Xiaoqi Zheng
Xiaoqi Zheng
(0)

BaseInfo

  • Gender：male
  • Appointment Post：
  • Academic Credentials：
  • Tel：2164323734
  • Email：xqzheng@shnu.edu.cn
  • Address：100 Guilin road
  • Department：Department of mathematics
  • Degree：
  • Graduate School：
  • Office Location：Shanghai

ResearchDirection

  • DNA Methylation and tumor heterogeneity

    Tumor tissues are not pure but contain unknown quantities of normal cells. The normal contamination in the tumor sample complicates the differential methylation calling between tumor and normal. Our purpose here is to identify tumor purity and differentially methylated regions (DMR) from only tumor samples.

    Furthermore, even in pure tumor tissues, different cells could have different methylation patterns due to tumor heterogeneity. We aim to identify methylation signature of different tumor subclone and deconvolute subclone structure from methylation profile of tumor tissues.


  • Computational methods in precision medicine

    The ability to predict the response of a cancer patient to a therapeutic agent is a major goal in modern oncology that should ultimately lead to personalized treatment. Our goal is to investigate the molecular mechanism of cancer cells to drugs, and identify cancer patients that might respond better to certain cancer drugs based on the genetic, epigenetic, and gene expression status of their tumor cells.

AcademicAchievement

AcademicAchievement

2016

1.X Zheng*, N Zhang, HJ Wu, H Wu*, Estimating and accounting for tumor   purity in the analysis of DNA methylation data from cancer studies, Genome   Biology, in revision.

2.ZQ Wu, XY Li, T Ni, N Lu, T An, R Fu, RG Rowe, Y Lin, A   Scherer, T Feinberg, SX Liu, QL Guo, X Zheng, SJ   Weiss*, Snail1-Dependent p53 Repression Regulates Expansion and Activity of   Tumor-Initiating Cells in Breast Cancer, Nature Cell Biology,   2016, Accepted.

3.X Liu, J Yang, Y Zhang, Y Fang, F Wang, J Wang, X   Zheng* J Yang*: A systematic study on drug response associated genes   using baseline gene expressions of the Cancer Cell Line Encyclopedia, Scientific   Reports, 2016, 6:22811

4.Y Li, Q Liu, X Zheng*: DUC-Curve, a   Highly Compact 2D Graphical Representation of DNA Sequences and Its   Application in Sequence Alignment , Physica A,   2016, 456:256-270.

5.F Wang, N Zhang, J Wang, H Wu*, X Zheng*:   Tumor purity and differential methylation in cancer epigenomics, Briefings   in Functional Genomics, 2016 doi: 10.1093/bfgp/elw016.

2015

6.N Zhang#, HJ Wu#, W Zhang, J Wang, H Wu*, X   Zheng*: Predicting tumor purity from methylation microarray   data Bioinformatics, 2015, 31(21):3401–3405.

7.N Zhang#, H Wang#, Y Fang, J Wang*, X Zheng*,   XS Liu*: Predicting anticancer drug responses using a duallayer integrated   cell line-drug network model, PLoS Computational Biology,   2015, 11:e1004498.

8.H Wang#, X Zheng#, T Fei, J Wang, X Li,   Y Liu, F Zhang: Towards pathway-centric cancer therapies via pharmacogenomic   profiling analysis of ERK signalling pathway. Clinical and   translational medicine2015, 4(1):1-9

9.Z Dong#, N Zhang#, C Li, H Wang, Y Fang, J Wang, X   Zheng*: Anticancer drug sensitivity prediction in cell lines from   baseline gene expression through recursive feature selection BMC   cancer, 2015,15(1):489

2014

10.Zheng X#, Zhao Q#, Wu H-J#, Li W, Wang H, Meyer CA, Qin QA, Xu H,   Zang C, Jiang P*, Zhang Y*, Liu XS*: MethylPurify: tumor purity deconvolution   and differential methylation detection from single tumor DNA   methylomes. Genome Biology 2014, 15:419. [Link]

11.Li L, Yu S, Xiao W, Li Y, Huang L, Zheng X*,   Zhou S*, Yang H*: Sequence-based identification of recombination spots using   pseudo nucleic acid representation and recursive feature extraction by linear   kernel SVM. BMC bioinformatics 2014,   15:340. [Link]

12.Li Y, Liu Q, Zheng X*, He PA: UC‐Curve: A highly compact 2D graphical representation of   protein sequences. International Journal of Quantum Chemistry 2014,   114:409-415.

