汪国华

单位职称

学校：东北林业大学 专业：计算机与控制工程学院 职务/职称：院长/教授

邮箱

ghwang@nefu[DOT]edu.cn

研究方向

生物信息学, 生物大数据分析与管理, 基因组测序数据挖掘算法, 计算表观遗传学, 单细胞数据分析算法与系统, 医学人工智能、 转化医学信息学。

获得的学术荣誉称号

计算机学会优秀博士论文奖提名

已入选的人才计划

2022年度国家杰青

工作经历

哈尔滨工业大学 2004年7月 - 至今

计算机科学与技术学院

2004年7月—2009年9月:哈尔滨工业大学计算机科学与技术学院 讲师

2009年 9月—2014年12月:哈尔滨工业大学计算机科学与技术学院 副教授

2014年12月—2019年6月:哈尔滨工业大学计算机科学与技术学院 教授

2016年12月至今:哈尔滨工业大学计算机科学与技术学院 长聘教授

东北林业大学 2019年7月 - 至今

计算机与控制工程学院

东北林业大学计算机与控制工程学院 - 教授

东北林业大学计算机与控制工程学院 - 院长

团队成员

老师

研究生

  • 2015级：董丽丽（博）、 罗锡梅（博）
  • 2016级：王芳（博）、 王嘉男（博）
  • 2017级：王聪（博）
  • 2018级：刘翘铭（博）、任彤彤（博）
  • 2019级：孟萍（博）
  • 2020级：高文韬（博）、李鸿飞（博）、克劲松（硕）
  • 2021级：崔玲玉（博）、刘崇辉（博）、周慕蓉（博）、赵健梅（博）
  • 2022级：钱智鹏（博）、卢乾梓（博）、姜忠俊（博）、胡恒（博）
  • 2023级：周圣明（博）、殷宇航（博）、高润天（博）、王子璇（博）、乔冠宇（博）

相关科研网站链接

数据库

生物序列预测

承担项目

  1. 国家自然科学基金杰出青年科学基金项目，“生物信息处理与分析”，2023.1-2027.12，项目负责人
  2. 国家重点研发计划“高准确、全类型TB级通量测序数据实时分析系统”，2022.11-2025.10，项目负责人
  3. 国家重点研发计划“工业酶设计的智能算法研究”，2021.7-2024.6，子课题负责人
  4. 国家自然科学基金面上项目，“基于差异-共表达网络的单细胞关键基因识别与细胞分类方法研究”，2021.1-2024.12，项目负责人
  5. 国家自然科学基金面上项目“结合甲基化DNA的转录因子识别及其调控功能研究”，2018.1-2021.12，项目负责人
  6. 国家自然科学基金面上项目“基于个体基因组单核苷酸突变的等位基因转录调控模型研究”，2014.1-2017.12，项目负责人
  7. 国家自然科学基金青年项目“基于CHIP-SEQ数据的microRNA启动子区域预测及转录因子结合位点分析”，2010.1-2012.12，项目负责人
  8. 教育部新世纪优秀人才支持计划“面向个人基因组的生物信息学问题研究”，2014.1-2016.12，项目负责人
  9. 国家863项目“转化医学生物信息技术及产品研发”，2012.1-2015.12，项目负责人
  10. 博士后国际交流计划派出项目“基因组中DNA甲基化对疾病调控机制研究”，2014.4-2016.4，项目负责人

