Li Chunquan resume

 1.Born in September 1979, deputy director (ZHENG Ke), Ph.D., Professor, doctoral tutor, Department of medical informatics. The research direction is "the regulation of gene transcription, upstream and downstream networks and pathways in complex diseases such as malignant tumors and cardiovascular diseases". Harbin Medical University, leader of bioinformatics, director of the Institute of bioinformatics. The model worker, the young 54 medal winner, the winner of the Distinguished Youth Training Fund of the academician Wei Han, the winner of the ten young scientific and technological talents award, the outstanding doctoral thesis winner of the province, and the publication of bioinformatics theory and medical practice by the people's Health Publishing House, are the Editorial Committee of the national bioinformatics training. Class teachers (three sessions in total), National Bioinformatics Summer School Training Teachers, National Bioinformatics Backbone Teachers Training Course Lecture Teachers. 2.So far, more than 60 SCI research papers have been published, with a total impact of more than 200. There are nearly 40 papers by the first author, co-author or communication author, of which 4 papers are SCI influencing factor > 10 and 17 papers are SCI influencing factor > 5. The papers were published in the magazine "Nucleic Acids Research", "Briefing in bioinformatics" and "Bioinformatics" published by the British publishing group. As the project leader, he is responsible for the projects funded by the National Natural Science Foundation of China, the National Natural Science Foundation youth fund project, the national Ministry of education doctoral discipline special research fund project, the academician Yu Weihan outstanding youth training fund, the Provincial Natural Science Foundation Project and the science and technology research project of the provincial education department. The research results were awarded the first prize of Heilongjiang natural science and Technology Academic Achievement Award (ranked first) and the Chinese medical science and Technology Award three (rank fifth). 3.The SEdb super enhancers database (http://www.licpathway.net/sedb/) is the most comprehensive human super enhancer biological information resource library in the world. The SEdb bioinformatics resource database has screened 542 sets of histone acetylation modification data from over three thousand samples by integrating the original sequencing data of H3K27AC, SRA, ENCODE, Roadmap and GGR in NCBI. Using bioinformatics software and algorithms, the most comprehensive SEdb bioinformatics database about human beings is obtained through a large number of computational mining. SE Analysis Online Software Analysis Platform (http://licpathway.net/SEanalysis/index.do) is the first online super-enhancer upstream and downstream regulatory network analysis tool based on Web Platform in the field of super-enhancers. SE analysis tool (http://licpathway.net/SEanalysis/index.do) belongs to an online software analysis platform, which can provide three powerful super-enhanced upstream and downstream regulatory analysis. In addition to containing more than 330,000 superenhancers for more than 540 cells/tissues in SEdb database, SEanalysis also integrates 5042 ChIP-seq data of transcription factors from ENCODE, Remap, Cistrome, ChIP-Atlas and GTRD databases. Motif contains about 700 human transcription factors and 2880 pathways from 10 databases. With the help of powerful bioinformatics network technology, a complex regulatory network of superenhancers, downstream target genes, transcription factors and upstream signaling pathways was constructed. Based on the complex regulatory network of hundreds of cells/tissues, three regulatory analysis strategies related to superenhancers were developed: (1) downstream enhancer analysis of pathways; (2) upstream regulation analysis of superenhancers; (3) genome region analysis. 4.Subpathway Miner and other sub-pathway recognition related software platforms are cited by the high-impact top Review Journal Nature reviews cancer (SCI impact factor = 37.9), and are listed in the journal paper path recognition software list, recommended to cancer researchers in various countries to use the system. At the same time, GSEA and SPIA are among the most famous channel identification software in the world, which indicates that Subpath Miner software platform has entered the international mainstream channel identification software ranks. Subpathway Miner and other related software platforms were also cited and recommended by two top international journals in 2011, CHEMICAL REVIEWS (SCI impact factor = 40.2) and ANNUAL REVIEWS (SCI impact factor = 21.6). In addition, the platform has been cited or reported by high-impact international professional journals, such as Briefings in Bioinformatics, DRUG DISCOVERY TODAY, Clinical Pharmacoligy & Therapeutics. At present, SubpathwayMiner related analysis platform has been used by research institutions in dozens of countries, such as the United States, Britain, Germany, Japan, Canada, Korea and so on.

