目的：采用高通量基因芯片观察大鼠抑郁症模型基因表达的变化，结合基因功能分类体系探讨抑郁症的发病机制。
AIM: To observe the alteration of gene expression of depression rat models by gene chips of high flux, and explore the pathogenesis of depression combining with classification system of gene function.
应用机器学习进行分类是基因功能预测的一种重要手段。
Classification by machine learning is an important technique to predict gene functions.
依据这两个准则，本文提出了一种改进的基于基因功能树的基因功能分类算法。
According to these two algorithms, this thesis proposed a new gene function classification algorithm based on gene function tree.
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