University of Washington
4333 Brooklyn Ave NE
SEATTLE, WA 98195 206/543-4043
NSF Program(s):
PLANT GENOME RESEARCH PROJECT, ADVANCES IN BIO INFORMATICS
Field Application(s):
Program Reference Code(s):
BIOT,9184,9109
Program Element Code(s):
1329,1165
ABSTRACT
Rice is one of the most important crops in the world, and the main source of food for nearly half of the world's population. Rice research can be applied the other major cereals, such as wheat and
maize, and many aspects of rice genomics can be transferred to the many minor economic grass species that have themselves not warranted extensive research and breeding. Drafts of the rice genome have been recently published, and current estimates indicate that 60,000 genes
are present in rice.
The plan is to construct a structural and functional model for every protein encoded by the rice genome using methods developed at the University of Washington. The project will further the understanding and elucidation of the function of characterized as well as novel proteins, identify those proteins that improve yield and confer disease and pest resistance, and enable genetic engineering of rice crops with beneficial traits not naturally found in rice.
The research, involving the collaborative efforts of scientists from all over the world, will provide opportunities for the training of undergraduate and graduate students, and post-doctoral fellows. All the information generated by the research will be generated through a web server and database: http://bioverse.compbio.washington.edu, which will provide a synergistic portal to obtain a comprehensive picture of rice and cereal organismal biology. Besides helping understand how other plant genomes work, this research will also set up a framework
for integrating single molecule and genomic data, and thus the science developed will help with projects on analyzing other genomes.
PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH
(Showing: 1 - 18 of 18).
Chang AN, McDermott J, Samudrala R..
"An enhanced java graph applet interface for visualizing interactomes.,"
Bioinformatics,
v.21,
2005,
p. 1741.
Cheng G, Qian B, Samudrala R, Baker D..
"Improvement in protein functional site prediction by distinguishing structural and functional constraints on protein family evolution using computational design.,"
Nucleic Acids Research,
v.33,
2005,
p. 5861.
Hong L-H, Samudrala R.
"Accurate and automated assignment of secondary structure with PsiCSI.,"
Protein Science,
v.12,
2003,
p. 288.
Hung L-H, Ngan S-C, Liu T, and Samudrala R..
"PROTINFO: New algorithms for enhanced protein structure prediction.,"
Nucleic Acids Research,
v.33,
2005,
p. W77.
Hung L-H, Samudrala R.
"An automated assignment-free Bayesian approach for accurately identifying proton contacts from NOESY data,"
Journal of Biomolecular NMR,
v.36,
2006,
p. 189.
Hung L-H, Samudrala R..
"PROTINFO: Secondary and tertiary protein structure prediction.,"
Nucleic Acids Research,
v.31,
2003,
p. 3296.
Liu, TY; Samudrala, R.
"The effect of experimental resolution on the performance of knowledge-based discriminatory functions for protein structure selection,"
PROTEIN ENGINEERING DESIGN & SELECTION,
v.19,
2006,
p. 431
- 437.
McDermott J, Bumgarner RE, Samudrala R..
"Functional annotation from protein interaction networks.,"
Bioinformatics,
v.21,
2005,
p. 3217.
McDermott J, Guerquin M, Frazier Z, Chang A, Samudrala R..
"BIOVERSE: Enhancements to the framework for structural, functional, and contextual annotations of proteins and proteomes.,"
Nucleic Acids Research,
v.33,
2005,
p. W324.
McDermott J, Samudrala R..
"BIOVERSE: Functional, structural, and contextual annotation of proteins and proteomes.,"
Nucleic Acids Research,
v.31,
2003,
p. 3736.
McDermott J, Samudrala R..
"Enhanced functional information from protein networks.,"
Trends in Biotechnology,
v.22,
2004,
p. 60.
Ngan S-C, Inouye M, Samudrala R.
"A knowledge-based scoring function based on residue triplets for protein structure prediction.,"
Protein Engineering, Design, and Selection,
v.19,
2006,
p. 187.
Wang K and Samudrala R..
"FSSA: A novel method for identifying functional signatures from structural alignments.,"
Bioinformatics,
v.21,
2005,
p. 2969.
Wang K, Fain B, Levitt M, Samudrala R..
"Improved protein structure selection using decoy-dependent discriminatory functions.,"
BMC Structural Biology,
v.4,
2004,
p. 8.
Wang W, Zheng H, Yang S, Yu H, Li J, Jiang H, Su J, Yang L, Zhang J, McDermott J, Samudrala R, Wang J, Yang H, Yu J, Kristiansen K, Wong GK, Wang J..
"Origin and evolution of new exons in rodents.,"
Genome Research,
v.15,
2005,
p. 1258.
Wang, K; Samudrala, R.
"Automated functional classification of experimental and predicted protein structures,"
BMC BIOINFORMATICS,
v.7,
2006,
Wang, K; Samudrala, R.
"Incorporating background frequency improves entropy-based residue conservation measures,"
BMC BIOINFORMATICS,
v.7,
2006,
Yu J, Wang J, Lin W, Li S, Li H, Zhou J, ..., McDermott J,
Samudrala R, Wang J, Wong GK..
"The genomes of Oryza sativa: A history of duplications.,"
Public Library of Science Biology,
v.3,
2005,
p. e38.
(Showing: 1 - 18 of 18).
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