Educational experience (in reverse chronological order):

 2009/09-2012/07, Ph. D., Biophysics (bioinformatics), Ph. D. 2003/09-2005/07, Harbin Institute of Technology, master of computer science and technology. 1998/09-2002/07, H., Bachelor of marine engineering.

Research work experience (research and academic work experience, in reverse chronological order):

 2017/10 - up to now, Professor, School of medical information. 2012/10 - 2017/09, associate professor, School of bioinformatics and technology, School of medical information. 2009/10-2012/09, Professor, lecturer, School of bioinformatics and technology. 2005/08-2009/09, Professor, assistant professor of bioinformatics and technology.

Presiding over or participating in scientific research projects and personnel planning projects (in reverse chronological order):

 1.The National Natural Science Foundation of China (81572341), the identification of high abnormal regions of metabolic pathways in non coding RNA and its molecular interaction mechanism, 2016/1-2019/12, 678 thousand yuan, research and chair. 2.Heilongjiang Provincial Natural Science Foundation projects, F2016031, 2016/07-2019/07, integration of microRNA and mRNA expression spectrum, identify complex disease risk pathways, 60 thousand yuan, research and chair. 3.National Natural Science Foundation of China Youth Project, 3140 1127, Research on identifying complex disease risk pathways based on intra-pathway structure and inter-pathway crosstalk, 2015/1-2017/127, 200,000 yuan, in-service research and participation. 4.Yuweihan Academician's Outstanding Youth Foundation Project, no, no, 2014/07-2017/06, 300,000 yuan, in research, presided over. National Natural Science Foundation Youth Project, 31200996, Regional System Identification of Cancer Risk Metabolic Pathway Integrating High-throughput Genes, Metabolites and Pathway Structure Information, 2013/1-2015/120,000 yuan, 220,000 yuan, in-service research and hosting. 5.The project of the provincial education department, 12531295, the integrated identification method of metabolic pathways for complex disease risk, 2013/1-2015/12, 20 thousand yuan, research and hosting.

6.National Ministry of Education, Ph.D. Program, 20102307120027, Research on Metabolic Pathway Fusion Mining and Network Analysis, 2011/01-2013/12, 36,000 yuan, completed and presided over.

7.The provincial graduate student innovation fund (key) project, YJSCX2011-316HLJ, the fusion genome and metabonomics, refined the identification of metabolic pathways in complex disease risk areas, 2011/9-2012/7, 50 thousand yuan, completed problems, and applicants.

7.The provincial graduate student innovation fund (key) project, YJSCX2011-316HLJ, the fusion genome and metabonomics, refined the identification of metabolic pathways in complex disease risk areas, 2011/9-2012/7, 50 thousand yuan, completed problems, and applicants.

8.National Natural Science Foundation of China's major research project, 91029717, Fusion Histology to explore the molecular mechanism of uncontrollable inflammation into cancer, 2011/1-2013/12, 600,000, has been completed, participated.

 9.Project of National Natural Science Foundation of China, 30871394, Research on Information Fusion Method for Recognition of Functional Modules of Complex Disease Associated MicroRNAs, 2009/1-2011/120,300,000 yuan, Completed and Participated.

List of published SCI research papers (co-first author labeled#, co-author labeled *)

2019:

