Professor | Zhu Liucun | Asia Growth Partners

Name

Zhu Liucun

Contact Information

zhuliucun@shu.edu.cn

Language ability

Chinese, English

Province

Shanghai

University/Lab Affiliation and Title	Shanghai University
Faculty	Life Sciences
Academic Background & Achievements	2005/9 - 2010/6 PhD in Botany: Nanjing University 2001/9 - 2005/6 Bachelor in Biophysics: Nanjing University
Work Experience	2015/7 - Present, Shanghai University, School of Life Sciences, Associate Professor 2010/7 - 2015/7, Shanghai University, Institute of Systems Biotechnology, Lecturer 2008/9 - 2009/9, Purdue University, Agronomy, Jointly trained PhD student

University/Lab Affiliation and Title

Shanghai University

Faculty

Life Sciences

Academic Background & Achievements

Work Experience

2015/7 - Present, Shanghai University, School of Life Sciences, Associate Professor
2010/7 - 2015/7, Shanghai University, Institute of Systems Biotechnology, Lecturer
2008/9 - 2009/9, Purdue University, Agronomy, Jointly trained PhD student

Areas of Focus	Genomics and Bioinformatics Biomedical Big Data Analysis Machine Learning in Genomics
Publications	Network-based method for mining novel HPV infection related genes using random walk with restart algorithm., Zhu Liucun, Su Fangchu, Xu YaoChen, Zou Quan, 2018 Melanoma long non-coding RNA signature predicts prognostic survival and directs clinical risk-specific treatments., Chen Xijia, Guo Wenna, Xu Xin-Jian, Su Fangchu, Wang Yi, Zhang Yingzheng, Wang Qiang, Zhu Liucun, 2017 Transcriptome sequencing uncovers a three–long noncoding RNA signature in predicting breast cancer survival., Guo, W., Wang, Q., Zhan, Y., Chen, X., Yu, Q., Zhang, J., ... & Zhu, L., 2016

Areas of Focus

Genomics and Bioinformatics
Biomedical Big Data Analysis
Machine Learning in Genomics

Publications

Network-based method for mining novel HPV infection related genes using random walk with restart algorithm., Zhu Liucun, Su Fangchu, Xu YaoChen, Zou Quan, 2018
Melanoma long non-coding RNA signature predicts prognostic survival and directs clinical risk-specific treatments., Chen Xijia, Guo Wenna, Xu Xin-Jian, Su Fangchu, Wang Yi, Zhang Yingzheng, Wang Qiang, Zhu Liucun, 2017
Transcriptome sequencing uncovers a three–long noncoding RNA signature in predicting breast cancer survival., Guo, W., Wang, Q., Zhan, Y., Chen, X., Yu, Q., Zhang, J., ... & Zhu, L., 2016

Genomics Bioinformatics High-Throughput Sequencing Rna Epigenomics Biological Networks Functional Genes Biomedical Big Data Machine Learning

Xiao-Lei Wang - Shanghai Jiao Tong University

Chao Chen - Central South University

Dehua Hu - Central South University

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