omicsDB

Name: Quanzhong Liu Gender: male Job title: Associate Professor

Mailing address: Northwest A & F University, Yangling, China. Post code: 712100

Email: liuqzhong@nwsuaf.edu.cn

Education and Working

1999.9-2003.07  B.E. in Computer Science and Technology, School of Computer and Information Engineering, Henan University
2003.9-2006.7  M.E. in Computer Software and Theory, School of Computer Science, Northwestern Polytechnical University
2007.9-2012.10  Ph.D. in Agricultural Electrification and Automation, College of Mechanical and Electronic Engineering, Northwest A&F University
2004.01-2006.01  Software Engineer, NECAS Company Limited, Xi'an Software Park
2006-2008  Assistant Professor, College of Information Engineering, Northwest A&F University, Yangling
2009.2-2010.2  Visiting student, University of Massachusetts, USA
2008-2014  Lecturer, College of Information Engineering, Northwest A&F University, Yangling
2015-present  Associate Professor, College of Information Engineering, Northwest A&F University, Yangling

Research Interests

My research interests are big data techniques, machine learning and computational biology. More specifically, my research focuses on machine learning/deep learning algorithms for genome sequence analysis.

Scientific Research Projects

Participated in the national Natural Science Foundation of China, national Key RESEARCH and development, National Science and Technology Support Program and other projects, developed a number of software systems

Academic achievements

15. Zhang, X; Zhao, LW ; Chai, ZY; Wu, H ; Yang, W ; Li, C; Jiang, Y *;Liu, QZ*, (2024). NPI-DCGNN: An Accurate Tool for Identifying ncRNA-Protein Interactions Using a Dual-Channel Graph Neural Network.. JOURNAL OF COMPUTATIONAL BIOLOGY .DOI: 10.1089/cmb.2023.0449

14. Zhao, LW; Hao, R; Chai, ZY; Fu, WW ; Yang, W; Li, C; Liu, QZ* Jiang, Y*., (2024). DeepOCR: A multi-species deep-learning framework for accurate identification of open chromatin regions in livestock.Computational Biology and Chemistry. 110

13. Wang, X ; Chai, ZY ; Li, SH ; Liu, Y ; Li, C*; Jiang, Y*, Liu, QZ*(2024) CTISL: a dynamic stacking multi-class classification approach for identifying cell types from single-cell RNA-seq data. Bioinformatics, 40(2)

12. Chen, JX ; Wang, M; Zhao, DF; Li, FY ; Wu, H; Liu, QZ ; Li, SQ* ,(2023) MSINGB: A Novel Computational Method Based on NGBoost for Identifying Microsatellite Instability Status from Tumor Mutation Annotation Data. Interdisciplinary Sciences: Computational Life Sciences .15(1),100-110

11. Liu Q,Fang H, Wang M, Li S, Coin LJM, Li F*, Song J*.(2022). DeepGenGrep: a general deep learning-based predictor for multiple genomic signals and regions. Bioinformatics. 2022, 38(17):4053–4061.

10. Wang, M., Li, F., Wu, H., Liu Q., & Li, S. (2022). PredPromoter-MF(2L): A Novel Approach of Promoter Prediction Based on Multi-source Feature Fusion and Deep Forest. Interdisciplinary Sciences: Computational Life Sciences. doi:10.1007/s12539-022-00520-4

9. Liu Q., Chen, J., Wang, Y., Li, S., Jia, C., Song, J., & Li, F. (2021). DeepTorrent: a deep learning-based approach for predicting DNA N4-methylcytosine sites. Briefings in Bioinformatics, 22(3), bbaa124. doi:10.1093/bib/bbaa124

8. Liang, X., Li, F., Chen, J., Li, J., Wu, H., Li, S., . . . Liu Q. (2021). Large-scale comparative review and assessment of computational methods for anti-cancer peptide identification. Briefings in Bioinformatics, 22(4), bbaa312. doi:10.1093/bib/bbaa312

7. Chen, J., Li, F., Wang, M., Li, J., Marquez-Lago, T. T., Leier, A., . . . Song, J. (2021). BigFiRSt: A Software Program Using Big Data Technique for Mining Simple Sequence Repeats From Large-Scale Sequencing Data. Front Big Data, 4, 727216. doi:10.3389/fdata.2021.727216

6. Li, F., Leier, A., Liu Q., Wang, Y., Xiang, D., Akutsu, T., . . . Song, J. (2020). Procleave: Predicting Protease-specific Substrate Cleavage Sites by Combining Sequence and Structural Information. Genomics, Proteomics & Bioinformatics, 18(1), 52-64. doi:https://doi.org/10.1016/j.gpb.2019.08.002

5. Li, F., Fan, C., Marquez-Lago, T. T., Leier, A., Revote, J., Jia, C., . . . Song, J. (2020). PRISMOID: a comprehensive 3D structure database for post-translational modifications and mutations with functional impact. Briefings in Bioinformatics, 21(3), 1069-1079. doi:10.1093/bib/bbz050

4. Li, F., Chen, J., Leier, A., Marquez-Lago, T., Liu Q., Wang, Y., . . . Song, J. (2019). DeepCleave: a deep learning predictor for caspase and matrix metalloprotease substrates and cleavage sites. Bioinformatics, 36(4), 1057-1065. doi:10.1093/bioinformatics/btz721 %J Bioinformatics

3. Liu Q., Song, J., & Li, J. (2016). Using contrast patterns between true complexes and random subgraphs in PPI networks to predict unknown protein complexes. Scientific Reports, 6(1), 21223. doi:10.1038/srep21223

2. Liu Q., Shi, P., Hu, Z., & Zhang, Y. (2014). A novel approach of mining strong jumping emerging patterns based on BSC-tree. International Journal of Systems Science, 45(3), 598-615. doi:10.1080/00207721.2012.724110

1. Liu Q., Chen, C., Zhang, Y., & Hu, Z. (2011). Feature selection for support vector machines with RBF kernel. Artificial Intelligence Review, 36(2), 99-115. doi:10.1007/s10462-011-9205-2