
NSF Org: |
IIS Division of Information & Intelligent Systems |
Recipient: |
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Initial Amendment Date: | August 20, 2008 |
Latest Amendment Date: | September 14, 2011 |
Award Number: | 0812111 |
Award Instrument: | Continuing Grant |
Program Manager: |
Sylvia Spengler
sspengle@nsf.gov (703)292-7347 IIS Division of Information & Intelligent Systems CSE Directorate for Computer and Information Science and Engineering |
Start Date: | September 1, 2008 |
End Date: | August 31, 2013 (Estimated) |
Total Intended Award Amount: | $445,359.00 |
Total Awarded Amount to Date: | $1,390,291.00 |
Funds Obligated to Date: |
FY 2009 = $364,992.00 FY 2010 = $465,950.00 FY 2011 = $266,275.00 |
History of Investigator: |
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Recipient Sponsored Research Office: |
3112 LEE BUILDING COLLEGE PARK MD US 20742-5100 (301)405-6269 |
Sponsor Congressional District: |
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Primary Place of Performance: |
3112 LEE BUILDING COLLEGE PARK MD US 20742-5100 |
Primary Place of
Performance Congressional District: |
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Unique Entity Identifier (UEI): |
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Parent UEI: |
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NSF Program(s): | Info Integration & Informatics |
Primary Program Source: |
01000910RB NSF RESEARCH & RELATED ACTIVIT 01001011DB NSF RESEARCH & RELATED ACTIVIT 01001011RB NSF RESEARCH & RELATED ACTIVIT 01001112RB NSF RESEARCH & RELATED ACTIVIT |
Program Reference Code(s): |
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Program Element Code(s): |
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Award Agency Code: | 4900 |
Fund Agency Code: | 4900 |
Assistance Listing Number(s): | 47.070 |
ABSTRACT
Recent advances in genome sequencing technologies have enabled the
sequencing of bacteria directly from the environment, providing a
broader outlook on the diversity of bacteria than ever before
possible. Recent studies of environmental samples have revealed
complex communities containing many previously unknown species, and
uncovered a large amount of genetic variation and diversity even among
closely related strains. Characterizing this genomic variation is
critical in studies of microbial ecology and evolution, yet currently
available computational tools, originally developed for the study of
single organisms, are ill-suited for this task.
This proposal aims to develop the theoretical and computational
infrastructure for the study of genomic variation within mixtures of
organisms. The proposed research relies on both theoretical and
empirical analyses of the structure of genome assembly graphs in order
to characterize graph signatures that are correlated with intra- and
inter- species polymorphisms. A particular focus is placed on
understanding and using the information provided by next generation
sequencing technologies as well as other high-throughput experimental
techniques. The proposed work provides critical analysis tools
to help biologists explore the genetic variation within the
environment.
Additional information about this project is available at
http://www.cbcb.umd.edu/research/Genomic_Variation.shtml.
PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH
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PROJECT OUTCOMES REPORT
Disclaimer
This Project Outcomes Report for the General Public is displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed in this Report are those of the PI and do not necessarily reflect the views of the National Science Foundation; NSF has not approved or endorsed its content.
This project covered the development of algorithms for analyzing genome assembly graphs with the goal of uncovering signatures of genomic variation, as found, for example, in a mixture of organisms some of which contain specific genes important for their adaptation to the environment.
The project has resulted in over 15 publications in peer reviewed journals and conferences, and the related research has contributed to a better understanding on genome assembly and its limitations. In addition, several software packages were developed and made available open-source to the community, including a novel metagenomic assembly pipeline metAMOS - the only tool that can actually discover genomic variation in metagenomic data.
This project has also directly and indirectly contributed to the training of six graduate students, several of whom have graduated and pursued academic and industry positions. In addition, this award allowed us to initiate a summer internship program, which is still ongoing, and which has trained over 20 undergraduate and highschool students.
To summarize, our project has had a direct impact in our field, both through the development of new ideas, algorithms, and software, as well as to biologists who can use the tools we developed. In addition, our work has had a significant impact in the training of the next generation of scientists at several levels in their academic career, from highschool to post-graduate studies.
Last Modified: 11/01/2013
Modified by: Mihai Pop
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