发表学术论文

  1. Wang F, Yang F, Huang L, Song J, Gasser RB, Aebersold R*, Wang G*, Yao J*. Deep Domain Adversarial Neural Network for the Deconvolution of Cell Type Mixtures in Tissue Proteome Profiling. Nature Machine Intelligence. volume 5, pages1236–1249 (2023).
  2. L. Zhou, X. Meng, Y. Huang, K. Kang, J. Zhou, Y. Chu, H. Li, D. Xie, J. Zhang, W. Yang, N. Bai, Y. Zhao, M. Zhao, G. Wang*, L. Carin*, X. Xiao*, K. Yu*, Z. Qiu*, and X. Gao*. An Interpretable deep learning workflow for discovering sub-visual abnormalities in CT scans of COVID-19 inpatients and survivors. Nature Machine Intelligence. 2022; 4: 494-503.
  3. Song G#, Wang G#, Luo X#, Cheng Y, Song Q, Wan J, Moore C, Song H, Jin P, Qian J*, Zhu H*. An all-to-all approach to the identification of sequence-specific readers for epigenetic DNA modifications on cytosine. Nature Communications. 2021; 12(1):795
  4. Hoang T, Wang J, Boyd P, Wang F, Santiago C, Jiang L, Yoo S, Lahne M, Todd LJ, Jia M, Saez C, Keuthan C, Palazzo I, Squires N, Campbell WA, Rajaii F, Parayil T, Trinh V, Kim DW, Wang G, Campbell LJ, Ash J, Fischer AJ, Hyde DR*, Qian J*, Blackshaw S*. Gene regulatory networks controlling vertebrate retinal regeneration. Science. 2020; 370(6519):eabb8598.
  5. White DT#, Eroglu AU#, Wang G#, Zhang L, Sengupta S, Ding D, Rajpurohit SK, Walker SL, Ji H, Qian J, Mumm JS*. ARQiv-HTS, a versatile whole-organism screening platform enabling in vivo drug discovery at high-throughput rates. Nature Protocol. 2016 Dec;11(12):2432-2453.
  6. Zhu H*, Wang G, Qian J*. Transcription factors as readers and effectors of DNA methylation. Nature Review Genetics.2016;17(9):551-65
  7. Ding K, Sun S, Luo Y, Long C, Zhai J, Zhai Y, Wang G*. PlantCADB: A Comprehensive Plant Chromatin Accessibility Database. Genomics Proteomics Bioinformatics. 2022; S1672-0229(22) 00133-4.
  8. Wang F, Liu C, Li J, Yang F, Song J, Zang T, Yao J*, Wang G*. SPDB: a comprehensive resource and knowledgebase for proteomic data at the single-cell resolution. Nucleic Acids Research.2023 Nov 11:gkad1018.
  9. Xu C, Jin X, Wei S, Wang P, Luo M, Xu Z, Yang W, Cai Y, Xiao L, Lin X, Liu H, Cheng R, Pang F, Chen R, Su X, Hu Y, Wang G, Jiang Q*. DeepST: identifying spatial domains in spatial transcriptomics by deep learning. Nucleic Acids Research. 2022;50(22):e131.
  10. Zhang T, Zhang Z, Li L, Dong B, Wang G*, Zhang D*. GTAD: a graph-based approach for cell spatial composition inference from integrated scRNA-seq and ST-seq data. Brief Bioinform. 2023 Nov 22;25(1):bbad469
  11. Li Y, Guo Z, Gao X, Wang G*. MMCL-CDR: Enhancing Cancer Drug Response Prediction with Multi-Omics and Morphology Images Contrastive Representation Learning. Bioinformatics. 2023 Dec 9:btad734.
  12. Liu Q, Wang D, Zhou L, Li J, Wang G*. MTGDC: a multi-scale tensor graph diffusion clustering for single-cell RNA sequencing data. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2023: 1 - 12.
  13. Wang X, Gao X, Wang G*, Li D*. miProBERT: identification of microRNA promoters based on the pre-trained model BERT . Briefings in bioinformatics, 2023, 24(3): bbad093.
  14. Wang X, Li J, Wang G*. MicroRNA Promoter Identification in Human with a Three-level Prediction Method. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2023: 1 - 10.
  15. Dong B, Sun W, Xu D, Wang G*, Zhang T*. MDformer: A transformer-based method for predicting miRNA-Disease associations using multi-source feature fusion and maximal meta-path instances encoding. Comput Biol Med. 2023 Dec;167:107585.
