Bioinformatics, Computational Biology, Biostatistics

1. Next generation data analysis

2. Network inference and anlaysis

3. Metagenomics data analysis

4. Genome-wise association study (GWAS)

2019.1-2022.12 “Research on the compositional data analysis and its application to metagenomics data” National Science Foundation of China， ¥590,000RMB (PI).

2016.1-2020.12   "Research on the key technology for new drug design based on 3D structure of protein machine" (Project III)"System-based drug design for protein machine" Ministry of Science and Technology ¥500,000RMB     (Co-PI)

2015.1-2019.12   China 973 project: "System Biology Research based on protein regulatory network" (III) "Disease related network analysis" Ministry of Science and Technology  ¥5,710,000RMB    (PI)

2015.1-2018.12   "Network-based Genome-wide association analysis"      National Science Foundation of China    ¥700,000RMB (PI)

2012.1-2015.12.   “Construction and Analysis of Genetic Interaction Data” National Science Foundation of China    ¥600,000RMB (PI)

2009.1-2011.12 NSFC project “On the statistical methods for preprocessing of gene chips based on the physical-chemical model of probe hybridization”. National Science Foundation of China      ¥240,000RMB (PI)

2008.1-2010.12 China 863 project “On the construction and analysis of protein complex networks and its application to liver cancer”. Ministry of Science and Technology,   ¥1,000,000RMB   (PI)

2005.1-2008.12 NSFC project “Research on the modeling of Transcription factor binding site (TFBS)” National Science Foundation of China, ¥280,000RMB  (PI)

1. Huili Yuan  Shun He  Minghua Deng. Compositional data network analysis via lasso penalized D-trace loss. Bioinformatics, https://doi.org/10.1093/bioinformatics/btz098, Published: 14 February 2019

2. Yujuan Gao, Sheng Wang, Minghua Deng* and Jinbo Xu*. RaptorX-Angle: real-value prediction of protein backbone dihedral angles through a hybrid method of clustering and deep learning. BMC Bioinformatics 2018, 19 (Suppl 4) :100. https://doi.org/10.1186 /s12859-018-2065-x. APBC 2018 Best Paper Award.

3. Huili Yuan; Ruibin Xi; Chong Chen; Minghua Deng*. Differential network analysis using a D-trace loss. Biometrika 2017, 4: 755–770.

4. Changjing Wu, Hongyu Zhao, Huaying Fang and Minghua Deng*. Graphical model selection with latent variables.Electronic Journal of Statistics 2017, 11, 3485–3521.

5. Zengmiao Wang, Huaying Fang, Nelson Leung-Sang Tang and Minghua Deng. VCNet: vector-based gene co-expression network construction and its application to RNA-seq data. Bioinformatics 33(14):2173–2181, 2017.

6. Huaying Fang, Chengcheng Huang, Hongyu Zhao and Minghua Deng. CCLasso: Correlation Inference for Compositional Data through Lasso. Bioinformatics. 2015 Oct 1;31(19):3172-80. doi: 10.1093/bioinformatics/btv349..

7. Lin Wang, Wei Zheng, Hongyu Zhao, Minghua Deng. Statistical Analysis Reveals Co-Expression Patterns of Many Pairs of Genes in Yeast Are Jointly Regulated by Interacting Loci. PLoS Genetics 9(3): e1003414,2013.

8. Lin Hou, Lin Wang, Minping Qian, Dong Li, Chao Tang, Yunping Zhu, Minghua Deng, Fangting Li. Modular analysis of the probabilistic genetic interaction network. Bioinformatics 27(6):853-859,2011.

9. Hao Zheng, Xingyi Hang, Ji Zhu, Minping Qian, Wubin Qu, Chenggang Zhang, Minghua Deng. REMAS: a new regression model to identify alternative splicing events from exon array data. BMC Bioinformatics 10 (Suppl 1):S18, 2009. APBC2009 Best Paper Award.  

10. Minghua Deng, Shepra Mehta, Fengzhu Sun, Ting Chen. Inferring domain-domain interactions from protein-protein interactions. Genome Research 12(10):1540-1548,2002. See also The ACM-SIGACT 6th Annual International Conference on Computational Molecular Biology (RECOMB02), 95-103, April, 2002.