研究领域：生物信息学，图论及其应用
0531-88361896
bingqiang@sdu.edu.cn
1999.9-2003.6 山东大学 数学与应用数学 学士
2003.9-2006.7 山东大学 运筹学与控制论 硕士
2006.9-2010.7 山东大学 运筹学与控制论 博士
2007.1-2010.1 美国乔治亚大学生物信息学
2010.7-2013.8 山东大学数学学院讲师
2013.9-2017.8 山东大学数学学院副教授
2017.9至今 山东大学数学学院教授
教育部“长江学者”青年学者，山东省“泰山学者”青年专家
Since 2018
1. Highly accurate diagnosis of pancreatic cancer by integrative modeling using gut microbiome and exposome data, Yuli Zhang, Haohong Zhang, Bingqiang Liu*, Kang Ning*, iScience, 15 March 2024. 27(3): 109294. (SCI, IF 5.750)
2. A weighted two-stage sequence alignment framework to identify motifs from ChIP-exo data, Yang Li#, Yizhong Wang#, Cankun Wang, Anjun Ma, Qin Ma*, Bingqiang Liu*, Patterns, 2024 Feb 02, 5, 100927. (SCI, IF 6.500)
3. CEMIG: prediction of the cis-regulatory motif using the de Bruijn graph from ATAC-seq Yizhong Wang#, Yang Li#, Cankun Wang, Chan-Wang Jerry Lio, Qin Ma*, Bingqiang Liu* Briefings in Bioinformatics, 2024 Jan 06, 25(1): 1-8. (SCI, IF 9.500)
4. MarsGT: Multi-omics analysis for rare population inference using single-cell graph transformer. Xiaoying Wang#, Maoteng Duan#, Jingxian Li, AnjunMa, Gang Xin, Dong Xu, Zihai Li, Bingqiang Liu*, QinMa*. Nature Communications, 2024, 15:338. (SCI, IF16.600)
5. Inference of disease-associated microbial gene modules based on metagenomic and meta-transcriptomic data. Zhaoqian Liu, Qi Wang, Anjun Ma, Shaohong Feng, Dongjun Chung, Jing Zhao, Qin Ma*, Bingqiang Liu*. Computers in Biology and Medicine, 2023. 165(107458). (SCI, IF7.700)
6. Computational methods and challenges in analyzing intratumoral microbiome data. Qi Wang, Zhaoqian Liu, Anjun Ma, Zihai Li, Bingqiang Liu*, Qin Ma*. Trends in Microbiology. 2023. 31(7): 707-722. (SCI, IF18.230)
7. Single-cell biological network inference using a heterogeneous graph transformer. Anjun Ma#, Xiaoying Qang#, Jingxian Li, Cankun Wang, Tong Xiao, Yuntao Liu, Hao Cheng, Juexin Wang, Yang Li, Yuzhou Chang, Jinpu Li, Duolin Wang, Yuexu Jiang, Li Su, Gang Xin, Shaopeng Gu, Zihai Li, Bingqiang Liu*, Dong Xu*, Qin Ma*. Nature Communications, 2023, 14:964. (SCI, IF17.694)
8. Deep transfer learning of cancer drug responses by integrating bulk and single-cell RNA-seq data, Junyi Chen#, Xiaoying Wang#, Anjun Ma*, Qi-En Wang, Bingqiang Liu, Lang Li, Dong Xu, Qin Ma*, Nature Communications, 2022, 13:6494. (SCI, IF17.694)
9. Define and visualize pathological architectures of human tissues from spatially resolved transcriptomics using deep learning, Yuzhou Chang#, Fei He#, Juexin Wang#, Shuo Chen, Jingyi Li, Jixin Liu, Yang Yu, Li Su, Anjun Ma, Carter Allen, Yu Lin, Shaoli Sun, Bingqiang Liu, José Javier Otero, Dongjun Chung, Hongjun Fu, Zihai Li, Dong Xu, Qin Ma. Computational and Structural Biotechnology Journal, 2022, V20: 4600-4617. (SCI, IF 6.155)