  16. Liu Q, Zhao X, Wang G*. A Clustering Ensemble Method for Cell Type Detection by Multiobjective Particle Optimization. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 2023 Jan-Feb;20(1):1-14.
  17. Bian J, Zhang X, Zhang X, Xu D, Wang G*. MCANet: shared-weight-based MultiheadCrossAttention network for drug–target interaction prediction. Briefings in Bioinformatics, 2023, 24(2): bbad082.
  18. Dong B, Sun W, Xu D, Wang G*., Zhang T*. DAEMDA: A Method with Dual-Channel Attention Encoding for miRNA-Disease Association Prediction. Biomolecules. 2023 Oct 12;13(10):1514.
  19. Chen S, Yu Y, Wang X, Wang S, Zhang T, Zhou Y, He R, Meng N, Wang Y, Liu W, Liu Z, Liu J, Guo Q, Huang H, Sederoff RR, Wang G*, Qu G*, Chen S*. Chromosome‐level genome assembly of a triploid poplar Populus alba ‘Berolinensis’. Molecular Ecology Resources, 2023: 1092-107.
  20. Cui L, Li H, Bian J, Wang G*, Liang Y*, Liang Y. Unsupervised construction of gene regulatory network based on single-cell multi-omics data of colorectal cancer. Briefings in Bioinformatics, 2023, 24(2): bbad011.
  21. Li Y, Guo Z, Wang K, Gao X, Wang G*. End-to-end interpretable disease–gene association prediction. Briefings in Bioinformatics, 2023, 24(3): bbad118.
  22. Liu C, Zhang Y, Gao X*, Wang G*. Identification of cell subpopulations associated with disease phenotypes from scRNA-seq data using PACSI. BMC biology, 2023, 21(1): 1-19.
  23. Zhang T, Li L, Sun H, Wang G*. DeepITEH: a deep learning framework for identifying tissue-specific eRNAs from the human genome. Bioinformatics, 2023, 39(6): btad375.
  24. Zhang T, Li L, Sun H, Xu D, Wang G*. DeepICSH: a complex deep learning framework for identifying cell-specific silencers and their strength from the human genome. Briefings in Bioinformatics, 2023: bbad316.
  25. Zhao J, Qian F, Li X, Yu Z, Zhu J, Yu R, Zhao Y, Ding K, Li Y, Yang Y, Pan Q, Chen J, Song C, Wang Q, Zhang J, Wang G*, Li C*. CanMethdb: a database for genome-wide DNA methylation annotation in cancers. Bioinformatics, 2023, 39(1): btac783.
  26. Dong L, Wang J, Wang G*. ASAS-EGB: A statistical framework for estimating allele-specific alternative splicing events using transcriptome data. Computers in Biology and Medicine. 2023 Jun:160:106981.
  27. Meng P, Wang G, Guo H*, Jiang T*. Identifying cancer driver genes using a two-stage random walk with restart on a gene interaction network. Computers in Biology and Medicine .2023 May:158:106810.
  28. Liu Y, Zhao X, Bian J, Wang G*. Feature selection combined with top-down and bottom-up strategies for survival analysis: A case of prognostic prediction in glioblastoma. Comput Biol Med. 2023;153:106486.
  29. Gao W, Xu D, Li H, Du J, Wang G*, Li D. Identification of adaptor proteins by incorporating deep learning and PSSM profiles. Methods. 2023;209:10-7.
  30. Ren T, Huang S, Liu Q, Wang G*. scWECTA: A weighted ensemble classification framework for cell type assignment based on single cell transcriptome. Comput Biol Med. 2023;152:106409.
  31. Wang X, Liu Y, Li J, Wang G*. StackCirRNAPred: computational classification of long circRNA from other lncRNA based on stacking strategy. BMC Bioinformatics. 2022;23(1):563.
  32. Zhao X, Zhai J, Liu T, Wang G*. Ensemble classification based feature selection: a case of identification on plant pentatricopeptide repeat proteins. Briefings in Bioinformatics. 2022;23(6).
  33. Zhao X, Liu T, Wang G*. Ensemble classification based signature discovery for cancer diagnosis in RNA expression profiles across different platforms. Briefings in Bioinformatics. 2022;23(5).
