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BioMed Research International
Volume 2015, Article ID 391475, 27 pages
Research Article

Applying NGS Data to Find Evolutionary Network Biomarkers from the Early and Late Stages of Hepatocellular Carcinoma

1Laboratory of Control and Systems Biology, Department of Electrical Engineering, National Tsing Hua University, Hisnchu 30013, Taiwan
2Biomedical Technology and Device Research Laboratories, Industrial Technology Research Institute, Hsinchu 31040, Taiwan
3Graduate Institute of Biomedical Informatics, College of Medical Science and Technology, Taipei Medical University, Taipei 110, Taiwan

Received 27 February 2015; Revised 23 April 2015; Accepted 23 April 2015

Academic Editor: Zheng Li

Copyright © 2015 Yung-Hao Wong et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Supplementary Material

Supplementary material S.1 uses the Maximum Likelihood Method to do the parameter identification of regression model in equation (1). S.2 uses the AIC and student’s t-test to calculate the p-values of association abilities, and detect the system model order and determine the significance of the model parameters. Table S3: (a) The 43 identified significant proteins of early stage liver cancer. (b) The 80 identified significant proteins of late stage liver cancer. (c) The 74 identified significant proteins of total stage liver cancer.

  1. Supplementary Material