13.Li L, Yu S, Xiao W, Li Y, Hu W, Huang L, Zheng X*,   Zhou S, Yang H: Protein submitochondria localization from integrated sequence   repesentation and SVM-based backward feature extraction. Mol   BioSyst 2014.

14.Yu X, Gao H, Zheng X, Li C, Wang J: A computational method of   predicting regulatory interactions in Arabidopsis based on gene expression   data and sequence information. Computational biology and   chemistry 2014, 51:36-41.

2013

15.Zhu J, Qin Y, Liu T, Wang J, Zheng X*:   Prioritization of candidate disease genes by topological similarity between   disease and protein diffusion profiles. BMC bioinformatics 2013,   14:S5.

2012

16.Yu X, Zheng X, Meng L, Li C, Wang J: A Support Vector Machine   Based Method to Predict Success for Polymerase Chain Reactions. Combinatorial   chemistry & high throughput screening 2012, 15:486-491.

17.Yu X, Zheng X*, Liu T, Dou Y, Wang J:   Predicting subcellular location of apoptosis proteins with pseudo amino acid   composition: approach from amino acid substitution matrix and auto covariance   transformation. Amino acids 2012,   42:1619-1625.

18.Liu T, Geng X, Zheng X*, Li R, Wang J:   Accurate prediction of protein structural class using auto covariance   transformation of PSI-BLAST profiles. Amino acids 2012,   42:2243-2249.

19.Li Y, Qin Y, Zheng X*, Zhang Y: Three‐unit semicircles curve: A compact 3D graphical representation   of DNA sequences based on classifications of nucleotides. International   Journal of Quantum Chemistry2012, 112:2330-2335.

20.Li L, Zhang Y, Zou L, Li C, Yu B, Zheng X*,   Zhou Y*: An ensemble classifier for eukaryotic protein subcellular location   prediction using gene ontology categories and amino acid   hydrophobicity. PloS one2012, 7:e31057.

2011

21.Zheng X, Liu T, Yang Z, Wang J: Large cliques in Arabidopsis gene   coexpression network and motif discovery. Journal of plant   physiology 2011, 168:611-618.

22.Yu X, Liu T, Zheng X*, Yang Z, Wang J:   Prediction of regulatory interactions in Arabidopsis using gene-expression   data and support vector machines. Plant Physiology and   Biochemistry 2011, 49:280-283.

23.Wang W, Geng X, Dou Y, Liu T, Zheng X*:   Predicting protein subcellular localization by pseudo amino acid composition   with a segment-weighted and features-combined approach. Protein   and peptide letters2011, 18:480-487.

24.Li C, Ma H, Zhou Y, Wang X, Zheng X:   Similarity analysis of DNA sequences based on the weighted pseudo‐entropy. Journal of computational chemistry 2011,   32:675-680.

25.25. Dou Y, Geng X, Gao H, Yang J, Zheng X,   Wang J: Sequence conservation in the prediction of catalytic sites. The   protein journal 2011, 30:229-239.

2010

26.Zheng X, Li C, Wang J: An information‐theoretic approach to the prediction of protein structural   class. Journal of computational chemistry 2010,   31:1201-1206.

27.Liu T, Zheng X*, Wang J: Prediction of   protein structural class for low-similarity sequences using support vector   machine and PSI-BLAST profile. Biochimie 2010,   92:1330-1334.

28.Liu T, Zheng X*, Wang J: Prediction of   protein structural class using a complexity-based distance measure. Amino   acids 2010, 38:721-728.

29.Liu T, Zheng X*, Wang C, Wang J:   Prediction of subcellular location of apoptosis proteins using pseudo amino   acid composition: an approach from auto covariance transformation. Protein   and peptide letters2010, 17:1263-1269.

30.Li C, Li Z, Zheng X, Ma H, Yu X: A   generalization of Lempel-Ziv complexity and its application to the comparison   of protein sequences. Journal of mathematical chemistry 2010,   48:330-338.

