Suppr超能文献

使用时间抽象对基因表达数据进行聚类。

Clustering gene expression data with temporal abstractions.

作者信息

Sacchi L, Bellazzi R, Larizza C, Magni P, Curk T, Petrovic U, Zupan B

机构信息

Dipartimento di Informatica e Sistemica, Università di Pavia, Italy.

出版信息

Stud Health Technol Inform. 2004;107(Pt 2):798-802.

Abstract

This paper describes a new technique for clustering short time series coming from gene expression data. The technique is based on the labelling of the time series through temporal trend abstractions and a consequent clustering of the series on the basis of their labels. Clustering is performed at three different levels of aggregation of the original time series, so that the results are organized and visualized as a three-levels hierarchical tree. Results on simulated and on yeast data are shown. The technique appears robust and efficient and the results obtained are easy to be interpreted.

摘要

本文描述了一种用于对来自基因表达数据的短时间序列进行聚类的新技术。该技术基于通过时间趋势抽象对时间序列进行标记,并基于这些标记对序列进行聚类。聚类是在原始时间序列的三个不同聚合级别上进行的,以便将结果组织并可视化为一个三级层次树。展示了在模拟数据和酵母数据上的结果。该技术显得稳健且高效,所获得的结果易于解释。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验