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High-dimensional data sets have become quite significant in data science. For example, gene expression data sets often have many dimensions, where each dimension corresponds to a different gene, metabolite, or RNA. These data sets capture the expression levels of hundreds of thousands of genes across multiple samples, such as different tissues or conditions.

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Introduction to Machine Learning for Bioinformatics

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  • 发表日期：

    2025年

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  • Gautam B. Singh

摘要

High-dimensional data sets have become quite significant in data science. For example, gene expression data sets often have many dimensions, where each dimension corresponds to a different gene, metabolite, or RNA. These data sets capture the expression levels of hundreds of thousands of genes across multiple samples, such as different tissues or conditions.