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Hierarchical tree snipping: clustering guided by prior knowledge

机译:分层树剪裁:以先验知识为指导的聚类

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摘要

Motivation: Hierarchical clustering is widely used to cluster genes into groups based on their expression similarity. This method first constructs a tree. Next this tree is partitioned into subtrees by cutting all edges at some level, thereby inducing a clustering. Unfortunately, the resulting clusters often do not exhibit significant functional coherence.
机译:动机:分层聚类广泛用于根据基因的表达相似性将基因聚类。此方法首先构造一棵树。接下来,通过在某种程度上剪切所有边缘将该树划分为子树,从而引发聚类。不幸的是,所得的簇通常不表现出明显的功能一致性。

著录项

  • 来源
    《Bioinformatics》 |2007年第24期|3335-3342|共8页
  • 作者单位

    Department of Computer Science Ben Gurion University Beer Sheva 84105 Israel;

    Department of Biomedical Engineering;

    Center for Advanced Genomic Technology;

    Bioinformatics Program and;

    Children's Hospital Boston Harvard/MIT Program in Health Sciences and Technology 300 Longwood Avenue Boston MA 02115 USA;

  • 收录信息 美国《科学引文索引》(SCI);美国《化学文摘》(CA);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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