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Transdisciplinary Cancer Genomics Research: Post-Genome Wide Association (Post-GWA) Initiative (U19)

Sector: Education • Location: United States of America

Source: Grants.gov

Project
Archived

Purpose. The purpose of this funding opportunity announcement (FOA), issued by the National Cancer Institute (NCI), is to promote thorough and efficient identification of genomic regions associated with cancer susceptibility. The FOA specifically solicits applications proposing transdisciplinary research projects designed to: a) take advantage of the existing Genome Wide Association Studies (GWAS)

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The project “Transdisciplinary Cancer Genomics Research: Post-Genome Wide Association (Post-GWA) Initiative (U19)” is an infrastructure initiative in the Education sector, located in United States of America. Taiyo aggregates data on it from Grants.gov.

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archived

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Description

Description

Purpose. The purpose of this funding opportunity announcement (FOA), issued by the National Cancer Institute (NCI), is to promote thorough and efficient identification of genomic regions associated with cancer susceptibility. The FOA specifically solicits applications proposing transdisciplinary research projects designed to: a) take advantage of the existing Genome Wide Association Studies (GWAS) of cancer by exploiting previously generated initial scan GWAS data; and b) accelerate and coordinate integrative post-GWAS discovery research. To address these goals, each application should consist of two to three component sub-projects closely pertinent to a single unifying research theme. At least one of these sub-projects must address the replication or expansion of prior GWAS findings and at least one sub-project must center on epidemiologic aspects. In addition, biological and/or mechanistic studies complementing and connecting the required sub-projects are strongly encouraged as a third sub-project. The long-term goal is to provide a rigorous knowledge base that would enable clinical translation and public health dissemination of the GWAS findings. It is anticipated that these goals will require collaboration of multi-center teams comprising both epidemiologists and basic scientists.

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Source reliability

High

Data quality score

100%

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