SGER: Rule Discovery for Predicting Optimal siRNA's

SGER：预测最佳 siRNA 的规则发现

• 批准号: 0333789
• 负责人: Fran Lewitter
• 金额: $ 10万
• 依托单位: Whitehead Institute for Biomedical Research
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2003
• 资助国家: 美国
• 起止时间: 2003-09-01 至 2005-02-28
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0333789&HistoricalAwards=false
• 关键词: SGER; Rule; Discovery; Predicting; Optimal

The Whitehead Institute for Biomedical Research has been awarded a Small Grant for Exploratory Research to find rules for predicting the optimal oligonucleotide to silence a gene. A promising new technology, siRNA (short interfering RNA), provides an experimental method for studying the function of a gene by reducing or eliminating its expression. This technology is being used to study biological processes in model organisms. A properly selected short double stranded RNA sequence (~21 nucleotides) can silence the expression of a gene. However, selection of the best sequence among the many choices is still more of an art than a science. The team will use experimental laboratory data consisting of multiple siRNAs for many genes. Using novel computational approaches, they will attempt to discover a set of rules that will help to predict the optimal sequence for gene silencing. Because of the nature of the data, new statistical methods will need to be applied to the data. The computational tools built based on these rules will be useful to scientists wishing to silence specific genes, specific gene families, or even specific biological pathways within a genome.

怀特黑德生物医学研究所已获得探索性研究的一项小赠款，以找到预测最佳寡核苷酸以使基因沉默的规则。一种有希望的新技术，siRNA（简短干扰RNA），提供了一种实验方法，可以通过减少或消除其表达来研究基因的功能。该技术用于研究模型生物的生物过程。 正确选择的短双链RNA序列（〜21个核苷酸）可以使基因的表达保持沉默。 但是，在众多选择中选择最佳顺序仍然更多是艺术而不是科学。该团队将使用由许多基因组成的多个siRNA组成的实验性实验室数据。使用新颖的计算方法，他们将尝试发现一组规则，这些规则将有助于预测基因沉默的最佳顺序。 由于数据的性质，需要将新的统计方法应用于数据。基于这些规则构建的计算工具将对希望沉默特定基因，特定基因家族甚至基因组中特定的生物学途径的科学家有用。