 1. Ning Z#, Feng C#, Song C#, Liu W, Shang D, Li M, Wang Q, Zhao J, Liu Y, Chen J,Yu X*, Zhang J*, Li C (Li Chun Quan) * .Topologically inferring active miRNA-mediated subpathways toward precise cancer classification by directed random walk. Mol Oncol. 2019 Aug 13. 2. Meng Li # , Jianmei Zhao # , Xuecang Li # , Yang Chen, Chenchen Feng,Fengcui Qian, Yuejuan Liu, Jian Zhang, Jianzhong He, Bo Ai, Ziyu Ning,Wei Liu, Xuefeng Bai, Xiaole Han, Zhiyong Wu, Xiue Xu, Zhidong Tang,Qi Pan, Liyan Xu, Chunquan Li(Li Chun Quan)*, Qiuyu Wang* and Enmin Li*.HiFreSP: A novel high-frequency sub-pathway mining approach to identify robust prognostic gene signatures.Brief Bioinform.2019 July 27.doi: 10.1093/bib/bbz078.PMID: 31350847. 3. Jianmei Zhao#,Xuecang Li#,Jincheng Guo#,Meng Li,Jian Zhang,Jiyu Ding,Shang Li,Zhidong Tang,Fengcui Qian,Yanyu Li,Qiuyu Wang,Chunquan Li(Li Chun Quan),* Enmin Li*and Liyan Xu*.ReCirc: prediction of circRNA expression and function through probe reannotation of non-circRNA microarrays.Molecular omics.2019 Mar 27.doi: 10.1039/c8mo00252e.PMID: 30916068. 4. Qian FC#, Li XC#, Guo JC#, Zhao JM, Li YY, Tang ZD, Zhou LW, Zhang J, Bai XF,Jiang Y, Pan Q, Wang QY, Li EM, Li CQ(Li Chun Quan)*, Xu LY*, Lin DC*. SEanalysis: a web tool for super-enhancer associated regulatory analysis. Nucleic Acids Res. 2019 Apr 27.pii: gkz302. doi: 10.1093/nar/gkz302. [Epub ahead of print] PubMed PMID:31028388. 5. Jiang Y, Qian F, Bai X, Liu Y, Wang Q, Ai B, Han X, Shi S, Zhang J, Li X, Tang Z, Pan Q, Wang Y, Wang F, Li C . SEdb: a comprehensive human super-enhancer database. Nucleic Acids Res. 2019 Jan 8;47(D1):D235-D243. doi: 10.1093/nar/gky1025. PubMed PMID: 30371817; PubMed Central PMCID: PMC6323980.

2018：

 6. Feng C#, Song C#, Ning Z#, Ai B, Wang Q, Xu Y, Li M, Bai X, Zhao J, Liu Y, Li X, Zhang J*, Li C(Li Chun Quan)*. ce-Subpathway: Identification of ceRNA-mediated subpathways via joint power of ceRNAs and pathway topologies. J Cell Mol Med. 2018 Nov 12. doi:10.1111/jcmm.13997. [Epub ahead of print] PubMed PMID: 30421585. 7. Jiang Y#, Jiang YY#*, Xie JJ#, Mayakonda A#, Hazawa M, Chen L, Xiao JF, Li CQ (Li Chun Quan), Huang ML, Ding LW, Sun QY, Xu L, Kanojia D, Jeitany M, Deng JW, Liao LD, Soukiasian HJ, Berman BP, Hao JJ, Xu LY, Li EM, Wang MR, Bi XG, Lin DC*, Koeffler HP. Co-activation of super-enhancer-driven CCAT1 by TP63 and SOX2 promotes squamous cancer progression. Nat Commun. 2018 Sep 6;9(1):3619. doi: 10.1038/s41467-018-06081-9. PubMed PMID: 30190462. 8. Tang Z#, Li X#, Zhao J#, Qian F, Feng C, Li Y, Zhang J, Jiang Y, Yang Y, Wang Q, Li C(Li Chun Quan)*. TRCirc: a resource for transcriptional regulation information of circRNAs. Brief Bioinform. 2018 Sep 3. doi: 10.1093/bib/bby083. [Epub ahead of print] PubMed PMID: 30184150. 9. Han J*#, Liu S#, Jiang Y#, Xu C#, Zheng B, Jiang M, Yang H, Su F, Li C(Li Chun Quan)*, Zhang Y*.Inference of patient-specific subpathway activities reveals a functional signature associated with the prognosis of patients with breast cancer. J Cell Mol Med. 2018 Jul 4. doi: 10.1111/jcmm.13720. [Epub ahead of print] PubMed PMID: 29971923. 10. Liu W#, He JZ#, Wang SH, Liu DK, Bai XF, Xu XE, Wu JY, Jiang Y, Li CQ , Chen LQ, Li EM*, Xu LY*. MASAN: a novel staging system for prognosis of patients withoesophageal squamous cell carcinoma. Br J Cancer. 2018 May 16. doi:10.1038/s41416-018-0094-x. [Epub ahead of print] PubMed PMID: 29765149. 11. Huang GW#, Xue YJ#, Wu ZY#, Xu XE, Wu JY, Cao HH, Zhu Y, He JZ, Li CQ, Li EM*, Xu LY*. A three-lncRNA signature predicts overall survival and disease-free survival in patients with esophageal squamous cell carcinoma. BMC Cancer. 2018 Feb6;18(1):147. 12. Zhang J#, Feng C#, Song C#, Ai B, Bai X, Liu Y, Li X, Zhao J, Shi S, Chen X, Su X*, Li C*. Identification and analysis of a key long non-coding RNAs (lncRNAs)-associated module reveal functional lncRNAs in cardiac hypertrophy. J Cell Mol Med. 2018 Feb;22(2):892-903. 13. Xie JJ#*, Jiang YY#, Jiang Y#, Li CQ, Chee LM, An O, Mayakonda A, Ding LW, Long L, Sun C, Lin LH, Chen L, Wu JY, Wu ZY, Cao Q, Fang WK, Yang W, Meltzer SJ, Yang H, Fullwood M, Xu LY*, Li EM*, Lin DC*, Koeffler HP. Super-Enhancer-Driven Long Non-Coding RNA LINC01503, Regulated by TP63, Is Over-Expressed and Oncogenic in Squamous Cell Carcinoma.Gastroenterology. 2018;doi: 10.1053/j.gastro.2018.02.018. PubMed PMID: 29454790.