  34. Zhao X, He Y, Wu Y, Liu T, Wang G*. IOFS-SA: An interactive online feature selection tool for survival analysis. Comput Biol Med. 2022;150:106121.
  35. Zhang T, Zhou J, Gao W, Jia Y, Wei Y, Wang G*. Complex genome assembly based on long-read sequencing. Briefings in Bioinformatics. 2022;23(5).
  36. Zhang T, Jia Y, Li H, Xu D, Zhou J, Wang G*. CRISPRCasStack: a stacking strategy-based ensemble learning framework for accurate identification of Cas proteins. Briefings in Bioinformatics. 2022;23(5).
  37. Liu C, Chen S, Wang G*, Chen S*. Decoding the molecular regulation mechanism of plant architecture in woody plants. New Phytologist. 2022;235(1):8-10.
  38. Li Y, Qiao G, Gao X, Wang G*. Supervised graph co-contrastive learning for drug-target interaction prediction. Bioinformatics. 2022;38(10):2847-54.
  39. Teng Z., Zhao Z., Li Y., Tian Z., Guo M., Lu Q., and Wang G*, i6mA-Vote: Cross-Species Identification of DNA N6-Methyladenine Sites in Plant Genomes Based on Ensemble Learning With Voting. Front Plant Science, 2022. 13: p. 845835.
  40. Muller-Xing R., Ardiansyah R., Xing Q., Faivre L., Tian J., Wang G., Zheng Y., Wang X., Jing T., de Leau E., Chen S., Chen S., Schubert D., and Goodrich J., Polycomb Proteins Control Floral Determinacy by H3K27me3-mediated Repression of Pluripotency Genes in Arabidopsis thaliana. J Exp Bot, 2022.
  41. Li H., Shi L., Gao W., Zhang Z., Zhang L., Zhao Y., and Wang G*, dPromoter-XGBoost: Detecting promoters and strength by combining multiple descriptors and feature selection using XGBoost. Methods, 2022;204:215-222
  42. Li H., Gong Y., Liu Y., Lin H., and Wang G*, Detection of transcription factors binding to methylated DNA by deep recurrent neural network. Briefings in Bioinformatics, 2022. 23(1).
  43. Li Y., Qiao G., Wang K., and Wang G*, Drug-target interaction predication via multi-channel graph neural networks. Briefings in Bioinformatics, 2022. 23(1).
  44. Liu Q., Wan J., and Wang G*, A survey on computational methods in discovering protein inhibitors of SARS-CoV-2. Briefings in Bioinformatics, 2022. 23(1).
  45. Liu Q, Luo X, Li J, Wang G*. scESI: evolutionary sparse imputation for single-cell transcriptomes from nearest neighbor cells. Briefings in Bioinformatics. 2022;23(5).
  46. Zhang S., Jiang H., Gao B., Yang W., and Wang G*, Identification of Diagnostic Markers for Breast Cancer Based on Differential Gene Expression and Pathway Network. Front Cell Dev Biol, 2022 Jan 12:9:811585.
  47. Zhang S., Zhang J., Zhang Q., Liang Y., Du Y., and Wang G*, Identification of Prognostic Biomarkers for Bladder Cancer Based on DNA Methylation Profile. Front Cell Dev Biol, 2022 Jan 31:9:817086.
  48. Chen Y., You D., Zhang T., and Wang G*, SLDMS: A Tool for Calculating the Overlapping Regions of Sequences. Front Plant Science, 2022 Jan 3:12:813036.
  49. Teng Z., Zhang Z., Tian Z., Li Y., and Wang G*, ReRF-Pred: predicting amyloidogenic regions of proteins based on their pseudo amino acid composition and tripeptide composition. BMC Bioinformatics, 2021. 22(1): p. 545.
  50. Li Y, Wang K, Wang G*. Evaluating Disease Similarity Based on Gene Network Reconstruction and Representation. Bioinformatics. 2021;37(20):3579-3587
  51. Luo X, Zhang T, Zhai Y, Wang F, Zhang S,Wang G*. Effects of DNA Methylation on TFs in Human Embryonic Stem Cells. Front Genet. 2021;12:639461.
  52. Zhao X., Wang H., Li H., Wu Y., and Wang G*, Identifying Plant Pentatricopeptide Repeat Proteins Using a Variable Selection Method. Front Plant Sci, 2021;12:506681
