MicroRNAs (miRNAs) are extensively involved in many diverse biological processes and a single miRNA can regulate the expression of hundreds of gene targets. Changes in miRNA expression can have profound biological impacts, leading to a variety of human diseases. Thus, functional characterization of miRNAs has become one of the most active research fields in biology in recent years. Despite rapid progress in miRNA research, one major obstacle in this field is the lack of robust computational and experimental methods for functional miRNA analysis. 1) On the experimental side, there is a strong demand to develop new methods that can potently suppress the expression of miRNAs for loss-of-function analysis. 2) On the computational side, improved target prediction tools are strongly demanded, as accurate prediction of miRNA targets is a critical first step for miRNA functional analysis. Further, there is a lack of comprehensive online resources for functional analysis of miRNAs by accessing data from both computational and experimental sources. To address these issues, we propose to develop new methods for both computational and experimental analyses of miRNAs. These new methods will be based on recent progress from our research supported by this R01 grant. All newly generated computational and experimental resources will be integratively presented in an online miRNA database, with experimental reagents freely distributed to the research community.

Public Health Relevance

MicroRNAs are involved in many diverse biological processes and a single microRNA can modulate the expression of hundreds of gene targets. The major goal of this study is to develop new methods for both computational and experimental analyses of miRNAs. The successful completion of this project will significantly advance our ability to understand the gene regulation by microRNAs in a variety of normal physiological processes and disease states.

National Institute of Health (NIH)
National Institute of General Medical Sciences (NIGMS)
Research Project (R01)
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Biodata Management and Analysis Study Section (BDMA)
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Ravichandran, Veerasamy
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Washington University
Schools of Medicine
Saint Louis
United States
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