2017：

 14.Pan Qi, Li Meng *, Qian Fengcui, Tang Zhidong, Zhao Yue, Wang Qiuyu, Li Chunquan. Biomarkers of copy number and expression information of integrin genes in identifying glioma risk pathways. Cancer, aberration, mutation, January 2017, Vol. 29, 1. 15. Lin DC#*, Dinh HQ#, Xie JJ#*, Mayakonda A#, Silva TC, Jiang YY, Ding LW, He JZ, Xu XE, Hao JJ, Wang MR, Li C, Xu LY, Li EM*, Berman BP*, Phillip Koeffler H. Identification of distinct mutational patterns and new driver genes in oesophageal squamous cell carcinomas and adenocarcinomas. Gut. 2017 Aug 31. pii: gutjnl-2017-314607. doi: 10.1136/gutjnl-2017-314607. [Epub ahead of print] PubMed PMID: 28860350. 16. Zhang HYang H#, Shang D#, Xu Y, Zhang C, Feng L, Sun Z, Shi X, Zhang Y, Han J, Su F, Li C*, Li X*. The LncRNA Connectivity Map: Using LncRNA Signatures to Connect Small Molecules, LncRNAs, and Diseases. Sci Rep. 2017 Jul 27;7(1):6655. doi: 10.1038/s41598-017-06897-3. PubMed PMID: 28751672; PubMed Central PMCID: PMC5532316. 17. Zhan XH#, Jiao JW#, Zhang HF, Li CQ, Zhao JM, Liao LD, Wu JY, Wu BL, Wu ZY, Wang SH, Du ZP, Shen JH, Zou HY, Neufeld G, Xu LY*, Li EM*. A three-gene signature from protein-protein interaction network of LOXL2- and actin-related proteins for esophageal squamous cell carcinoma prognosis. Cancer Med. 2017 Jul;6(7):1707-1719. doi: 10.1002/cam4.1096. Epub 2017 May 29. PubMed PMID: 28556501; PubMed Central PMCID: PMC5504325. 18. Han J#, Liu S#, Sun Z, Zhang Y, Zhang F, Zhang C, Shang D, Yang H, Su F, Xu Y, Li C*, Ren H*, Li X*. LncRNAs2Pathways: Identifying the pathways influenced by a set of lncRNAs of interest based on a global network propagation method. Sci Rep. 2017 Apr 20;7:46566. doi: 10.1038/srep46566. PubMed PMID: 28425476; PubMed Central PMCID: PMC5397852. 19. Song C#, Zhang J#, Qi H#, Feng C, Chen Y, Cao Y, Ba L, Ai B, Wang Q, Huang W, Li C *, Sun H*. The global view of mRNA-related ceRNA cross-talks across cardiovascular diseases. Sci Rep. 2017 Aug 31;7(1):10185. doi: 10.1038/s41598-017-10547-z. PubMed PMID: 28860540; PubMed Central PMCID: PMC5579186. 20. Li C#*, Wang Q#*, Ma J#, Shi S, Chen X, Yang H, Han J*. Integrative Pathway Analysis of Genes and Metabolites Reveals Metabolism Abnormal Subpathway Regions and Modules in Esophageal Squamous Cell Carcinoma. Molecules. 2017 Sep 22;22(10). pii: E1599. doi: 10.3390/molecules22101599. PubMed PMID: 28937628. 21. Li CQ #, Huang GW#, Wu ZY#, Xu YJ, Li XC, Xue YJ, Zhu Y, Zhao JM, Li M, Zhang J, Wu JY, Lei F, Wang QY, Li S, Zheng CP, Ai B, Tang ZD, Feng CC, Liao LD, Wang SH, Shen JH, Liu YJ, Bai XF, He JZ, Cao HH, Wu BL, Wang MR, Lin DC, Koeffler HP, Wang LD, Li X*, Li EM*, Xu LY*. Integrative analyses of transcriptome sequencing identify novel functional lncRNAs in esophageal squamous cell carcinoma. Oncogenesis. 2017 Feb 13;6(2):e297. doi: 10.1038/oncsis.2017.1. PubMed PMID: 28194033; PubMed Central PMCID: PMC5337622.

