Unsupervised learning approaches are frequently used to stratify patients into clinically relevant subgroups and to identify biomarkers such as disease-associated genes. However, clustering and biclustering techniques are oblivious to the functional relationship of genes and are thus not ideally suited to pinpoint molecular mechanisms along with patient subgroups.

中文翻译：

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BiCoN：患者和组学数据的网络约束双聚类

无监督学习方法经常用于将患者分为临床相关的亚组，并识别疾病相关基因等生物标志物。然而，聚类和双聚类技术忽略了基因的功能关系，因此不适合精确定位分子机制和患者亚组。