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A method and system for analyzing gene expression data using a smooth response surface algorithm

机译:使用平滑响应面算法分析基因表达数据的方法和系统

摘要

A Smooth Response Surface (SRS) algorithm is provided as a more elaborate data mining technique for analyzing gene expression data, as well as computationally constructing a gene regulatory network. A three-dimensional smooth response surface is generated to capture the biological relationship between the target and activator-repressor. This novel technique is applied to functionally describe triplets of activators, repressors and targets, and their regulations in gene expression data. A diagnostic strategy is built into the SRS algorithm to evaluate the scores of the triplets so that those with low scores are kept and a regulatory network is constructed based on this information and existing biological knowledge. The predictions based on the identified triplets in two yeast expression data agree with experimental data in the literature. The invention provides a novel model with attractive mathematical and statistical features that make the algorithm valuable for mining expression or concentration information in gene expression analysis for determining the function of uncharacterized proteins, as well as for developing a more accurate understanding of coherent regulatory pathways.
机译:平滑响应表面(SRS)算法是一种更精细的数据挖掘技术,用于分析基因表达数据以及通过计算构建基因调控网络。生成三维平滑响应表面以捕获目标与激活物-阻遏物之间的生物学关系。这项新技术应用于功能性描述激活子,阻遏物和靶标的三联体,以及它们在基因表达数据中的调控。 SRS算法中内置了诊断策略以评估三元组的分数,以便保留分数较低的三元组,并基于此信息和现有的生物学知识构建监管网络。基于在两个酵母表达数据中鉴定出的三联体的预测与文献中的实验数据一致。本发明提供了具有吸引人的数学和统计特征的新颖模型,这使得该算法对于挖掘基因表达分析中的表达或浓度信息,以确定未表征的蛋白质的功能以及发展对连贯的调节途径的更准确的理解是有价值的。

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