  53. Wang X, Yang Y, Liu J*, Wang G*. The stacking strategy-based hybrid framework for identifying non-coding RNAs. Briefings in Bioinformatics. 2021;22(5):bbab023
  54. Huang S, He X, Wang G*, Bao E*. AlignGraph2: similar genome-assisted reassembly pipeline for PacBio long reads. Briefings in Bioinformatics. 2021;22(5):bbab022
  55. Sun S., Xu L., Zou Q., and Wang G*, BP4RNAseq: a babysitter package for retrospective and newly generated RNA-seq data analyses using both alignment-based and alignment-free quantification method. Bioinformatics, 2021. 37(9): 1319-1321.
  56. Guan D, McCarthy SA, Ning Z, Wang G*, Wang Y, Durbin R. Efficient iterative Hi-C scaffolder based on N-best neighbors. BMC Bioinformatics. 2021;22(1):569.
  57. Liu Y, Huang Y, Wang G*, Wang Y*. A deep learning approach for filtering structural variants in short read sequencing data. Briefings in Bioinformatics. 2021;22(4):bbaa370
  58. Hoang T, Wang J, Boyd P, Wang F, Santiago C, Jiang L, Yoo S, Lahne M, Todd LJ, Jia M, Saez C, Keuthan C, Palazzo I, Squires N, Campbell WA, Rajaii F, Parayil T, Trinh V, Kim DW, Wang G, Campbell LJ, Ash J, Fischer AJ, Hyde DR, Qian J, Blackshaw S. Gene regulatory networks controlling vertebrate retinal regeneration. Science. 2020 Nov 20;370(6519):eabb8598.
  59. Dong L, Wang J, Wang G*. BYASE: A Python library for estimating gene and isoform level allele-specific expression. Bioinformatics. 2020;36(19):4955-4956
  60. Juan L, Wang Y, Jiang J, Yang Q, Wang G*, Wang Y*. Evaluating Individual Genome Similarity With a Topic Model. Bioinformatics. 2020;36(18):4757-4764.
  61. Wang J, Chen S, Dong L, Wang G*. CHTKC: A Robust and Efficient K-Mer Counting Algorithm Based on a Lock-Free Chaining Hash Table. Briefings in Bioinformatics. 2021;22(3):bbaa063
  62. Luo X, Wang F, Wang G*, Zhao Y*. Identification of methylation states of DNA regions for Illumina methylation BeadChip. BMC genomics. 2020, 21(1):1-10.
  63. Xudong Zhao, Qing Jiao, Hangyu Li, Yiming Wu, Hanxu Wang, Shan Huang and Guohua Wang*. ECFS-DEA: an ensemble classifier-based feature selection for differential expression analysis on expression profiles. BMC Bioinformatics.2020;21(1):43
  64. Jiang S, Wang J, Yang C, Tan R, Hou J, Shi Y, Wang G et al. Continuous culture of urine-derived bladder cancer cells for precision medicine. Protein Cell. 2019;10(12):902-7.
  65. Wang G, Luo X, Wang J, Wan J, Xia S, Zhu H, Qian J, Wang Y. MeDReaders: a database for transcription factors that bind to methylated DNA. Nucleic Acids Research. 2018;46(D1):D146-D151.
  66. Qu K, Han K, Wu S, Wang G, Wei L. Identification of DNA-Binding Proteins Using Mixed Feature Representation Methods. Molecules. 2017 Sep 22;22(10).
  67. Liu S, Zibetti C, Wan J, Wang G, Blackshaw S, Qian J. Assessing the model transferability for prediction of transcription factor binding sites based on chromatin accessibility. BMC Bioinformatics. 2017 Jul 27;18(1):355.
  68. Zhao Y, Wang F, Chen S, Wan J, Wang G*. Methods of MicroRNA Promoter Prediction and Transcription Factor Mediated Regulatory Network. Biomed Res Int. 2017;2017:7049406.
  69. Peng J, Bai K, Shang X, Wang G, Xue H, Jin S, Cheng L, Wang Y, Chen J. Predicting disease-related genes using integrated biomedical networks. BMC Genomics.. 2017;18(Suppl 1):1043
  70. White DT#, Eroglu AU#, Wang G#, Zhang L, Sengupta S, Ding D, Rajpurohit SK, Walker SL, Ji H, Qian J, Mumm JS. ARQiv-HTS, a versatile whole-organism screening platform enabling in vivo drug discovery at high-throughput rates. Nat Protoc. 2016 Dec;11(12):2432-2453.
  71. Zhu H, Wang G, Qian J. Transcription factors as readers and effectors of DNA methylation. Nat Rev Genet. 2016;17(9):551-65
