Novel technique for preprocessing high dimensional time-course data from DNA microarray

Mathematical model-based clustering

Kazumi Hakamada, Masahiro Okamoto, Taizo Hanai

研究成果: ジャーナルへの寄稿記事

15 引用 (Scopus)

抄録

Motivation: Classifying genes into clusters depending on their expression profiles is one of the most important analysis techniques for microarray data. Because temporal gene expression profiles are indicative of the dynamic functional properties of genes, the application of clustering analysis to time-course data allows the more precise division of genes into functional classes. Conventional clustering methods treat the sampling data at each time point as data obtained under different experimental conditions without considering the continuity of time-course data between time periods t and t + 1. Here, we propose a method designated mathematical model-based clustering (MMBC). Results: The proposed method, designated MMBC, was applied to artificial data and time-course data obtained using Saccharomyces cerevisiae. Our method is able to divide data into clusters more accurately and coherently than conventional clustering methods. Furthermore, MMBC is more tolerant to noise than conventional clustering methods.

元の言語英語
ページ(範囲)843-848
ページ数6
ジャーナルBioinformatics
22
発行部数7
DOI
出版物ステータス出版済み - 4 1 2006

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Model-based Clustering
DNA Microarray
Microarrays
Oligonucleotide Array Sequence Analysis
Cluster Analysis
Preprocessing
DNA
High-dimensional
Theoretical Models
Genes
Mathematical Model
Mathematical models
Clustering Methods
Gene expression
Yeast
Gene
Sampling
Clustering Analysis
Gene Expression Profile
Saccharomyces Cerevisiae

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Medicine(all)
  • Biochemistry
  • Molecular Biology
  • Computer Science Applications
  • Computational Theory and Mathematics
  • Computational Mathematics

これを引用

Novel technique for preprocessing high dimensional time-course data from DNA microarray : Mathematical model-based clustering. / Hakamada, Kazumi; Okamoto, Masahiro; Hanai, Taizo.

:: Bioinformatics, 巻 22, 番号 7, 01.04.2006, p. 843-848.

研究成果: ジャーナルへの寄稿記事

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