2016：

 22. Zou HY, Lv GQ, Dai LH, Zhan XH, Jiao JW, Liao LD, Zhou TM, Li CQ , Wu BL, Xu LY*, Li EM*. A truncated splice variant of human lysyl oxidase-like 2 promotes migration and invasion in esophageal squamous cell carcinoma. Int J Biochem Cell Biol. 2016 Jun;75:85-98. 23. Guo JC, Li CQ, Wang QY, Zhao JM, Ding JY, Li EM*, Xu LY*. Protein-coding genes combined with long non-coding RNAs predict prognosis in esophageal squamous cell carcinoma patients as a novel clinical multi-dimensional signature. Mol Biosyst. 2016 Sep 23. PubMed PMID: 27714034. 24. Han J#, Liu S#, Zhang Y#, Xu Y, Jiang Y, Zhang C, Li C *, Li X*. MiRSEA: Discovering the pathways regulated by dysfunctional MicroRNAs. Oncotarget. 2016 Jul 26. PubMed PMID: 27474169. 25. Shi X#, Xu Y#, Zhang C, Feng L, Sun Z, Han J, Su F, Zhang Y*, Li C *, Li X*. Subpathway-LNCE: Identify dysfunctional subpathways competitively regulated by lncRNAs through integrating lncRNA-mRNA expression profile and pathway topologies. Oncotarget. 2016 Sep 13. PubMed PMID:27634882. 26. Zhao J#, Li X#,Yao Q#, Li M, Zhang J, Ai B, Liu W, Wang Q, Feng C, Liu Y, Bai X, Song C, Li S, Li E, Xu L*, Li C *. RWCFusion: identifying phenotype-specific cancer driver gene fusions based on fusion pair random walk scoring method. Oncotarget. 2016 Aug 5. PubMed PMID: 27506935. 27. Li S, Xu Y, Sun Z, Feng L, Shang D, Zhang C, Shi X, Han J, Su F, Yang H, Zhao J, Song C, Zhang Y, Li C *, Li X*. Identification of a lncRNA involved functional module for esophageal cancer subtypes. Mol Biosyst. 2016 Aug 19. PubMed PMID: 27539139. 28. Feng C#, Zhang J#, Li X#, Ai B, Han J, Wang Q, Wei T, Xu Y, Li M, Li S, Song C, Li C *. Subpathway-CorSP: Identification of metabolic subpathways via integrating expression correlations and topological features between metabolites and genes of interest within pathways. Sci Rep. 2016 Sep 14;6:33262. 29. Song C#, Zhang J#, Liu Y, Pan H, Qi HP, Cao YG, Zhao JM, Li S, Guo J, Sun HL*, Li CQ *. Construction and analysis of cardiac hypertrophy-associated lncRNA-mRNA network based on competitive endogenous RNA reveal functional lncRNAs in cardiac hypertrophy. Oncotarget. 2016 Mar 8;7(10):10827-40.