  72. Campochiaro PA, Hafiz G, Mir TA, Scott AW, Zimmer-Galler I, Shah SM, Wenick AS, Brady CJ, Han I, He L, Channa R, Poon D, Meyerle C, Aronow MB, Sodhi A, Handa JT, Kherani S, Han Y, Sophie R, Wang G, Qian J. Pro-permeability Factors in Diabetic Macular Edema; the Diabetic Macular Edema Treated With Ozurdex Trial. Am J Ophthalmol. 2016;168:13-23
  73. Wang G, Wang F, Huang Q, Li Y, Liu Y, Wang Y. Understanding Transcription Factor Regulation by Integrating Gene Expression and DNase I Hypersensitive Sites. Biomed Res Int. 2015;2015:757530
  74. Wang G, Liu Y, Zhu D, Klau GW, Feng W. Bioinformatics Methods and Biological Interpretation for Next-Generation Sequencing Data. Biomed Res Int. 2015; 2015:690873
  75. Zou Q, Li J, Song L, Zeng X, Wang G. Similarity computation strategies in the microRNA-disease network: a survey. Brief Funct Genomics. 2015 Jul 1. pii: elv024
  76. Zhao Y, Zou Q; Jiang Y; Wang, G*. A Graphic Processing Unit Web Server for Computing Correlation Coefficients for Gene Expression Data. Journal of Computational and Theoretical Nanoscience, 12(4), pp 582-584
  77. Oliver VF, Jaffe AE, Song J, Wang G, Zhang P, Branham KE, Swaroop A, Eberhart CG, Zack DJ, Qian J, Merbs SL. Differential DNA methylation identified in the blood and retina of AMD patients. Epigenetics. 2015;10(8):698-707
  78. Zou Q, Hu Q, Guo M, Wang G*. HAlign: Fast multiple similar DNA/RNA sequence alignment based on the centre star strategy. Bioinformatics. 2015 Aug 1;31(15):2475-81
  79. Wan J, Oliver VF, Wang G, Zhu H, Zack DJ, Merbs SL, Qian J. Characterization of tissue-specific differential DNA methylation suggests distinct modes of positive and negative gene expression regulation. BMC Genomics. 2015 Feb 5;16:49
  80. Campochiaro PA, Hafiz G, Mir TA, Scott AW, Sophie R, Shah SM, Ying HS, Lu L, Chen C, Campbell JP, Kherani S, Zimmer-Galler I, Wenick A, Han I, Paulus Y, Sodhi A, Wang G, Qian J. Pro-permeability Factors After Dexamethasone Implant in Retinal Vein Occlusion; The Ozurdex for Retinal Vein Occlusion (ORVO) Study. Am J Ophthalmol. 2015;160(2):313-321
  81. Zhang D, Wang G, Wang Y. Transcriptional regulation prediction of antiestrogen resistance in breast cancer based on RNA polymerase II binding data. BMC Bioinformatics. 2014;15 Suppl 2:S10
  82. Zhu S, Wang G, Liu B, Wang Y. Modeling exon expression using histone modifications. ta. PLoS ONE. 2013; 8(6): e67448
  83. Cheng L, Wang G, Li J, Zhang T, Xu P, Wang Y. SIDD: A Semantically Integrated Database towards a Global View of Human Disease. PLoS One. 2013;8(10):e75504
  84. Zou Q, Li X, Jiang Y, Zhao Y, Wang G*. BinMemPredict: a Web server and software for predicting membrane protein types. Current Proteomics. 2013; 10(1): 2-9
  85. Jiang Q, Wang G, S Jin, Y Li, Wang Y*. Predicting human microRNA-disease associations based on support vector machine. International Journal of Data Mining and Bioinformatics. 2013; 8(3):282-293
  86. Wang G*, Qi K, Zhao Y, Li Y, Juan L, Teng M, Li L, Liu Y, Wang Y. Identification of Regulatory Regions of Bidirectional Genes in Cervical Cancer. BMC Medical Genomics. 2013;6 Suppl 1:S5
  87. Juan L, Wang G, Radovich M, Schneider BP, Clare SE, Wang Y, Liu Y. Potential roles of microRNAs in regulating long intergenic noncoding RNAs. BMC Medical Genomics. 2013;6 Suppl 1:S7
  88. Teng M, Wang Y, Kim S, Li L, Shen C, Wang G, Liu Y, Huang T, Nephew KP, Balch C. Empirical Bayes model comparisons for differential methylation analysis. Comparative and Functional Genomics, 2012:376706.
