代志军

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一、个人简介

代志军:男,1986年4月生,博士、副教授、硕士生导师、美国密歇根州立大学博士后。湖南省生物信息学会会员,湖南省农业大数据分析与决策工程技术研究中心秘书、校“1515”学术骨干人才。主讲《基因组学》、《机器学习-实验》、《科技论文写作》等课程。主要从事动植物全基因组选择/预测育种、计算机辅助药物设计、病虫害智能预测预报等领域的算法开发及应用研究。

二、教育背景

2017/08–2019/01:美国密歇根州立大学,数量遗传学与基因组学研究组,博士后研究员

2011/09–2014/12:湖南农业大学,生物信息学专业,博士

2008/09–2011/06:湖南农业大学,生物信息学专业,硕士

2004/09–2008/06:湖北工程学院,生物科学专业,学士

三、成果介绍

1. 主持或参与的主要科研项目

1) 国家自然科学青年基金项目,31701164,基于变量选择与训练群体优化的植物基因组选择方法研究,2018/01-2020/12, 主持

2) 国家自然科学基金面上项目,32272567,内生菌诱导GST介导棒头草对精喹禾灵抗性机制,2023/01-2026/12, 参与

3) 国家自然科学基金面上项目,31670689,CRISPR/Cas9介导的茶树基因组定向编辑系统构建及茶树遗传转化体系改良,2017/01-2020/12, 参与

4) 湖南省自然科学青年基金项目,2018JJ3238,水稻数量性状全基因组选择新方法及应用,2018/01-2020/12, 主持

5) 湖南省科技重大专项-湖南省种业创新项目(子课题),2021NK1011,基于CNN深度学习的基因组选择模型构建技术与应用,2022/01-2024/10,参与

6) 湖南省教育厅科学研究优秀青年项目,22B0208,基于构效关系与分子对接的PPO抑制型除草剂合理设计,2022/11-2024/12, 主持

7) 湖南省教育厅科学研究一般项目,16C0776,方差分析与直接分类用于RNA-seq 癌基因表达分析,2016/09-2018/12, 主持

8) 作物种质创新与资源利用国家重点实验室培育基地开放项目,15KFXM11,基于最大互信息系数与直接分类的水稻蛋白质相互作用预测,2016/04-2018/03, 主持

9) 湖南农业大学青年科学基金项目,16QN33,高维特征选择与直接分类用于癌症差异甲基化研究,2016/09-2018/12, 主持

 

2. 主要科研论文(=Equal contribution, @Correspondence)

2023

31)  Zilan Ning, Zhijun Dai, Hongyan Zhang, Yuan Chen@, Zheming Yuan@. A clustering method for small scRNA-seq data based on subspace and weighted distance. PeerJ, 2023, 11: e14706.

2022

30)  Zilan Ning, Jin Chen, Jianjun Huang, Umar Jlbrilla Sabo, Zheming Yuan@, Zhijun Dai@. WeDIV – An improved k-means clustering algorithm with a weighted distance and a novel internal validation index. Egypt Inform J, 2022, 23(4): 133-144.

29)  Heng Zhou, Qingfang Ba, Zheming Yuan, Zhijun Dai@. QSAR Modeling on Angiotensin-Converting Enzyme Inhibitory Peptides Based on Stepwise Non-linear Regression. Chemistry (化学通报, CSCD), 2022, 85(6): 736-745.

28)  Sidong Qin=, Yanjun Fan=, Shengnan Hu, Yongqiang Wang, Ziqi Wang, Yixiang Cao, Qiyuan Liu, Siqiao Tan@, Zhijun Dai@, and Wei Zhou@. iPReditor-CMG: Improving a predictive RNA editor for crop mitochondrial genomes using genomic sequence features and an optimal support vector machine. Phytochemistry, 2022, 200, 113222.

2021

27)  Zhijun Dai, Heng Zhou, Qingfang Ba, Yang Zhou, Lifeng Wang@, and Guochen Li@. Improving depression prediction using a novel feature selection algorithm coupled with context-aware analysis. J Affect Disorders, 2021, 295: 1040-1048.

2020

26)  Yuting Li, Zhijun Dai, Dan Cao, Feng Luo, Yuan Chen@, and Zheming Yuan@. Chi-MIC-share: a new feature selection algorithm for quantitative structure–activity relationship models. RSC Advances, 2020, 10(34): 19852-19860.

25)  Zheming Yuan=, Yi Xiao=, Zhijun Dai, Jianjun Huang, Zhenhai Zhang@, Yuan Chen@. Modelling the effects of Wuhan’s lockdown during COVID-19, China. Bull World Health Organ, 2020, 98(7): 484–494.

24)  Zhijun Dai, Nanye Long, Wen Huang@. Influence of Genetic Interactions on Polygenic Prediction. G3-Genes Genom Genet, 2020, 10(1): 109-115.

