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DESCRIPTION (provided by applicant): MicroRNAs (miRNAs) are an abundant class of small non-coding RNAs that regulate messenger RNAs (mRNAs) post-transcriptionally. miRNAs induce target messenger RNA degradation or translational inhibition, predominantly through cognitive binding sites in the 3 untranslated regions (3UTRs). Accurate identification of miRNA targets is essential for the understanding of their functions. Target identification has been a major challenge for understanding this recently recognized exciting dimension of gene regulation. To this end, computational target prediction methods have proven to be valuable. However, current prediction methods suffer from a number of limitations that hinder progress. Recently, biochemical purification and high throughput deep-sequencing have become feasible. Furthermore, we have developed a high-throughput methodology to experimentally test thousands of miRNA-3UTR interactions, and have acquired mRNA/miRNA expression data on hundreds of cancer cell lines. These experimental advances have presented us the opportunity to develop state-of-the-art miRNA target prediction algorithms. In this application, we propose to adapt an interdisciplinary approach to develop novel miRNA-target prediction algorithms to overcome the limitations of current prediction algorithms. Our complementary expertise in RNA Bioinformatics and Statistics and large scale experimental testing have placed us in a unique position to pursue the following specific aims: 1) Develop a target prediction algorithm based on deep sequencing data from biochemically purified miRNA-target complexes; 2) Perform large-scale miRNA-3UTR reporter assays to derive functional miRNA-target interactions; 3) Develop algorithms and perform analyses and validation for more informative predictions on the level of miRNA-mediated regulation and miRNA-regulated pathways and networks; 4) Develop user-friendly software tools and database for distribution to the scientific community. This project will advance our understanding of miRNA-mediated gene regulation in molecular biology and systems biology, facilitate development of miRNA-based therapeutics, and in turn benefit human health.
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Novel Bioinformatics Tools for Quantitative Prediction of Primary MicroRNA Processing
  • 批准号:
    10437869
  • 项目类别:
  • 资助金额:
    $45.28万
  • 财政年份:
    2020
  • 负责人:
    YE DING
  • 依托单位:
Novel Bioinformatics Tools for Quantitative Prediction of Primary MicroRNA Processing
  • 批准号:
    10031383
  • 项目类别:
  • 资助金额:
    $47.64万
  • 财政年份:
    2020
  • 负责人:
    YE DING
  • 依托单位:
Novel Bioinformatics Tools for Quantitative Prediction of Primary MicroRNA Processing
  • 批准号:
    10698014
  • 项目类别:
  • 资助金额:
    $45.06万
  • 财政年份:
    2020
  • 负责人:
    YE DING
  • 依托单位:
Novel Bioinformatics Tools for Quantitative Prediction of Primary MicroRNA Processing
  • 批准号:
    10246941
  • 项目类别:
  • 资助金额:
    $45.28万
  • 财政年份:
    2020
  • 负责人:
    YE DING
  • 依托单位:
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