Learning Phenotype Structure Using Sequence Model
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A microarray is a collection of small DNA spots attached to a solid surface. In microarray experiments, the signal collected from each spot is used to estimate the expression level of a gene. A microarray contains thousands of DNA spots.An essential problem in microarray data analysis is to discover phenotype structures.The objective is to 1) discovery groups of samples equivalent to different phenotypes (such as disease or normal), and 2) for each assembly of samples, discover the typical expression pattern. The collective drawback is that the recognized signatures often include a large number of genes but with low discriminative power.Here a propose model is , g*sequence model to report this constraint, where the ordered appearance values among genes are profitably exploited , an algorithm FINDER is established in this process.
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