Dr. Xiaojian Shao

Dr. Xiaojian Shao

Research Officer at NRC

Publications

You can also find my articles on my Google Scholar profile.

Peer-reviewed Journal Publications (* co-first author, # co-corresponding author)

  1. Xiaojian Shao#, Sangeetha Vishweswaraiah, Miroslava Čuperlović-Culf et al. Dementia with Lewy bodies post-mortem brains reveal differentially methylated CpG sites with biomarker potential. Nature Communications Biology, 2022
  2. Mylarappa Ningappa*, Xiaojian Shao*, Chethan Ashokkumar, Qingyong Xu, Adriana Zeevi, Elin Grundberg, Tomi Pastinen, Rakesh Sindhi. The role of dynamic DNA methylation in liver transplant rejection in children. Transplantation Direct 2022.
  3. Xiaojian Shao#, Catherine Le Stunff, Warren Cheung, Tony Kwan, Mark Lathrop, Tomi Pastinen, Pierre Bougnères. Differentially methylated CpGs in response to growth hormone administration in children with idiopathic short stature. Clinical Epigenetics 2022, 14(1):1-12.
  4. Xiang Li, Xiaojian Shao, et al. Blood DNA methylation at TXNIP and glycemic changes in response to weight-loss diet interventions: The POUNDS lost trial. International Journal of Obesity 2022, 46(6):1122-1127
  5. Yang Guo, Fatemeh Esfahani, Xiaojian Shao, et al. Integrative COVID-19 biological network inference with probabilistic core decomposition, Briefings in Bioinformatics, 2021; bbab455
  6. Yixiao Zeng, Kaiqiong Zhao, Kathleen Oros Klein, Xiaojian Shao, et al. Thousands of CpGs Show DNA Methylation Differences in ACPA-Positive Individuals. Genes, 2021, 12(9): 1349.
  7. Xiaolin Huang, Xiaojian Shao, et al. The impact of lockdown timing on COVID-19 transmission across US counties. EClinicalMedicine, 2021, 38: 101035.
  8. Romain Lambrot, Donovan Chan, Xiaojian Shao, et al. Whole-genome sequencing of H3K4me3 and DNA methylation in human sperm reveals regions of overlap linked to fertility and development. Cell Reports, 2021, 36(3): 109418.
  9. Mingju Cao*, Xiaojian Shao*, et al. High-resolution analyses of human sperm dynamic methylome reveals thousands of novel age-related epigenetic alterations. Clinical Epigenetics 2020, 12(1):1-16.
  10. Donovan Chan*, Xiaojian Shao*, et al. Customized MethylC-Capture Sequencing to Evaluate Variation in the Human Sperm DNA Methylome Representative of Altered Folate Metabolism. Environmental Health Perspectives 2019. 127 (8), 087002.
  11. Xiaojian Shao, Marie Hudson, et al. Rheumatoid arthritis-relevant DNA methylation changes identified in ACPA-positive asymptomatic individuals using methylome capture sequencing. Clinical Epigenetics 2019, 11 (1), 110.
  12. Yan Xu, Xingyan Li, Yingxia Yang, Chunhui Li, Xiaojian Shao. Human age prediction based on DNA methylation of non-blood tissues. Computer Methods and Programs in Biomedicine. 2019, 171: 11-18.
  13. Fiona Allum, Åsa K. Hedman, Xiaojian Shao, et al. Dissecting features of epigenetic variants underlying cardiometabolic risk using full-resolution epigenome profiling in regulatory elements. Nature Communications. 2019, 10 (1209).
  14. Yong Tao, et al. (Xiaojian Shao is listed as a co-author). Aging-like Spontaneous Epigenetic Silencing Facilitates Wnt Activation, Stemness, and BrafV600E-Induced Tumorigenesis. Cancer Cell. 2019, 35(2)
  15. Xue Bai, Zhenzhen Liu, Xiaojian Shao, et al. The heterogeneity of plasma miRNA profiles in hepatocellular carcinoma patients and the exploration of diagnostic circulating miRNAs for hepatocellular carcinoma. PloS One. 2019, 14(2).
  16. Mathieu Bourgey, Rola Dali, et al. (Xiaojian Shao is listed as a co-author). GenPipes: an open-source framework for distributed and scalable genomic analyses. GigaScience 2019, 8 (6), giz037.
  17. Warren Cheung*, Xiaojian Shao*, Andréanne Morin* et al. Functional variation in allelic methylomes underscores a strong genetic contribution and reveals novel epigenetic alterations in the human epigenome. Genome Biology 2017, 18:50.
  18. Simone Ecker et al. (Xiaojian Shao is listed as one co-author). Genome-wide analysis of differential transcriptional and epigenetic variability across human immune cell types. Genome Biology 2017, 18:18
  19. Lu Chen, Bing Ge et al. (Xiaojian Shao is listed as one formal analysis co-author). Genetic Drivers of Epigenetic and Transcriptional Variation in Human Immune Cells. Cell 2016, Vol. 167:5.
