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Identification of Co-Regulation Patterns By Unsupervised Cluster Analysis of Gene Expression Data
Identification of Co-Regulation Patterns By Unsupervised Cluster Analysis of Gene Expression Data
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机译:通过基因表达数据的无监督聚类分析识别共调控模式
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摘要
A method is provided for unsupervised clustering of gene expression data to identify co-regulation patterns. A clustering algorithm randomly divides the data into k different subsets and measures the similarity between pairs of datapoints within the subsets, assigning a score to the pairs based on similarity, with the greatest similarity giving the highest correlation score. A distribution of the scores is plotted for each k. The highest value of k that has a distribution that remains concentrated near the highest correlation score corresponds to the number of co-regulation patterns.
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