10. Leveraging Existing 16SrRNA Microbial Data to Define a Composite Biomarker for Autism Spectrum Disorder, Yushuang Xu#, Yihua Wang#, Jinshuang Xu, Yu Song, Bingqiang Liu*, Zhifan Xiong*, Microbiology Spectrum. 2022, 10(4): e0033122. (SCI, IF 9.043)
11. DESSO-DB: A web database for sequence and shape motif analyses and identification. Xiaoying Wang, Cankun Wang, Lang Li, Qin Ma, Anjun Ma*, Bingqiang Liu*, Computational and Structural Biotechnology Journal, 2022, V20: 3053-3058. (SCI, IF 6.155)
12. A novel computational framework for genome-scale alternative transcription units prediction. Qi Wang, Zhaoqian Liu, Bo Yan,Wen-Chi Chou, Laurence Ettwiller, Qin Ma* and Bingqiang Liu*, Briefings in bioinformatics, 2021, Nov 22(6). (SCI, IF 13.994)
13. The functional determinants in the organization of bacterial genomes. Zhaoqian Liu, Jingtong Feng, Bin Yu, Qin Ma*, and Bingqiang Liu*, Briefings in bioinformatics, 2021 May 20; 22(3). (SCI, IF 13.994)
14. Network analyses in microbiome based on high-throughput multi-omics data. Zhaoqian Liu#, Anjun Ma#, Ewy Mathé, Marlena Merling, Qin Ma*, and Bingqiang Liu*, Briefings in bioinformatics, 2021, Mar 22(2):1639-1655. (SCI, IF 13.994)
15. Prediction of protein–protein interactions based on elastic net and deep forest, Bin Yu#*, Cheng Chen#, Xiaolin Wang, Zhaomin Yu, Anjun Ma, Bingqiang Liu. Expert Systems with Applications, 2021 Aug. 15, 176: 114876. (SCI, IF6.954)
16. LncRNA DGCR5 Isoform-1 Silencing Suppresses the Malignant Phenotype of Clear Cell Renal Cell Carcinoma via miR-211-5p/Snail Signal Axis, Guangxin Zhong, Dan Luo, Yijun Fan, Jue Wang, Bingqiang Liu, Zhonghua Xu and Xiang Zhang*, Frontiers in Cell and Developmental Biology, 2021 12 Jul. 9(700029). (SCI, IF6.684)
17. GTB-PPI: Prediction of protein-protein interactions based on L1-regularized logistic regression and gradient tree boosting. Bin Yu*, Cheng Chen, Hongyan Zhou, Bingqiang Liu, Qin Ma*. Genomics, Proteomics & Bioinformatics, 2020, Oct. 18(5): 582-592. (SCI, IF7.691)
18. Elucidation of Biological Networks across Complex Diseases Using Single-Cell Omics. Yang Li, Anjun Ma, Ewy A. Mathé, Lang Li, Bingqiang Liu*, and Qin Ma*, Trends in Genetics, 2020, 36(12): 951-966. (SCI, IF 11.821)
19. DNNAce: Prediction of prokaryote lysine acetylation sites through deep neural networks with multi-information fusion. Bin Yu, Yu Zhaomin, Cheng Chen, Anjun Ma, Bingqiang Liu, Baoguang Tian, and Qin Ma, Chemometrics and Intelligent Laboratory Systems, 2020, 200: 103999. (SCI, IF 2.895)
20. IRIS3: integrated cell-type-specific regulon inference server from single-cell RNA-Seq. Anjun Ma, Cankun Wang, Yuzhou Chang, Faith H Brennan, Adam McDermaid, Bingqiang Liu, Chi Zhang, Phillip G Popovich, Qin Ma*, Nucleic Acids Research, 2020, 48(W1): W275-W286. (SCI, IF 19.161)
