Abstract
This paper is devoted to identifying the biomarkers of rat liver regeneration via the adaptive logistic regression. By combining the adaptive elastic net penalty with the logistic regression loss, the adaptive logistic regression is proposed to adaptively identify the important genes in groups. Furthermore, by improving the pathwise coordinate descent algorithm, a fast solving algorithm is developed for computing the regularized paths of the adaptive logistic regression. The results from the experiments performed on the microarray data of rat liver regeneration are provided to illustrate the effectiveness of the proposed method and verify the biological rationality of the selected biomarkers.
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This work was supported by National Nature Science Foundation of China (No. 61203293), Key Scientific and Technological Project of Henan Province (No. 122102210131), Program for Science and Technology Innovation Talents in Universities of Henan Province (No. 13HASTIT040), Foundation of Henan Educational Committee (No. 13A120524), Henan Normal University Doctoral Topics (No. qd14156), Henan Higher School Funding Scheme for Young Teachers (No. 2012GGJS-063).
Recommended by Associate Editor Matjaz Gams
Liu-Yuan Chen received his B. Sc. and M. Sc. degrees in applied mathematics from the Henan Normal University, China in 2003 and 2009, respectively. Currently, he is a Ph. D. candidate of Wuhan University of Technology, China.
His research interests include machine learning and data mining.
ORCID iD: 0000-0001-8160-5447
Jie Yang received her B. Sc. degree in communication engineering from Xidian University, China in 1982 and M. Sc. degree in computer and automation from Wuhan Transportation University, China in 1988. She received Ph.D. degree in electronic engineering from the Shanghai Jiao Tong University, China in 1999. Since 1999, she is a professor and doctoral supervisor in the School of Electronics and Information at Wuhan University of Technology, China.
Her research interests include image processing, information hiding, cryptography and multimedia communication.
Guo-Guo Xu received her B. Sc. degree in biological sciences from Shangqiu Normal University, China in 2011. Currently, she is a master student of School of Life Sciences at Henan Normal University, China.
Her research interests include rat liver regeneration and planaria head regeneration.
Yun-Qing Liu received his B. Sc. degree in mechanical design manufacturing and automation from College of Air Defence Force of Chinese People’s Liberation Army, China in 2009. Currently, he is a master student of School of Life Sciences at Henan Normal University, China.
His research interests include rat liver regeneration and planaria head regeneration.
Jun-Tao Li received his B. Sc. and M. Sc. degrees in applied mathematics from Henan Normal University, China in 2001 and 2004, respectively. He received Ph.D. degree in control theory and control engineering from Beihang University, China in 2010. Since 2011, he is an associate professor of Henan Normal University, China.
His research interests include machine learning and its applications.
Cun-Shuan Xu received his B. Sc. degree from Henan Normal University, China in 1982 and M. Sc. degree from Beijing Normal University, China in 1985. He received Ph.D. degree from Bremen University, Germany in 1995. Since 1995, he is a professor of School of Life Sciences at Henan Normal University, China.
His research interests include regenerating biology and medicine.
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Chen, LY., Yang, J., Xu, GG. et al. Biomarker identification of rat liver regeneration via adaptive logistic regression. Int. J. Autom. Comput. 13, 191–198 (2016). https://doi.org/10.1007/s11633-015-0919-5
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DOI: https://doi.org/10.1007/s11633-015-0919-5