2015：

 30. Zhang Y, Liu W, Xu Y, Li C , Wang Y, Yang H, Zhang C, Su F, Li Y*, Li X*. Identification of subtype specific miRNA-mRNA functional regulatory modules in matched miRNA-mRNA expression data: multiple myeloma as a case. Biomed Res Int. 2015 Mar 19;2015:501262. 31. Chen X, Wang Y, Wang P, Lian B, Li C , Wang J, Li X, Jiang W. Systematic Analysis of the Associations between Adverse Drug Reactions and Pathways. Biomed Res Int. 2015;2015:670949 32. Zhang C#, Li C #, Xu Y#, Feng L, Shang D, Yang X, Han J, Sun Z, Li Y*, Li X*. Integrative analysis of lung development-cancer expression associations reveals the roles of signatures with inverse expression patterns. Mol Biosyst. 2015 May; PubMed PMID: 25720795. 33. Deng L, Xu Y, Zhang C, Yao Q, Feng L, Li C *. A network-based strategy from the global perspective for identification of risk pathways in complex diseases. Prog Biochem Biophys. 2015 Jan 15;42(3):11 34. Shang D#, Yang H#, Xu Y, Yao Q, Zhou W, Shi X, Han J, Su F, Su B, Zhang C, Li C *, Li X*. A global view of network of lncRNAs and their binding proteins. Mol Biosyst. 2015 Feb;11(2):656-663. 35. Zhang J#, Wang Y#, Shang D#, Yu F, Liu W, Zhang Y, Feng C, Wang Q, Xu Y, Liu Y, Bai X, Li X, Li C *. Characterizing and optimizing human anticancer drug targets based on topological properties in the context of biological pathways. J Biomed Inform. 2015 Apr;54:132-140. 36. Liu W#, Wang Q#, Zhao J, Zhang C, Liu Y, Zhang J, Bai X, Li X, Feng H, Liao M, Wang W*, Li C *. Integration of pathway structure information into a reweighted partial Cox regression approach for survival analysis on high-dimensional gene expression data. Mol Biosyst. 2015 Jul;11(7):1876-86. 37. Lv W#, Wang Q#, Chen H#, Jiang Y#, Zheng J, Shi M, Xu Y, Han J, Li C *, Zhang R*. Prioritization of rheumatoid arthritis risk subpathways based on global immune subpathway interaction network and random walk strategy. Mol Biosyst. 2015 Oct 13;11(11):2986-97. 38. Han J#, Li C #, Yang H#, Xu Y, Zhang C, Ma J, Shi X, Liu W, Shang D, Yao Q, Zhang Y, Su F, Feng L, Li X*. A novel dysregulated pathway-identification analysis based on global influence of within-pathway effects and crosstalk between pathways. Journal of the Royal Society Interface. 2015 Jan 6;12(102):20140937. 39. Yao Q#, Xu Y#, Yang H, Shang D, Zhang C, Zhang Y, Sun Z, Shi X, Feng L, Han J, Su F, Li C *, Li X*. Global Prioritization of Disease Candidate Metabolites Based on a Multi-omics Composite Network. Sci Rep. 2015 Nov 24;5:17201. 40. Han J#, Shi X#, Zhang Y#, Xu Y, Jiang Y, Zhang C, Feng L, Yang H, Shang D, Sun Z, Su F, Li C *, Li X*. ESEA: Discovering the Dysregulated Pathways based on Edge Set Enrichment Analysis. Sci Rep. 2015 Aug 12;5:13044. doi: 10.1038/srep13044. 41. Feng L#, Xu Y#, Zhang Y#, Sun Z, Han J, Zhang C, Yang H, Shang D, Su F, Shi X, Li S, Li C *, Li X*. Subpathway-GMir: identifying miRNA-mediated metabolic subpathways by integrating condition-specific genes, microRNAs, and pathway topologies. Oncotarget. 2015 Oct 12. doi: 10.18632/oncotarget.5341. 42. Liu W#, Bai X#, Liu Y#, Wang W, Han J, Wang Q, Xu Y, Zhang C, Zhang S, Li X, Ren Z, Zhang J*, Li C *. Topologically inferring pathway activity toward precise cancer classification via integrating genomic and metabolomic data: prostate cancer as a case. Sci Rep. 2015 Aug 19;5:13192.