  20. Xiaofei Yang, Xiaojian Shao, Lin Gao, Shihua Zhang. Comparative DNA methylation analysis to decipher common and cell type-specific patterns among multiple cell types. Briefings in Functional Genomics 2016, 15 (6): 399-407. (Invited Review)
  21. Yang Zou, Xiaojian Shao, Dong Dong. Inferring the determinants of protein evolutionary rates in mammals. Gene, Feb 2016.
  22. Toby Dylan Hocking, Patricia Goerner-Potvin, Andreanne Morin, Xiaojian Shao, Tomi Pastinen and Guillaume Bourque. Optimizing ChIP-seq peak detectors using visual labels and supervised machine learning. Bioinformatics, 2016.
  23. Stephan Busche*, Xiaojian Shao*, et al. Population whole-genome bisulfite sequencing across two tissues highlights environment as principal source of human methylome variation. Genome Biology 2015, 16:290.
  24. Fiona Allum*, Xiaojian Shao*, et al. Characterization of functional methylome by next-generation capture sequencing identifies novel disease associated variants. Nature Communications 2015, 6:7211.
  25. Xiaofei Yang, Xiaojian Shao, Lin Gao, Shihua Zhang. Systematic DNA methylation analysis of multiple cell lines reveals common and specific patterns within and across tissues of origin. Human Molecular Genetics 2015, 24(15):4373-4384.
  26. Xiaojian Shao, Cuinyun Zhang, Ming-an Sun, Xuemei Lu, and Hehuang Xie. Genome-wide assessment of DNA methylation pattern variation during cellular differentiation and reprogramming. BMC Genomics 2014, 15: 978-988. Highly accessed.
  27. Lei Zhao, et al. (Xiaojian Shao is listed as a co-author). The dynamics of DNA methylation fidelity during mouse embryonic stem cells self-renewal and differentiation. Genome Research 2014, 24(8):1296-307.
  28. Yan Xu, Xiaojian Shao, et al., iSNO-AAPair: incorporating amino acid pairwise coupling into PseAAC for predicting cysteine S-nitrosylation sites in proteins. Peer J. 2013; 1: e171.
  29. Chuanhua Zhang, Xiaojian Shao#, Dewei Li. Knowledge-based support vector classification based on C-SVC. Procedia Computer Science 2013,17: 1083–1090.
  30. Jianlin He, Xinxi Sun, Xiaojian Shao, Liji Liang, and Hehuang Xie. DMEAS: DNA Methylation Entropy Analysis Software. Bioinformatics 2013, 29(16): 2044-2045.
  31. Xiaojian Shao*, Chris Tan*, et al. A regression framework incorporating quantitative and negative interaction data improves quantitative prediction of PDZ domain-peptide interaction from primary sequence. Bioinformatics 2011, 27(3): 383-390.
  32. Dong Dong*, Xiaojian Shao*, Naiyang Deng and Zhaolei Zhang. Gene expression variations are predictive for stochastic noise. Nucleic Acids Research 2011, 39(2): 403-413.
  33. Dong Dong, Xiaojian Shao and Zhaolei Zhang. Different effects of chromatin regulators and transcription factors on gene regulation: A nucleosomal perspective. Bioinformatics 2011, 27(2): 147-152.
  34. Xiaojian Shao, et al. Predicting DNA- and RNA-binding Proteins from Sequences with Kernel Methods. Journal of Theoretical Biology 2009, 258(2): 289-293.
  35. Hua Duan, Xiaojian Shao, et al. An Incremental Learning Algorithm for Lagrangian Support Vector Machines. Pattern Recognition Letters 2009, 30(15): 1384-1391.
  36. Tingting Gao, Yingjie Tian, Xiaojian Shao, Naiyang Deng. Accurate Prediction of Translation Initiation Sites by Universum SVM. In Proceedings of 2nd International Symposium on Optimization and Systems Biology, Lecture Notes in Operations Research, Vol 9, pp. 279-286, Beijing, 2008.
  37. Xiaojian Shao, Yingjie Tian, Naiyang Deng. SVM-based Automatic Classification for Protein Structural Domain. In Proceedings of 1st International Symposium on Optimization and Systems Biology, Lecture Notes in Operations Research, Vol. 7, pp. 341-350, Beijing, 2007.
  38. Xiaojian Shao, Guoping He. Lagrange Support Vector Regression. Intelligent Information Management Systems and Technologies 2005, 1(3): 434-440.

Chapter in Book

1．Mingan Sun, Xiaojian Shao, Yejun Wang, Microarray Data Analysis for Transcriptome Profiling. Methods Molecular Biology, Vol. 1751, Yejun Wang and Ming-an Sun (Eds): Transcriptome Data Analysis: Methods and Protocols, 978-1-4939-7709-3, 421690_1_En, (13), 2018
2．Xiaojian Shao#, Mingan Sun. Predicting Gene Expression Noise from Gene Expression Variations. Methods Molecular Biology, Vol. 1751, Yejun Wang and Ming-an Sun (Eds): Transcriptome Data Analysis: Methods and Protocols, 978-1-4939-7709-3, 421690_1_En, (13), 2018