Interpolation based consensus clustering for gene expression time series-Reference-Cited by-同舟云学术

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Interpolation based consensus clustering for gene expression time series

Published:2015-04-16 Issue:1 Volume:16 Page:
ISSN:1471-2105
Container-title:BMC Bioinformatics
language:en
Short-container-title:BMC Bioinformatics

Author:

Chiu Tai-Yu,Hsu Ting-Chieh,Yen Chia-Cheng,Wang Jia-Shung

Publisher

Springer Science and Business Media LLC

Subject

Applied Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Structural Biology

Link

http://link.springer.com/article/10.1186/s12859-015-0541-0/fulltext.html

Reference37 articles.

1. Bar-Joseph Z. Analyzing time series gene expression data. Bioinformatics. 2004; 20(16):2493–503.

2. de Ridder D, de Ridder J, Reinders MJT. Pattern Recognition in Bioinformatics. Brief Bioinformatics. 2013; 14(5):633–47.

3. Androulakis IP, Yang E, Almon RR. Analysis of time-series gene expression data: methods, challenges, and opportunities. Annu Rev Biomed Eng. 2007; 9:205–28.

4. Tamayo P, Slonim D, Mesirov J, Zhu Q, Kitareewan S, Dmitrovsky E, et al. Interpreting patterns of gene expression with self-organizing maps: Methods and application to hematopoietic differentiation. Proc Natl Acad Sci U S A. 1999; 96(6):2907–912.

5. Yeung KY, Medvedovic M, Bumgarner RE. Clustering gene-expression data with repeated measurements. Genome Biol. 2003; 4:R34.

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