2014：

 43. Li J#, Zhang Y#, Wang Y#, Zhang C, Wang Q, Shi X, Li C , Zhang R*, Li X*. Functional combination strategy for prioritization of human miRNA target. Gene. 2014;533(1):132-141. 44. Chen S#, Li C #, Wu B, Zhang C, Liu C, Lin X, Wu X, Sun L, Chen B, Zhong Z*, Xu L*, Li E. Identification of differentially expressed genes and their subpathways in recurrent versus primary bone giant cell tumors. Int J Oncol. 2014 Sep;45(3):1133-1142. 45. Li J, Li C , Han J, Zhang C, Shang D, Yao Q, Zhang Y, Xu Y, Liu W, Zhou M, Yang H, Su F, Li X*. The detection of risk pathways, regulated by miRNAs, via the integration of sample-matched miRNA-mRNA profiles and pathway structure. J Biomed Inform. 2014 June;49:187-197 46. Shang D#, Li C #, Yao Q#, Yang H, Xu Y, Han J, Li J, Su F, Zhang Y, Zhang C, Li D*, Li X*. Prioritizing Candidate Disease Metabolites Based on Global Functional Relationships between Metabolites in the Context of Metabolic Pathways. PLoS One. 2014 Aug 25;9(8):e104934. 47. Zhang C#, Li C #, Li J#, Han J, Shang D, Zhang Y, Zhang W, Yao Q, Han L, Xu Y, Yan W, Bao Z, You G, Jiang T*, Kang C*, Li X*. Identification of miRNA-mediated core gene module for glioma patient prediction by integrating high-throughput miRNA, mRNA expression and pathway structure. PLoS One. 2014 May 8;9(5):e96908. 48. Wu B#, Li C #, Du Z, Zhou F, Xie J, Luo L, Wu J, Zhang P, Xu L*, Li E*. Functional analysis of the mRNA profile of neutrophil gelatinaseassociated lipocalin overexpression in esophageal squamous cell carcinoma using multiple bioinformatic tools. Mol Med Rep. 2014 Oct;10(4):1800-1812. 49. Li F#, Xu Y#, Shang D, Yang H, Liu W, Han J, Sun Z, Yao Q, Zhang C, Ma J, Su F, Feng L, Shi X, Zhang Y, Li J, Gu Q, Li X*, Li C *. MPINet: metabolite pathway identification via coupling of global metabolite network structure and metabolomic profile. Biomed Res Int. 2014;2014:325697. 50. Wu B#, Li C#, Du Z, Yao Q, Wu J, Feng L, Zhang P, Li S, Xu L*, Li E*. Network based analyses of gene expression profile of LCN2 overexpression in esophageal squamous cell carcinoma. Sci Rep. 2014 Jun 23;4:5403.

2013：

 51. Wu B#, Li C #, Zhang P, Yao Q, Wu J, Han J, Liao L, Xu Y, Lin R, Xiao D, Xu L, Li E*, Li X*. Dissection of miRNA-miRNA interaction in esophageal squamous cell carcinoma. PLoS One. 2013;8(9):e73191. 52. Zhang F#, Gao B#, Xu L#, Li C , Hao D, Zhang S, Zhou M, Su F, Chen X, Zhi H, Li X*. Allele-specific behavior of molecular networks: understanding small-molecule drug response in yeast. PLoS One. 2013;8(1):e53581. 53. Shi H, Xu J, Zhang G, Xu L, Li C , Wang L, Zhao Z, Jiang W, Guo Z*, Li X*. Walking the interactome to identify human miRNA-disease associations through the functional link between miRNA targets and disease genes. BMC systems biology. 2013;7:101. 54. Wu B#, Luo L#, Li C , Xie J, Du Z, Wu J, Zhang P, Xu L*, Li E*. Comprehensive bioinformation analysis of the mRNA profile of fascin knockdown in esophageal squamous cell carcinoma. Asian Pacific journal of cancer prevention : APJCP. 2013;14(12):7221-7227. 55. Liu W#, Li C #, Xu Y, Yang H, Yao Q, Han J, Shang D, Zhang C, Su F, Li X, Xiao Y, Zhang F, Dai M*, Li X*. Topologically inferring risk-active pathways toward precise cancer classification by directed random walk. Bioinformatics. 2013;29(17):2169-2177. 56. Li C #, Han J#, Yao Q#, Zou C, Xu Y, Zhang C, Shang D, Zhou L, Sun Z, Li J, Zhang Y, Yang H, Gao X*, Li X*. Subpathway-GM: identification of metabolic subpathways via joint power of interesting genes and metabolites and their topologies within pathways. Nucleic acids research. 2013;41(9):e101.

