Xiaogang Zhong’s Publications

  1. Timofeeva OA, Palechor-Ceron N, Li G, Yuan H, Krawczyk E, Zhong X, Liu G, Upadhyay G, Dakic A, Yu S, Fang S, Choudhury S, Zhang X, Ju A, Lee MS, Dan HC, Ji Y, Hou Y, Zheng YL, Albanese C, Rhim J, Schlegel R, Dritschilo A, Liu X. Conditionally reprogrammed normal and primary tumor prostate epithelial cells: a novel patient-derived cell model for studies of human prostate cancer. Oncotarget, 2016. doi:10.18632/oncotarget.13937.
  2. Alamri AM, Kang K, Groeneveld S, Wang W, Zhong X, Kallakury B, Hennighausen L, Liu X, Furth PA. Primary cancer cell culture: mammary-optimized vs conditional reprogramming. Endocr Relat Cancer, 2016. doi: 10.1530/ERC-16-0071.
  3. Alothman S, Wang W, Goerlitz D, Islam M, Zhong X, Kishore A, Azhar R, Kallakury B, Furth PA. Responsiveness of Brca1 and Trp53 deficiency induced mammary preneoplasia to selective estrogen modulators versus an aromatase inhibitor in Mus musculus. Cancer Prevention Research, 2016.
  4. Mapstone M, Cheema AK, Zhong X, Fiandaca MS, Federo HJ. Biomarker validation: Methods and matrix matter.Alzheimer’s & Dementia, 2016. doi:10.1016/j.jalz.2016.11.004.
  5. Fiandaca MS, Zhong X, Cheema AK, Orquiza MH, Chidambaram S, Tan MT, Gresenz CR, FitzGerald KT, Nalls MA, Singleton AB, Mapstone M, Federoff HJ. Plasma 24-metabolite Panel Predicts Preclinical Transition to Clinical Stages of Alzheimer’s Disease. Front Neurol, 2015. doi:10.3389/fneur.2015.00237.
  6. Fiandaca MS, Mapstone M, Zhong X, Cheema AK, Federo HJ. The Era of Blood-derived Biomarkers Defining Preclinical Alzheimer’s Disease is Ready for Prime Time!! Neurotherapeutics, 2015, 12 (3), 679.
  7. Mapstone M, Cheema AK, Fiandaca MS, Zhong X, Mhyre TR, MacArthur LH, Hall WJ, Fisher SG, Peterson DR, Haley JM, Nazar MD, Rich SA, Berlau DJ, Peltz CB, Tan MT, Kawas CH and Federo HJ. Plasma phospholipids identify antecedent memory impairment in older adults. Nature Medicine, 2014, 20, 415418. doi:10.1038/nm.3466.
  8. Cheema AK, Pathak R, Zandkarimi F, Kaur P, Alkhalil L, Singh R, Zhong X, Ghosh S, Aykinburns N, and Hauer-Jensen M. Liver Metabolomics Reveals Increased Oxidative Stress and Fibrogenic Potential in Gfrp Transgenic Mice in Response to Ionizing Radiation. J. Proteome Res., 2014, 13 (6), 30653074.  doi:10.1021/pr500278t.
  9. Wang Y, Thomas A, Lau C, Rajan A, Zhu Y, Killian K, Lacopo P, Pham T, Morrow B, Zhong X, Meltzer P, and Giaccone G. Mutations in epigenetic regulatory genes are common in thymic carcinomas. Sci Rep, 2014. doi:10.1038/srep07336.
  10. Yuan A, Zhong X and Bonney GE. A Likelihood Model for Linkage Analysis of Genetic Traits. Austin. Biom and Biostat, 2014;1(1): 7.

  1. Mapstone M, Fiandaca MS, Cheema AK, Zhong X, Tan MT, Kawas C, Federo HJ. A Plasma-based Biomarker Panel Identies Preclinical Alzheimer’s Disease. Neurology April 8, 2014 vol. 82 no. 10 Supplement S38.001.
  2. Zhong X, Marchionni L, Cope L, Edwin IS, Elizabeth G, Edward GW, Giovanni P. Optimized cross-study analysis of microarray-based predictors. A chapter of the book “Advances in Statistical Bioinformatics: Models and Integrative Inference for High-Throughput Data”, edited by Kim-Anh Do, Zhaohui Steve Qin, and Marina Vannucci. Cambridge University Press, 2013.
  3. Ding J, Trippa L, Zhong X, Parmigiani G. Hierarchical Bayesian analysis of somatic mutation data in cancer. The Annals of Applied Statistics, 7 (2013), no. 2, 883{903. doi:10.1214/12- AOAS604.
  4. Provost E, Zhong X, Ashar F, Nguyen E, Parsons MJ, Leach SD. Development. (2012). Ribosomal biogenesis genes play an essential and p53-independent role in pancreas development.139:e1705.
  5. Jenkinson G, Zhong X, Goutsias J. BMC Bioinformatics, (2010). Thermodynamically consistent Bayesian analysis of closed biochemical reaction systems. Vol. 11, No. 547.
  6. Zhong X, Goutsias J. Johns Hopkins University, Department of Biostatistics Working Papers. (2009). Bayesian analysis of SILAC dynamics for closed biochemical reaction systems. paper 255.
  7. Zhong X and Parmigiani G. Johns Hopkins University, Department of Biostatistics Working Papers. (2009). Model-based identification of outliers in gene expression. paper 216.
  8.  Garrett-Mayer E, Parmigiani G, Zhong X, Cope L, Gabrielson E. Biostatistics. (2008). Cross-study validation and combined analysis of gene expression microarray data.9(2):333-354.
  9. Cope L, Zhong X, Garrett-Mayer E, Gabrielson E, Parmigiani G. Johns Hopkins University, Department of Biostatistics Working Papers. (2005). Cross-study validation of a molecular profile for BRCA1-linked breast cancers.  paper 71.
  10. Cope L, Zhong X, Garrett-Mayer E, Parmigiani G. Stat Appl Genet Mol Biol. (2004). MergeMaid: R tools for merging and cross-study validation of gene expression data.3:Article29.