2019

23)  Lifeng Wang, Pengwei Xing, Cong Wang, Xiaomao Zhou, Zhijun Dai@, Lianyang Bai@. Maximal Information Coefficient and Support Vector Regression Based Nonlinear Feature Selection and QSAR Modeling on Toxicity of Alcohol Compounds to Tadpoles of Rana temporaria. J Brazil Chem Soc, 2019, 30(2): 279-285.

2018

22)  Qian Xu, Li Xiao, Li Zeng, Zhijun Dai@, Ying Wu@. Pediatric burns in South Central China: an epidemiological study. Int J Clin Exp Med, 2018, 11(9): 9280-9287.

2017

21)  Xueli Zhang=, Congwei Sun=, Zheng Zhang, Zhijun Dai, Yuan Chen, Xiong Yuan, Zheming Yuan, Wenbang Tang, Lanzhi Li@, Zhongli Hu. Genetic dissection of main and epistatic effects of QTL based on augmented triple test cross design. PLoS ONE, 2017, 12(12): e0198054.

20)  Zheng Zhang, Xueli Zhang, Bocheng Mo, Zhijun Dai, Zhongli Hu, Lanzhi Li@, Xingfei Zheng@. Combining Ability Analysis of Agronomic Trait in Indica × Indica Hybrid Rice. Acta Agronomica Sinica (作物学报, CSCD), 2017, 43(10): 1448-1457.

2016

19)  Wei Zhou, Yanjun Fan, Xunhui Cai, Yan Xiang, Peng Jiang, Zhijun Dai, Yuan Chen, Siqiao Tan, Zheming Yuan@. High-accuracy QSAR models of narcosis toxicities of phenols based on various data partition, descriptor selection and modelling methods. RSC Advances, 2016, 6(108): 106847-106855.

2015

18)  Wei Zhou=, Shubo Wu=, Zhijun Dai=, Yuan Chen, Yan Xiang, Jianrong Chen, Congwei Sun, Qingming Zhou@, Zheming Yuan@. Nonlinear QSAR models with high-dimensional descriptor selection and SVR improve toxicity prediction and evaluation of phenols on Photobacterium phosphoreum. Chemometr Intell Lab, 2015, 145, 30-38.

17)  Congwei Sun=, Zhijun Dai=, Hongyan Zhang, Lanzhi Li@, and Zheming Yuan@. Binary Matrix Shuffling Filter for Feature Selection in Neuronal Morphology Classification. Comput Math Method M, 2015, Article ID 626975, 9 pages.

16)  Li Yang, Congwei Sun, Zhijun Dai, Miao He, Zheming Yuan@. Expansion of the Molecular Network Related to Petal Development Based on MADS-box Proteins and Protein-Protein Interaction Network in Arabidopsis thaliana. Chin Bull Bot (植物学报, CSCD), 2015, 50(5): 614-622.

2014

15)  Zhijun Dai, Lifeng Wang, Yuan Chen, Haiyan Wang, Lianyang Bai, Zheming Yuan@. A pipeline for improved QSAR analysis of peptides: physiochemical property parameter selection via BMSF, near-negighbor sample selection via semivariogram, and weighted SVR regression and prediction. Amino Acids, 2014, 46(4): 1105-1119.

14)  Lifeng Wang=, Zhijun Dai=, Hongyan Zhang, Lianyang Bai, Zheming Yuan@. Quantitative Sequence-Activity Model Analysis of Oligopeptides Coupling an Improved High-Dimension Feature Selection Method with Support Vector Regression. Chem Biol Drug Des, 2014, 83(4): 379-391.

13)  Kai Wang, Lifeng Wang, Zhijun Dai, Lianyang Bai, Zheming Yuan@. QSAR modeling of E. coli promoters with parameters selected by binary matrix shuffling filter. J Indian Chem Soc, 2014, 91(12): 2247-2253.

12)  Yong Li, Wei Zhou, Zhijun Dai, Yuan Chen, Zhiming Wang, Zheming Yuan@. Predicting the Protein Folding Rate Based on Sequence Feature Screening and Support Vector Regression. Acta Phys -Chim Sin, 2014, 30(6): 1091-1098.

11)  Jinghua Liang, Congwei Sun, Zhijun Dai, Li Yang, Zheming Yuan@. Nonlinear quantitative structure-activity relationship of amide mosquito repellent. Chinese Journal of Pesticide Science (农药学学报, CSCD), 2014, 16(6): 644-650.

10)  Hongyan Zhang, Lanzhi Li, Chao Luo, Congwei Sun, Yuan Chen, Zhijun Dai, Zheming Yuan@. Informative Gene Selection and Direct Classification of Tumor Based on Chi-Square Test of Pairwise Gene Interactions. Biomed Res Int, 2014, Article ID 589290, 9 pages.

