computers to understand genomic evolution. A team of universities received the grant, including the Georgia Institute of Technology, the University of South Carolina and Penn State. The funding is part of the American Recovery and Reinvestment Act.

"Genome sequences are now available for many organisms, but making biological sense of the genomic data requires high-performance computing methods and an evolutionary perspective, whether you are trying to understand how genes of new functions arise, why genes are organized as they are in chromosomes, or why these arrangements are subject to change," said lead investigator David A. Bader, professor, Computational Science and Engineering Division, Georgia Tech's College of Computing.

Even on today's fastest parallel computers, it could take centuries to analyze genome rearrangements for large, complex organisms. So, the research team -- which also includes Jijun Tang, associate professor, department of computer science and engineering, University of South Carolina, and Stephen Schaeffer, associate professor of biology, Penn State -- is focusing on future generations of petascale machines, which will be able to process more than a thousand trillion calculations per second. Today, most personal computers can only process a few hundred thousand calculations per second.

The researchers plan to develop new algorithms in an open-source software framework that will use the capabilities of parallel, petascale computing platforms to infer ancestral rearrangement events. The starting point to develop these new algorithms will be GRAPPA, an open-source code co-developed by Bader and initially released in 2000 that reconstructed the evolutionary relatedness among species.

The researchers will test the performance of their new algorithms by analyzing a collection of fruit fly genomes.

"Fruit flies -- formally known as Drosophila -- are an excellent model system for studying genome rearrangement because the genome sizes are relatively small for animals, the mechanism that alters gene order is reasonably well understood and the evolutionary relationships among the 12 sequenced genomes are known," said Schaeffer.

The analysis of genome rearrangements in Drosophila will provide a relatively simple system to understand the mechanisms that underlie gene order diversity, which can later be extended to more complex mammalian genomes, such as primates.


'/>"/>

Contact: A'ndrea Elyse Messer
aem1@psu.edu
814-865-9481
Penn State
Source:Eurekalert

Related biology news :

1. Petascale computing tools could provide deeper insight into genomic evolution
2. Petascale climate modeling heats up at University of Miami
3. Symposium marks 20th anniversary of Theoretical and Computational Biophysics Group
4. 7th annual [BC]2 Basel Computational Biology Conference Molecular Evolution June 18-19, 2009
5. Computational model examines the pathways of Alzheimers that strikes at the young
6. Computational model examines the pathways of Alzheimers that strikes at the young
7. 7th [BC]2 Basel Computational Biology Conference
8. Oxford Journals and the International Society for Computational Biology announce new partnership
9. New computational technique allows comparison of whole genomes as easily as whole books
10. Supercomputer provides massive computational boost to biomedical research at TGen
11. Penn presents inaugural symposium on applied mathematics and computational science
Post Your Comments:
*Name:
*Comment:
*Email:
(Date:3/17/2016)... 17, 2016 ABI Research, the leader ... global biometrics market will reach more than $30 ... from 2015. Consumer electronics, particularly smartphones, continue to ... anticipated to reach two billion shipments by 2021 ... Pavlakis , Research Analyst at ABI Research. "Surveillance ...
(Date:3/14/2016)... -- NXTD ) ("NXT-ID" or the "Company"), a ... airing of a new series of commercials on Time Warner ... st .  The commercials will air on Bloomberg TV, Fox ... Street show. --> NXTD ) ("NXT-ID" or the ... announces the airing of a new series of commercials on ...
(Date:3/11/2016)... , March 11, 2016 ... new market research report "Image Recognition Market by Technology ... (Marketing and Advertising), by Deployment Type (On-Premises and Cloud), ... To 2022", published by MarketsandMarkets, the global market is ... to USD 29.98 Billion by 2020, at a CAGR ...
Breaking Biology News(10 mins):
(Date:5/25/2016)... ... May 25, 2016 , ... Lady had been battling arthritis since ... ligament in her left knee. Lady’s owner Hannah sought the help of Dr Jeff ... surgeon, to repair her cruciate ligament and help with the pain of Lady’s arthritis. ...
(Date:5/24/2016)... , ... May 24, 2016 , ... ... newly re-branded identity. The new Media Cybernetics corporate branding reflects a results-driven revitalization ... imaging and image analysis. The re-branding components include a crisp, refreshed logo and ...
(Date:5/23/2016)... , May 23, 2016 - Leading ... 40% - Frontage Implement a Single Platform to Manage ... and Traceability Within the Bioanalytical lab Frontage Laboratories, a ... United States and China , has ... laboratory facilities. In addition to serving as the global electronic lab ...
(Date:5/20/2016)... Minneapolis, MN (PRWEB) , ... May 20, 2016 , ... ... and consumer goods companies, today announced its official 25th anniversary of the business. “We ... we are so grateful to our customers for the privilege and honor of serving ...
Breaking Biology Technology: