讲师

姓名:苏令涛 性别:男 学历:博士研究生

职称:讲师 办公室:J13-322 隶属部门:人工智能系

联系方式:Sulingtao@163.com

个人简介:

苏令涛,博士,山东省临沂市费县人。研究方向为生物信息学,通过使用当前主流的机器学习模型和数据挖掘技术对各种生物数据进行处理、挖掘和分析等,从而解决与人类息息相关的生命科学问题。在国内外知名期刊累积发表学术论文20余篇,获国家发明专利1项。先后参与生物信息领域国家自然基金项目3项,吉林省科技创新项目1项,参与美国自然基金重大项目3项。主持“吉林大学研究生创新研究计划”项目1项。2021年全职回国,加入山东科技大学计算机科学与工程学院。现担任CCF生物信息专业委员会通讯委员。

详细信息:

苏令涛1.jpeg

教育经历:
(1) 2015-09 至 2019-12, 吉林大学, 计算机应用技术, 博士

(2) 2012-09 至 2015-06, 吉林大学, 计算机应用技术, 硕士

(3) 2008-09 至 2012-06, 山东师范大学, 计算机科学与技术, 学士

工作经历:

(1) 2021-11 至今, 山东科技大学, 计算机科学与工程学院, 讲师

(2) 2019-12 至 2021-10, 美国密苏里大学哥伦比亚校区。

访学经历:

(1) 2017-08 至 2019-08, 美国密苏里大学哥伦比亚校区, 工学院

详细信息:

代表性论文列表:

1.      Lingtao Su, Chunhui Xu, Shuai Zeng, Li Su, Trupti Joshi, Gary Stacey. Large-Scale Integrative Analysis of Soybean Transcriptome Using an Unsupervised Autoencoder Model. Frontiers in Plant Science, 2022, 13. https://doi.org/10.3389/fpls.2022.831204.

2.      Lingtao Su, Guixia Liu, Juexin Wang, Jianjiong Gao, Dong Xu. Detecting Cancer Survival Related Gene Markers Based on Rectified Factor Network. Frontiers in Bioengineering and Biotechnology, 2020,8:349. PMID: 32426342.

3.      Lingtao Su, Guixia Liu, Juexin Wang, Dong Xu. A rectified factor network based biclustering method for detecting cancer-related coding genes and miRNAs, and their interactions. Methods, 2019, 166:22-30. PMID: 31121299.

4.      Lingtao Su, Dong Xu, Guixia Liu. A new method for disease-related gene prioritization. IEEE International Conference on Bioinformatics and Biomedicine (BIBM), Kansas City, MO, 2017, pp. 2315-2315.

5.      Lingtao Su, Guixia Liu, Tian Bia, Xiangyu Meng, Qingshan Ma. MGOGP: a gene module-based heuristic algorithm for cancer-related gene prioritization. BMC Bioinformatics, 2018, 19:215. PMID: 29871590.

6.      Lingtao Su, Xiangyu Meng, Qingshan Ma, Tian Bai, Guixia Liu. LPRP: A Gene-Gene Interaction Network Construction Algorithm and Its Application in Breast Cancer Data Analysis. Interdisciplinary sciences, computational life sciences, 2018, 10(1):131–142. PMID: 27640171.

7.      Lingtao Su, Guixia Liu, Han Wang, Yuan Tian, Zhihui Zhou, Liang Han, Lun Yan. Research on single nucleotide polymorphisms interaction detection from network perspective. PloS one, 2015, 10(3), e0119146. PMID: 25763929.

8.      Lingtao Su, Guixia Liu, Han Wang, Yuan Tian, Zhihui Zhou, Liang Han, Lun Yan. GECluster: a novel protein complex prediction method. Biotechnol Biotechnol Equip. 2014, 28(4):753-761. PMID: 26019559.

9.      Lingtao Su, Guixia Liu, Zhihui Zhou, Liang Han, Lun Yan. PPCMP: A method for protein complex prediction. Journal of Computational Information Systems, 2014, 10(13):5657-5664.

10.  刘桂霞,苏令涛,孟祥宇,马青山。 一种特定癌症差异表达基因调控网络的构建方法。 2018, 专利号:ZL201610128387.8

11.  Liyan Sun, Guixia Liu, Lingtao Su,Rongquan Wang. SEE: a novel multi-objective evolutionary algorithm for identifying SNP epistasis in genome-wide association studies, Biotechnology & Biotechnological Equipment, 2019, 33:1, 529-547. Online link: https://doi.org/10.1080/13102818.2019.1593052                                                                                                                       

12.  Liyan Sun, Guixia Liu, Lingtao Su, Rongquan Wang. HS-MMGKG: A Fast Multi-objective Harmony Search Algorithm for Two-locus Model Detection in GWAS, Current Bioinformatics, 2019, 14: 749. Online link: https://doi.org/10.2174/1574893614666190409110843

13.  Rongquan Wang, Guixia Liu, Caixia Wang, Lingtao Su, Liyan Sun. Predicting overlapping protein complexes based on core-attachment and a local modularity structure. BMC Bioinformatics, 2018, 19:305.

14.  Shuai Meng, Guixia Liu, Lingtao Su, Liyan Sun, Di Wu, Lingwei Wang, Zhao Zheng. Functional clusters analysis and research based on differential coexpression networks, Biotechnology & Biotechnological Equipment, 2018, 32:1, 171-182.

15.  Li Zhang, Han Wang, Lun Yan, Lingtao Su, Dong Xu. OMPcontact: An Outer Membrane Protein Inter-Barrel Residue Contact Prediction Method. ournal of Computational Biology, 2017, 24 (3), 217-228. PMID: 27513917

16.  Zhihui Zhou, Guixia Liu, Lingtao Su. A new approach to detect epistasis utilizing parallel implementation of ant colony optimization by MapReduce framework. International Journal of Computer Mathematics, 2016, 93 (3), 511-523.

17.  Zhihui Zhou, Guixia Liu, Lingtao Su, Lun Yan, Liang Han. Cchi: An efficient cloud epistasis test model in human genome wide association studies. 6th International Conference on Biomedical Engineering and Informatics, 2013, pp. 787-791.

18.  Zhihui Zhou, Guixia Liu, Lingtao Su, Liang Han, Lun Yan. A New Epistasis Detecting Algorithm Based on Ant Colony Optimization. In Proceedings of International Conference on Internet Multimedia Computing and Service (ICIMCS '14). Association for Computing Machinery, New York, NY, USA, 2014, 226–231.

19.  Zhihui Zhou, Guixia Liu, Lingtao Su, Liang Han, Lun Yan. Detecting Epistasis by LASSO-penalized-model Search Algorithm in Human Genome-Wide Association Studies, Advanced Materials Research, 2014, 989, 2426-2430.

20.  刘桂霞,王沫沅,苏令涛,吴春国,孙立岩,王荣全。基于深度神经网络的蛋白质相互作用预测框架,《吉林大学学报(工学版)》,2019年02期。

21.  Chang H, Zhang H, Zhang T, et al. A Multi-Level Iterative Bi-Clustering Method for Discovering miRNA Co-regulation Network of Abiotic Stress Tolerance in Soybeans. Frontiers in Plant Science, 2022, 13.