31.Dou Y, Zheng X, Yang J, Wang J:   Prediction of catalytic residues based on an overlapping amino acid   classification. Amino acids 2010,   39:1353-1361.

32.Dou Y, Zheng X, Wang J: Several   appropriate background distributions for entropy-based protein sequence   conservation measures. Journal of theoretical biology 2010,   262:317-322.

2009

33.Zheng X, Qin Y, Wang J: A Poisson model of sequence comparison and   its application to coronavirus phylogeny. Mathematical   biosciences 2009, 217:159-166.

34.Zheng X, Liu T, Wang J: A complexity-based method for predicting   protein subcellular location. Amino acids 2009,   37:427-433.

35.Zheng X, Li C, Wang J: A complexity-based measure and its   application to phylogenetic analysis. Journal of mathematical   chemistry 2009, 46:1149-1157.

36.Zheng X, Dou Y, Wang J: Phylogenetic inference from binary sequences   reduced by primary DNA sequences. Journal of mathematical   chemistry 2009, 46:1137-1148.

37.Li C, Yu X, Yang L, Zheng X, Wang Z:   3-D maps and coupling numbers for protein sequences. Physica   A: Statistical Mechanics and its Applications 2009,   388:1967-1972.

38.Dou Y, Zheng X, Wang J: Prediction of   catalytic residues using the variation of stereochemical properties. The   protein journal 2009, 28:29-33.

2008

39.Wang J, Zheng X*: Comparison of protein   secondary structures based on backbone dihedral angles. Journal   of theoretical biology 2008, 250:382-387.

40.Wang J, Zheng X*: WSE, a new sequence   distance measure based on word frequencies. Mathematical   biosciences 2008, 215:78-83.

  


Invited talks

  • “Tumor purity estimation and differential methylation analysis in cancer research”, The 14th China-Japan-Korea Bioinformatiics Training Course & Symposium , Xiamen, August 19-20, 2016.

  • “Tumor purity estimation and differential methylation analysis in cancer research”, The 4th Institute of Mathematical Statistics Asia Pacific Rim Meeting, The Chinese University of Hong Kong, June 27-30, 2016.

  • “基于DNA甲基化的肿瘤细胞纯度估计模型”, 2015年“大数据与生物信息学”学术年会, Dec. 18, 2015.

  • “Exploring genetic and epigenetic data in Cancer research: two case studies”, Tsinghua-Sanya Workshop on Big Data: Opportunities, Challenges and Innovations, Dec. 27 – Dec. 30, 2014.

  • “MethylPurify: tumor purity deconvolution and differential methylation detection from single tumor DNA methylomes”, The 8th International Conference on Systems Biology, Qingdao, 2014, 10.26.

  • “MethylPurify: tumor purity deconvolution and differential methylation detection from tumor DNA methylomes”, Genomics Get Together, Harvard School of Public Health, 2014, 1.17.

  • “A statistical approach for detecting tumor subclone through single-base resolution DNA methylation data”, CFCE retreat, 2013, 7.9.

TeachingWORK

  • Fall 2016, Advanced Algebra, Shanghai Normal University

  • Fall 2015, Probability Theory, Shanghai Normal University

  • Fall 2014, Programing Platforms in Computational Biology, Shanghai Normal University

  • Fall 2014, Bioinformatics (three courses), Tongji University

  • Spring 2014, Statistical learning and computational biology, Shanghai Normal University

  • Fall 2010, Graph Theory with Application, Shanghai Normal University

  • Fall 2011, Complex Variables Functions, Shanghai Normal University

  • Spring 2011, Advanced Mathematics, Shanghai Normal University

  • Fall 2010, Linear Algebra, Shanghai Normal University

  • Fall 2009, Combinatorics and Graph Theory, Shanghai Normal University

HonorReward

SocialAppointments

Editorial activities

  • Editor for Computational and Mathematical Methods in Medicine

  • Reviewer for Genome Biology, Molecular Biology and Evolution, Nucleic Acids Research, Bioinformatics, BMC Bioinformatics, PLoS ONE, Journal of Theoretical Biology, Journal of Biomedical Informatics, Journal of Bioinformatics and Computational Biology, Amino Acids

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