21. QUBIC2: a novel and robust biclustering algorithm for analyses and interpretation of large-scale RNA-Seq data. Juan Xie, Anjun Ma, Yu Zhang, Bingqiang Liu, Sha Cao, CankunWang, Jennifer Xu, Chi Zhang,* and Qin Ma*, Bioinformatics, 36(4), 2020, 1143–1149. (SCI, IF 6.937)
22. Identification of lncRNAs-gene interactions in transcription regulation based on co-expression analysis of RNA-seq data. Sijie Lu, Juan Xie, Yang Li, Bin Yu, Qin Ma*, and Bingqiang Liu*, Mathematical Biosciences and Engineering, 2019, 16(6), 7112-7125. (SCI, IF 2.194)
23. Prediction of regulatory motifs from human Chip-sequencing data using a deep learning framework. Jinyu Yang, Anjun Ma, Adam D. Hoppe, Cankun Wang, Yang Li, Chi Zhang, Yan Wang, Bingqiang Liu*, and Qin Ma*, Nucleic Acids Research, 2019, 47(15), 7809–7824. (SCI, IF 19.161)
24. MetaQUBIC: a computational pipeline for gene-level functional profiling of metagenome and metatranscriptome. Anjun Ma, Minxuan Sun, Adam McDermaid, Bingqiang Liu, Qin Ma*, Bioinformatics, 2019, 35(21): 4474–4477. (SCI, IF 5.61)
25. Interpretation of differential gene expression results of RNA-seq data: review and integration. Adam McDermaid, Brandon Monier, Jing Zhao, Bingqiang Liu, Qin Ma*, Briefings in bioinformatics, 2019, 20(6): 2044-2054. (SCI, IF 13.994)
26. rSeqTU-a machine-learning based R package for prediction of bacterial transcription units. Sheng-Yong Niu, Bingqiang Liu, Qin Ma* and Wen-Chi Chou*, Frontiers in Genetics, 2019, 10: 374. (SCI, IF 4.599)
27. Protein-protein interaction sites prediction by ensemble random forests with synthetic minority oversampling technique. Xiaoying Wang#, Bin Yu#*, Cheng Chen, Anjun Ma, Bingqiang Liu, Qin Ma*, Bioinformatics, 2019, 35(14): 2395–2402. (SCI, IF 6.937)
28. MiMod: A New Algorithm for Mining Biological Network Modules. Yang Li, Bingqiang Liu, Jing Li, Guojun Li*, IEEE Access, 2019, 7, 2909946. (SCI, IF 4.199)
29. Computational prediction of sigma-54 promoters in bacterial genomes by integrating motif finding and machine learning strategies. Bingqiang Liu, Ling Han, Xiangrong Liu, Jichang Wu, Qin Ma*, IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2019. 16(4): 1211–1218. (SCI, IF 3.702)
30. An algorithmic perspective of de-novo cis-regulatory motif finding based on ChIP-seq data. Bingqiang Liu, Jinyu Yang, Yang Li, Adam McDermaid, Qin Ma*, Briefings in Bioinformatics, 2018, 19(5): 1069-1081. (SCI, IF 13.994)
承担国家级项目：
1. 国家自然科学基金委员会，面上项目，基于单细胞多组学数据的细胞特异性分析及其调控机制相关算法研究，2023-2026，项目负责人；
2. 科技部，国家重点研发计划，乳腺癌精准医学中的数学模型和算法研究，2020-2025，项目负责人；
3. 科技部，创新工作方法专项，基于机器学习的智能创新方法关键技术研究与应用示范，2018-2021，课题负责人；
4. 国家自然科学基金委员会，面上项目，基于新一代测序数据的顺式调控模体预测与分析，2018-2021，项目负责人；
5. 国家自然科学基金委员会，重点项目，基于图与组合优化的生物数据和网络数据挖掘算法研究，2020-2024，项目骨干；
6. 国家自然科学基金委员会，重点项目，基于高通量RNA-seq数据转录组拼接的关键技术与算法研究，2015-2019，项目骨干；
7. 国家自然科学基金委员会，青年项目，基于ChIP-seq数据和系统发生信息的调控模体预测，2014-2016，项目负责人；
8. 国家自然科学基金委员会，面上项目，仅基于RNA-Seq数据拼装可变剪接转录组的计算方法研究，2013-2016，项目骨干；
9. 国家自然科学基金委员会，面上项目，原核生物转录因子结合位点的算法预测及应用，2011-2013，项目骨干；
