The gene ontology (GO) is a widely used resource for describing molecular functions, biological processes, and cellular components of gene products. Since its inception in 2006, the GO has been used to describe millions of gene products resulting in a massive data store of over 6 million annotations. The staggering amount of data that has resulted from annotating gene products with GO terms has led the way and opened new avenues for a wide variety of large‐scale computational analyses. Specifically, a variety of data mining techniques such as association rule mining, clustering etc. have been applied successfully to a range of biological applications. This article provides a review of four data mining applications/techniques for GO data mining gene expression data, association rule mining, clustering, and text mining and highlights future directions in each of these areas.

中文翻译：

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基因本体支持的数据挖掘

基因本体论（GO）是一种广泛使用的资源，用于描述基因产物的分子功能，生物学过程和细胞成分。自2006年成立以来，GO已用于描述数百万种基因产品，从而形成了一个拥有超过600万条注释的海量数据。用GO术语注释基因产物所产生的惊人数据量，为解决各种大规模计算分析开辟了道路，并开辟了新途径。具体地，诸如关联规则挖掘，聚类等的各种数据挖掘技术已经成功地应用于一系列生物学应用。本文概述了GO数据挖掘基因表达数据，关联规则挖掘，聚类，