BMC Genomics

official impact factor 4.21

Open Access Methodology article

A signature-based method for indexing cell cycle phase distribution from microarray profiles

Hideaki Mizuno1,2*, Yoshito Nakanishi1, Nobuya Ishii1, Akinori Sarai2 and Kunio Kitada1

Author Affiliations

1 Kamakura Research Laboratories, Chugai Pharmaceutical Co Ltd, Kamakura, Kanagawa, Japan

2 Department of Biosciences and Bioinformatics, Kyushu Institute of Technology, Iizuka, Fukuoka, Japan

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BMC Genomics 2009, 10:137 doi:10.1186/1471-2164-10-137

Published: 30 March 2009

Additional files

Additional file 1:

The gene list for cell cycle signatures. The CCS genes and assigned CCS subset IDs are listed.

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Additional file 2:

Validation of CCS method in the Whitfiled et al. cell cycle dataset. CCS scores were calculated for the total (upper panel) and the cycling (lower panel) gene dataset. The purple bars above the columns indicate Whitfield et al.'s estimations of the S phase.

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Additional file 3:

Analysis of the Yamamoto et al. dataset. Serum starved NIH3T3 cells were stimulated with FGF to re-enter the cell cycle. Profiles of unstimulated cells (FGF 0 h) and FGF-stimulated cells (FGF 3–12 h) were analyzed.

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Additional file 4:

CCS score plots for the WAP-Myc model. Same as for Fig. 3B.

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Additional file 5:

Analysis of the Langerød et al. breast cancer dataset. (A), (B) and (C) are the same as in Fig. 4.

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Additional file 6:

Power spectrum of the 51 cell cycle-regulated genes. The Hela S3 cell cycle dataset was processed as described in Methods. Fourier transformation magnitudes for the known 51 cell cycle-regulated genes for each periodicity were averaged and plotted.

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