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<h1 align="center" id="logo-text" style="font-size:72px; color:#096"><a href="http://cce.edbc.org//index.html"><img src="http://cce.edbc.org/images/logomember.jpg" alt="" width="931" height="160" /></a></h1>

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<h1 class="content">Hongbo Liu</h1>

<a href="mailto:hongbo919@gmail.com">hongbo919@gmail.com</a>

My major research is focused on the design and application of bioinformatics algorithms to elucidate global epigenetic dynamics and regulatory mechanisms in normal development and diseases such as cancer. Since starting bioinformatics research in early 2007, we have published more than 20 peer-reviewed papers in high profile journals, such as Nucleic Acids Research, Development, Database, Scientific Reports, Genes, Genomics and Briefings in bioinformatics. 

 

We developed a number of widely used algorithms to analyze DNA methylome data (<a href="http://fame.edbc.org/smart/index.html" target="new">SMART</a>,<a href="http://bioinfo.hrbmu.edu.cn/qdmr/" target="new">QDMR</a>, <a href="http://202.97.205.78/CpG_MPs/" target="new">CpG_MPs</a>, <a href="http://202.97.205.78/epidiff/" target="new">EpiDiff</a>) and ChIP-seq data (<a href="http://github.com/hbliu/QDCMR" target="new">QDCMR</a>), prediction tools including CpG islands (<a href="http://202.97.205.78/cpgmi/" target="new">CpG_MI</a>) and long non-coding RNAs, and a number of database platforms including <a href="http://sea.edbc.org" target="new">SEA</a>, <a href="http://devmouse.org/" target="new">DevMouse</a>, <a href="http://202.97.205.78/diseasemeth/" target="new">DiseaseMeth</a>, <a href="http://bioinfo.hrbmu.edu.cn/MetaImprint/" target="new">MetaImprint</a> and <a href="http://202.97.205.78/hhmd/" target="new">HHMD</a>. These algorithms and databases have been broadly adopted by thousands of academic users.

<a href="http://scholar.google.com/citations?hl=en&user=sM-dRkIAAAAJ" title="http://scholar.google.com/citations?hl=en&user=7IUCbE4AAAAJ&view_op=list_works&pagesize=100" target="_blank">My Citations @ Google Scholar</a>

Ph.D. in Bioinformatics: 9/2012 - 10/2015 

School of Life Science and Technology, 

Harbin Institute of Technology, Harbin, China 

Assistant professor: 7/2010 - present 

College of Bioinformatics Science and Technology, 

Harbin Medical University, Harbin, China 

M.D. in Bioinformatics: 9/2007 – 6/2010 

School of Life Science and Technology, 

Harbin Institute of Technology, Harbin, China 

Peer Reviewed Publications 

2015: 

<a>1. Liu H, Liu X, Zhang S, Lv J, Li S, Shang S, Jia S, Wei Y, Wang F, Su J et al: Systematic identification and annotation of human methylation marks based on bisulfite sequencing methylomes reveals distinct roles of cell-type-specific hypomethylation in regulation of cell identify genes. Nucleic Acids Research (In Publication) 2015.</a> <a>(First and Corresponding author)</a> 

<a>2. Wei Y, Zhang S, Shang S, Zhang B, Wang X, Li S, Liu H, Zhang Y: SEA: a comprehensive Super-Enhancer Archive. Nucleic Acids Research (DOI: 10.1093/nar/gkv1243) 2015.</a> <a>(Corresponding author)</a> 

<a>3. Lv J, Liu H, Liu H, Han X, Guo J, Han Z, He H, Zhang Y, Wu Q: lncRNAannodb: a mouse lncRNA annotation database in next-generation sequencing era. Scientific Reports (In Revision) 2015.</a> <a>(Co-first author)</a> 

<a>4. Lv J, Liu H, Yu S, Liu H, Cui W, Gao Y, Zheng T, Qin G, Guo J, Zeng T et al: Identification of 4438 novel lincRNAs involved in mouse pre-implantation embryonic development. Molecular genetics and genomics : MGG 2015, 290(2):685-697. (Co-first author) 

5. Zhang C, Zhao H, Li J, Liu H, Wang F, Wei Y, Su J, Zhang D, Liu T, Zhang Y: The identification of specific methylation patterns across different cancers. PLoS One 2015, 10(3):e0120361.</a> 

2014: 

<a>6. Liu, H., Zhu, R., Lv, J., He, H., Yang, L., Huang, Z., Su, J., Zhang, Y., Yu, S. and Wu, Q. (2014) DevMouse, the mouse developmental methylome database and analysis tools. Database : the journal of biological databases and curation, 2014, bat084.</a> (First author) 

<a>7. Lv, J., Huang, Z., Liu, H., Liu, H., Cui, W., Li, B., He, H., Guo, J., Liu, Q., Zhang, Y. et al. (2014) Identification and characterization of long intergenic non-coding RNAs related to mouse liver development. Molecular genetics and genomics : MGG. (Co-first author)</a> 

<a>8. </a>Wei, Y., Su, J., Liu, H., Lv, J., Wang, F., Yan, H., Wen, Y., Liu, H., Wu, Q. and Zhang, Y. (2014) MetaImprint: an information repository of mammalian imprinted genes. Development, 141, 2516-2523. 