2012：

 57. Li C #, Shang D#, Wang Y#, Li J, Han J, Wang S, Yao Q, Wang Y, Zhang Y, Zhang C, Xu Y, Jiang W, Li X*. Characterizing the network of drugs and their affected metabolic subpathways. PLoS One. 2012;7(10):e47326. 58. Li C #, Han J#, Shang D#, Li J, Wang Y, Zhang Y, Yao Q, Zhang C, Li K*, Li X*. Identifying disease related sub-pathways for analysis of genome-wide association studies. Gene. 2012;503(1):101-109. 59. Qiu F#, Xu Y#,*, Li K#, Li Z#, Liu Y#, DuanMu H, Zhang S, Chang Z, Zhou Y, Zhang R, Li C , Zhang Y, Liu M, Li X. CNVD: text mining-based copy number variation in disease database. Human mutation. 2012;33(11):E2375-81.

2011：

 60. Qiao W, Cheng H, Li C , Jin H, Yang S, Li X, Zhang Y*. Identification of pathways involved in paclitaxel activity in cervical cancer. Asian Pacific journal of cancer prevention : APJCP. 2011;12(1):99-102. 61. Li X#*, Li C #, Shang D#, Li J, Han J, Miao Y, Wang Y, Wang Q, Li W, Wu C, Zhang Y, Li X, Yao Q. The implications of relationships between human diseases and metabolic subpathways. PLoS One. 2011;6(6):e21131. 62. Xu J#, Li C#, Li Y, Lv J, Ma Y, Shao T, Xu L, Wang Y, Du L, Zhang Y, Jiang W, Li C , Xiao Y, Li X*. MiRNA-miRNA synergistic network: construction via co-regulating functional modules and disease miRNA topological features. Nucleic acids research. 2011;39(3):825-836. 63. Li J#, Gong B#, Chen X, Liu T, Wu C, Zhang F, Li C , Li X*, Rao S*. DOSim: an R package for similarity between diseases based on Disease Ontology. BMC bioinformatics. 2011;12:266.

2009：

 64. Li C , Li X*, Miao Y, Wang Q, Jiang W, Xu C, Li J, Han J, Zhang F, Gong B, Xu L. SubpathwayMiner: a software package for flexible identification of pathways. Nucleic acids research. 2009;37(19):e131.

Teaching paper

 Li Chunquan and Feng Chenchen. To explore the cultivation of innovation and practical ability of bioinformatics in medical colleges. The Straits technology and industry. Host: Ministry of science and technology, cross strait science and technology exchange center. 2017.04. Fourth Li Chunquan. Discussion on extracurricular training strategy of innovative thinking of bioinformatics undergraduates. Straits science and technology and industry. Host: Ministry of science and technology, cross strait science and technology exchange center. 2017.09. Ninth issue. Li Chunquan, Li Xuecang and Lu Peng Ju. To guide the reform of higher education with double creation education. "Red child". Organizer: China society, economy and Culture Exchange Association. 2017.10. 433rd issue.

1. National Natural Science Foundation of China, 81572341. High abnormal area recognition and molecular interaction mechanism of non coding RNA metabolic pathway in esophageal cancer, 2016/1-2019/12, 678 thousand yuan, research and chair.

2. National Natural Science Foundation Youth Project, 31200996, Regional System Identification of Cancer Risk Metabolic Pathway Integrating High-throughput Genes, Metabolites and Pathway Structural Information, 2013/1-2015/120,000 yuan, in-service research and hosting.

3. Provincial Natural Science Foundation projects, F2016031, 2016/07-2019/07, integration of microRNA and mRNA expression spectrum to identify complex disease risk pathways, 60 thousand yuan, in research, chair.

4. No, no, no, 2014/07-2017/06, 300,000 yuan, in research and hosting the outstanding youth training fund project of Academicians of Uygur and Han Dynasties.