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This article is part of the supplement: The International Conference on Intelligent Biology and Medicine (ICIBM): Systems Biology

Open Access Research

A dynamic time order network for time-series gene expression data analysis

Pengyue Zhang1, Raphaël Mourad1*, Yang Xiang2, Kun Huang2, Tim Huang3, Kenneth Nephew4, Yunlong Liu1 and Lang Li1

Author Affiliations

1 Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, IN 46202, USA

2 Department of Biomedical Informatics, The Ohio State University, Columbus, OH 43210, USA

3 Laboratory of Breast Cancer Epigenomics, The Ohio State University, Columbus, OH 43210, USA

4 Laboratory of Ovarian Cancer Epigenomics, Indiana University, Bloomington, IN 47405, USA

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BMC Systems Biology 2012, 6(Suppl 3):S9  doi:10.1186/1752-0509-6-S3-S9

Published: 17 December 2012

Additional files

Additional file 1:

Decomposition of the cubic function using knots.

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Additional file 2:

Solving of parameters βi1 and βi3.

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Additional file 3:

Matrix T*.

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Additional file 4:

Likelihood computation of regression for the time order determination.

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