<a>. Cai, J., Yang, L., He, H.J., Xu, T., Liu, H.B., Wu, Q., Ma, Y., Liu, Q.H. and Nie, M.H. (2014) Antioxidant capacity responsible for a hypocholesterolemia is independent of dietary cholesterol in adult rats fed rice protein. Gene, 533, 57-66.</a> 

2013: 

<a>9. Liu, H., Chen, Y., Lv, J., Zhu, R., Su, J., Liu, X., Zhang, Y. and Wu, Q. (2013) Quantitative epigenetic co-variation in CpG islands and co-regulation of developmental genes. Scientific reports, 3, 2576.</a> (First author) 

<a>10. Lv, J., Liu, H., Huang, Z., Su, J., He, H., Xiu, Y., Zhang, Y. and Wu, Q. (2013) Long non-coding RNA identification over mouse brain development by integrative modeling of chromatin and genomic features. Nucleic Acids Res, 41, 10044-10061.</a> (Co-first author) 

<a>11. Lv, J., Cui, W., Liu, H., He, H., Xiu, Y., Guo, J., Liu, Q., Zeng, T., Chen, Y., Zhang, Y. et al. (2013) Identification and Characterization of Long Non-Coding RNAs Related to Mouse Embryonic Brain Development from Available Transcriptomic Data. PLoS ONE, 8, e71152.</a> (Co-first author) 

<a>12. </a>Wang, F., Zhang, S., Wen, Y., Wei, Y., Yan, H., Liu, H., Su, J., Zhang, Y. and Che, J. (2013) Revealing the architecture of genetic and epigenetic regulation: a maximum likelihood model. Briefings in bioinformatics. 

<a>13. Su, J., Yan, H., Wei, Y., Liu, H., Wang, F., Lv, J., Wu, Q. and Zhang, Y. (2013) CpG_MPs: identification of CpG methylation patterns of genomic regions from high-throughput bisulfite sequencing data. Nucleic Acids Res, 41, e4.</a> 

<a>14. Xiao, X., Li, Z., Liu, H., Su, J., Wang, F., Wu, X., Wu, Q. and Zhang, Y. (2013) Genome-wide identification of Polycomb target genes in human embryonic stem cells. Gene, 518, 425-430.</a> 

<a>15. </a>Wu, X., Liu, H., Liu, H., Su, J., Lv, J., Cui, Y., Wang, F. and Zhang, Y. (2013) Z curve theory-based analysis of the dynamic nature of nucleosome positioning in Saccharomyces cerevisiae. Gene, 530, 8-18. 

2012: 

<a>16. Lv, J., Liu, H., Su, J., Wu, X., Li, B., Xiao, X., Wang, F., Wu, Q. and Zhang, Y. (2012) DiseaseMeth: a human disease methylation database. Nucleic Acids Res, 40, D1030-1035.</a> (Co-first author) 

<a>17. </a>Su, J., Shao, X., Liu, H., Liu, S., Wu, Q. and Zhang, Y. (2012) Genome-wide dynamic changes of DNA methylation of repetitive elements in human embryonic stem cells and fetal fibroblasts. Genomics, 99, 10-17.. 

<a>18. </a>Su, J., Qi, Y., Liu, S., Wu, X., Lv, J., Liu, H., Zhang, R. and Zhang, Y. (2012) Revealing epigenetic patterns in gene regulation through integrative analysis of epigenetic interaction network. Mol Biol Rep, 39, 1701-1712 

2011: 

<a>19. Zhang, Y., Liu, H., Lv, J., Xiao, X., Zhu, J., Liu, X., Su, J., Li, X., Wu, Q., Wang, F. et al. (2011) QDMR: a quantitative method for identification of differentially methylated regions by entropy. Nucleic Acids Res, 39, e58. (Co-first author)</a> 

20. Liu, H., Su, J., Li, J., Liu, H., Lv, J., Li, B., Qiao, H. and Zhang, Y. (2011) Prioritizing cancer-related genes with aberrant methylation based on a weighted protein-protein interaction network. BMC Syst Biol, 5, 158. 

2010: 

<a>21. Zhang, Y., Lv, J., Liu, H., Zhu, J., Su, J., Wu, Q., Qi, Y., Wang, F. and Li, X. (2010) HHMD: the human histone modification database. Nucleic Acids Res, 38, D149-154.</a> (Co-first author) 

<a>22. Su, J., Zhang, Y., Lv, J., Liu, H., Tang, X., Wang, F., Qi, Y., Feng, Y. and Li, X. (2010) CpG_MI: a novel approach for identifying functional CpG islands in mammalian genomes. Nucleic Acids Res, 38, e6.</a> 

<a>23. Lv, J., Qiao, H., Liu, H., Wu, X., Zhu, J., Su, J., Wang, F., Cui, Y. and Zhang, Y. (2010) Discovering cooperative relationships of chromatin modifications in human T cells based on a proposed closeness measure. PLoS ONE, 5, e14219.</a> 

<a>24. Lv, J., Su, J., Wang, F., Qi, Y., Liu, H. and Zhang, Y. (2010) Detecting novel hypermethylated genes in breast cancer benefiting from feature selection. Comput Biol Med, 40, 159-167.</a>

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