We are testing a new system for linking grants to scientists.
The funding information displayed below comes from the
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NSF Award Database.
The grant data on this page is limited to grants awarded in the United States and is thus partial. It can nonetheless be used to understand how funding patterns influence mentorship networks and vice-versa, which has deep implications on how research is done.
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High-probability grants
According to our matching algorithm, Manpreet S. Katari is the likely recipient of the following grants.
Years |
Recipients |
Code |
Title / Keywords |
Matching score |
2005 — 2006 |
Katari, Manpreet Singh |
F32Activity Code Description: To provide postdoctoral research training to individuals to broaden their scientific background and extend their potential for research in specified health-related areas. |
Networks of Nitrogen Regulated Genes in Seed
DESCRIPTION (provided by applicant): The goal of the project is to identify a network of genes that are nitrogen responsive and are involved in seed development. This project will integrate development and metabolism networks to better understand how metabolism influences development and vice versa. The project will generate microarray data from Arabidopsis seeds and siliques, with or without treatment with nitrogen and carbon, and from two different stages of seed development. The microarray data will be stored and analyzed using an integrated database called VirtualDB. VirtualDB will also store functional annotations from several other resources, such as Kegg and GO (Gene Ontology). The integrated nature of VirtualDB will allow us to make complex queries which will provide biological insight into our microarray results. We can visualize our network of nitrogen induced genes involved in seed development by using tools such as Cytoscape. A list of candidate genes will be created, based on the gene's functions and positions in the network, and then will be validated using mutant analysis. The mutant, either a gene knockout or an overexpression vector, will be analyzed via microarray experiments using RNA extracted from siliques and/or seeds.
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