  89. Zhu S, Jiang Q, Wang G, Liu B, Teng M, Wang Y. Chromatin structure characteristics of pre-miRNA genomic sequences. BMC Genomics. 2011 Jun 25;12:329
  90. Teng M, Wang Y, Wang G, Jung J, Edenberg H, Sanford J, Liu Y. Prioritizing single-nucleotide variations that potentially regulate alternative splicing. BMC Proceedings, 2011; 5(Suppl 9):S40
  91. Shen C, Huang Y, Liu Y, Wang G, Zhao Y, Wang Z, Teng M, Wang Y, Flockhart DA, Skaar TC, Yan P, Nephew KP, Huang TH, Li L. A modulated Empirical Bayes Model for Identifying Topological and Temporal Estrogen Receptor alpha Regulatory Networks in Breast Cancer. BMC Syst Biol. 2011;5(1):67
  92. Patel JB, Appaiah HN, Burnett RM, Bhat-Nakshatri P, Wang G, Mehta R, Badve S, Thomson MJ, Hammond S, Steeg P, Liu Y, Nakshatri H. Control of EVI-1 oncogene expression in metastatic breast cancer cells through microRNA miR-22. Oncogene. 2011; 30(11):1290-1301
  93. Wang G, Wang Y, Shen C, Huang Y, Kuang K, Huang T, Nephew K, Li L, Liu Y. RNA Polymerase II binding patterns reveal genomic regions involved in microRNA gene regulation. PLoS ONE. 2010;5(11): e13798
  94. Wang G, Wang Y, Teng M, Zhang D, Li L, Liu Y. Signal transducers and activators of transcription-1 (STAT1) regulates microRNA transcription in interferon γ – stimulated HeLa cells. PLoS ONE. 2010; 5(7):e11794
  95. Jiang Q, Hao Y, Wang G, Juan L, Zhang T, Teng M, Liu Y, Wang Y. Prioritization of disease microRNAs through a human phenome-microRNAome network. BMC Syst Biol. 2010; 4 Suppl 1:S2
  96. Liu Y, Balaraman Y, Wang G, Nephew KP, Zhou FC. Alcohol exposure alters DNA methylation profiles in mouse embryos at early neurulation. Epigenetics. 2009; 4(7):500-511. (co-first author)
  97. Wang Y, Wang G, Yang B, Tao H, Yang JY, Deng Y, Liu Y. Reconstruct gene regulatory network using slice pattern model. BMC Genomics. 2009; 10 Suppl 1:S2. (co-first author)
  98. Wang X, Wang K, Radovich M, Wang Y, Wang G, Feng W, Sanford JR, Liu Y. Genome-wide prediction of cis-acting RNA elements regulating tissue-specific pre-mRNA alternative splicin. BMC Genomics. 2009; 10 Suppl 1:S4
  99. Bhat-NakshatrWang G, Collins NR, Thomson MJ, Geistlinger TR, Carroll JS, Brown M, Hammond S, Srour EF, Liu Y, Nakshatri H. Estradiol-regulated microRNAs control estradiol response in breast cancer cells. Nucleic Acids Res. 2009; 37(14):4850-4861
  100. Jiang Q, Wang Y, Hao Y, Juan L, Teng M, Zhang X, Li M, Wang G, Liu Y. miR2Disease: a manually curated database for microRNA deregulation in human disease. Nucleic Acids Res. 2009; 37(Database issue):D98-104
  101. Wang G, Wang Y, Feng W, Wang X, Yang JY, Zhao Y, Wang Y, Liu Y. Transcription factor and microRNA regulation in androgen-dependent and -independent prostate cancer cells. BMC Genomics. 2008; 9 Suppl 2:S22
  102. Wang G, Wang X, Wang Y, Yang JY, Li L, Nephew KP, Edenberg HJ, Zhou FC, Liu Y. Identification of transcription factor and microRNA binding sites in responsible to fetal alcohol syndrome. BMC Genomics. 2008; 9 Suppl 1:S19
  103. Bhat-Nakshatri P, Wang G, Appaiah H, Luktuke N, Carroll JS, Geistlinger TR, Brown M, Badve S, Liu Y, Nakshatri H. AKT alters genome-wide estrogen receptor alpha binding and impacts estrogen signaling in breast cancer. Mol Cell Biol. 2008; 28(24):7487-7503
  104. Wang X, Wang G, Shen C, Li L, Wang X, Mooney SD, Edenberg HJ, Sanford JR, Liu Y. Using RNase sequence specificity to refine the identification of RNA-protein binding regions. BMC Genomics. 2008; 9 Suppl 1:S17

更新日期：2024.4.25

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