2013

9)   Wei Zhou, Zhijun Dai, Yuan Chen, Zheming Yuan@. Computational QSAR models with high-dimensional descriptor selection improve antitumor activity design of ARC-111 analogues. Med Chem Res, 2013, 22(1): 278-286.

8)   Haiyan Wang, Hongyan Zhang, Zhijun Dai, Mingshun Chen, Zheming Yuan@. TSG: a new algorithm for binary and multi-class cancer classification and informative genes selection. BMC Med Genomics, 2013, 6(Suppl 1):S3.

7)   Lanzhi Li, Congwei Sun, Yuan Chen, Zhijun Dai, Zhen Qu, Xingfei Zheng, Sibin Yu, Tongmin Mou, Chenwu Xu@, Zhongli Hu@. QTL mapping for combining ability in different population-based NCIIdesigns: a simulation study. J Genet, 2013, 92(3): 529-543.

6)   Na Han, Zheming Yuan@, Yuan Chen, Zhijun Dai, Zhiming Wang. Prediction of HLA-A@0201 Restricted Cytotoxic T Lymphocyte Epitopes Based on High-Dimensional Descriptor Nonlinear Screening. Acta Phys -Chim Sin, 2013, 29(9): 1945-1953.

2012

5)  Wei Zhou=, Zhijun Dai=, Yuan Chen, Haiyang Wang, Zheming Yuan@. High-dimensional descriptor selection and computational qsar modeling for antitumor activity of arc-111 analogues based on support vector regression (SVR). Int J Mol Sci, 2012, 13(1): 1161-1172.

4)   Hongyan Zhang, Haiyan Wang, Zhijun Dai, Mingshun Chen, Zheming Yuan@. Improving accuracy for cancer classification with a new algorithm for genes selection. BMC bioinformatics, 2012, 13:298.

3)   Manxiu Su, Lifeng Wang, Zhijun Dai, Zheming Yuan@, Lianyang Bai. Primary Structural Characterizations of Polypeptide and Antimicrobial Peptides QSAM Modeling. Chem J Chinese U, 2012, 33(11): 2526-2531.

2011

2)   Weiwei Li, Zhijun Dai, Xiansheng Tan, Zheming Yuan@. Phenol Compounds QSAR Modeling Based on Support Vector Regression. Prog Mod Biomed (现代生物医学进展), 2011, 11(24): 4857-4860.

1)   Zhijun Dai, Wei Zhou, Zheming Yuan@. A novel method of nonlinear rapid feature selection for high-dimensional features and its application in peptide QSAR modeling based on support vector machine. Acta Phys -Chim Sin, 2011, 27(7): 1654-1660.

 

3. 主要获奖成果

个人获奖:

1) 2022年湖南农业大学课堂教学竞赛三等奖

2) 2021年湖南农业大学年度考核优秀

3) 2019年湖南省教学成果三等奖(排名5)

4) 2019年湖南农业大学教学成果一等奖(排名5)

5) 2017年青年教师配备导师考核优秀

6) 2017年湖南农业大学教师课程教学考核优秀(生物统计学)

7) 2016年湖南农业大学年度考核优秀

8) 2016年湖南省自然科学三等奖(排名4)

9) 2014年第十届北美校友奖学金

10) 2014年湖南农业大学科研成就一等奖

11) 2013年湖南省优秀硕士学位论文

 

指导学生获奖:

1) 2023年全国高校数学建模挑战赛三等奖

2) 2023年校大学生生命科学创新创业大赛二等奖

3) 2023年校“挑战杯”大学生课外学术科技作品竞赛三等奖

4) 2022年全国大学生生命科学竞赛一等奖

5) 2022年湖南农业大学本科生百优毕业论文

6) 2021年校“互联网+”大学生创新创业大赛三等奖

7) 2016年全国研究生数学建模竞赛二等奖

8) 2015年湖南省研究生数学建模竞赛三等奖

 

4. 主持或参与的教改项目

1) 中国农学会教育教学类科研课题,PCE1606,“互联网+农业”新引擎助力创新创业教育改革,2016/11-2018/12, 主持

2) 湖南省教学改革重点项目,HNJG-2021-0073,新农科生物信息学分类培养体系的探索与实践,2021/10-2024/09, 参与

3) 湖南农业大学教学改革项目,XJJG-2020-074,疫情常态化防控背景下新农科学生分类培养体系的探索与实践——以《生物信息学》课程为例,2020/10-2022/10, 参与

4) 湖南农业大学教学改革项目,湘农教发【2019】68号,基于“个性化发展”的《R语言与生物统计学》“慕课学习+翻转课堂”教学模式研究,2019/09-2022/09, 参与

5) 湖南省大学生创业训练计划项目(推评为国家级),L&F天目定位贴纸,2020/06-2021/07, 李亚岚等 (指导)

 

5. 课程建设

1) 2021年,湖南省双一流本科课程,《R语言与生物统计学》,参与

2) 2018年,湖南省在线精品课程建设项目,《R语言与生物统计学》,参与