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Ovarian Cancer Proteogenomics Research Award

Sector: Aerospace & Defense • Location: United States of America

Source: Grants.gov

Project
Archived

The OCRP Proteogenomics Research Award supports the use of proteomics and/or genomics to explore new concepts or theories in ovarian cancer. The award is intended to support the genomic and/or transcriptomic and/or proteomic analysis of currently available clinical specimens with a focus on answering biologic and pathophysiologic questions of clinical relevance in ovarian cancer. The proposed rese

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The project “Ovarian Cancer Proteogenomics Research Award” is an infrastructure initiative in the Aerospace & Defense 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

The OCRP Proteogenomics Research Award supports the use of proteomics and/or genomics to explore new concepts or theories in ovarian cancer. The award is intended to support the genomic and/or transcriptomic and/or proteomic analysis of currently available clinical specimens with a focus on answering biologic and pathophysiologic questions of clinical relevance in ovarian cancer. The proposed research question should be innovative and have the potential to make an impact on ovarian cancer. Clinical trials are not allowed under the Proteogenomics Research Award mechanism. The analysis of clinical trial-derived specimens and/or large patient specimen cohorts is encouraged. Preliminary data are not required but are allowed. Applicants are encouraged to explore and consider the possible use of the unique proteomics resource at the Women’s Health Integrated Research Center Clinical Proteomics Platform, which was established by the Department of Defense (DOD) intramural Gynecologic Cancer Center of Excellence to provide cutting-edge capabilities for identifying and validating protein biomarkers and surrogates for enhanced cancer patient management through improved early detection, patient stratification, and monitoring for therapeutic efficacy, outcomes, and recurrence.

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Source reliability

High

Data quality score

100%

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