Abstract

Genotypic (DNA mutations) and phenotyping data on patients with melanoma are analyzed to identify markers of early disease diagnosis and critical involved genes. An optimal mining method was chosen from those that are traditionally used in the field. This method allows one to analyze a set of terms. Automatic and interactive approaches were performed, which both allow a considerable reduction in the computational requirements. New melanoma-associated genes and candidate relapse markers were identified. Data mining was performed with the JSM method of automated support of scientific research (JSM ASSR).

中文翻译：

---

黑色素瘤患者数据的智能挖掘，用于识别疾病标记和关键基因

摘要

分析黑素瘤患者的基因型（DNA突变）和表型数据，以鉴定早期疾病诊断的标志物和关键的相关基因。从该领域传统使用的方法中选择了一种最佳的开采方法。这种方法可以分析一组术语。执行了自动和交互式方法，这两种方法都可以大大减少计算需求。确定了新的黑色素瘤相关基因和候选复发标记。数据挖掘是通过自动支持科学研究的JSM方法（JSM ASSR）进行的。