胡学海

姓名

胡学海

性别


职称

教授

学位

博士

电话


邮箱

huxuehai@mail.hzau.edu.cn

政治面貌

中共党员

工作单位

bat365官网登录入口bat365官网登录入口

研究方向

1. 生物信息学:长期从事调控基因组及精准编辑方向研究,如AI引导下的植物关键顺式元件识别、转录因子结合位点预测、增强子核心区域预测等。

2. 统计遗传学:长期从事基于整合基因组、转录组、代谢组等多组学数据对人类复杂疾病、植物复杂性状的机制解析、表型预测等统计遗传方法的研究。


教育经历

1998.09-2002.06 武汉大学;信息与计算科学;本科

2002.09-2007.06 武汉大学;基础数学; 博士;分形几何学

主要职历

2007.07-2010.12 bat365官网登录入口理学院 讲师

2011.01-2014.06 bat365官网登录入口理学院 副教授

2014.07-2020.11 bat365官网登录入口bat365官网登录入口 副教授

2020.12-至今;bat365官网登录入口bat365官网登录入口 教授

科研成果

胡学海,男,教授,博士生导师。2002年本科毕业于武汉大学数学系,2007年获武汉大学基础数学博士学位。2007年7月起在bat365官网登录入口任讲师,2010年晋升为副教授,2013年聘为硕士生导师,2019年聘为博士生导师,2020年晋升为教授,2023年入选狮山硕彦拔尖人才B岗。现任bat365官网登录入口bat365官网登录入口大数据科学系主任。主讲《离散数学》、《神经网络与深度学习》、《生物统计》等本科和研究生课程。2017全年在美国加州大学河滨分校做国家公派访问学者。主要从事基于深度学习的调控基因组及精准编辑方向,以及整合多组学数据的表型预测等两个方向的研究。主持国家重点研发课题项目一项(2023YFD1202903),主持国家自然科学基金面上项目两项(32070689,11671003),青年基金一项(11001093)。



科研项目:

1. 主持国家重点研发计划“主要农作物基因编辑种质精准创制技术”中课题3《深度学习联合基因编辑与农作物种质创制》,批准号:2023YFD1202903,时间:2023.12-2028.11,120万元;

2. 主持国家自然科学基金面上项目《基于有向学习策略的整合多组学数据的基因组预测统计模型研究》,批准号:32070689,时间:2021.01-2024.12,58万元;

3. 主持国家自然科学基金面上项目《分形与序列复杂度方法在DNA调控元件预测中的应用》,批准号:11671003,时间:2017.01-2020.12,48万元;

4. 主持国家自然科学基金青年基金《形式级数域上若干丢番图逼近问题的分形性质研究》,批准号:11001093,时间:2011.01-2013.12,17万元;

5. 参与国家自然科学基金面上项目子项目《分形方法在分子进化与蛋白质研究中的应用》,批准号:11371016,时间:2014.01-2017.12,9.5万元;


期刊论文:发表科研论文20余篇,其中以第一或通讯作者发表SCI论文18篇,分别发表在Plant Biotechnology Journal、Plant Communications、Bioinformatics、Briefings in Bioinformatics等国际刊物上,同时担任Nature Communications、Plant Biotechnology Journal、The Plant Journal、Bioinformatics等多个SCI期刊的审稿人。主要论文目录如下:


[1] Kaixuan Deng#, Qizhe Zhang#, Yuxin Hong, Jianbing Yan* and Xuehai Hu*. iCREPCP: A deep learning-based web server for identifying base-resolution cis -regulatory elements within plant core promoters. Plant Communications. 2023, 4(1), 100455.
[2] Xuehai Hu#*, Alisdair R. Fernie and Jianbing Yan*. Deep Learning in Regulatory Genomics: From Identification to Design. Current Opinion in Biotechnology. 2023 Feb;79:102887.
[3] Huiling Cheng#, Lifen Liu#, Yuying Zhou, Kaixuan Deng, Yuanxin Ge and Xuehai Hu*. TSPTFBS 2.0: trans-species prediction of transcription factor binding sites and identi fi cation of their core motifs in plants. Frontiers in Plant Science. 2023, 14:1175837.
[4] Xiaohui Niu#, Kaixuan Deng, Lifen Liu, Kun Yang, Xuehai Hu*. A statistical framework for predicting critical regions of p53-dependent enhancers. Briefings in Bioinformatics, 2021, May 20; 22(3):bbaa053. doi: 10.1093/bib/bbaa053.
[5] Lifen liu#, Ge Zhang#, Shoupeng He, Xuehai Hu*. TSPTFBS: a Docker image for trans-species prediction of transcription factor binding sites in plants. Bioinformatics, 2021, Jan 8; 37(2):260-262.
[6] Xuehai Hu#, Weibo Xie, Chengchao Wu, Shizhong Xu*. A directed learning strategy integrating multiple omic data improves genomic prediction. Plant Biotechnology Journal. 2019 Oct; 17(10):2011-2020. doi: 10.1111/pbi.13117.
[7] Xiaohui Niu#, Kun Yang#, Ge Zhang, Zhiquan Yang and Xuehai Hu*. A Pretraining-Retraining Strategy of Deep Learning Improves Cell-Specific Enhancer Predictions. Frontiers in Genetics, 2020 Jan 8;10:1305.
[8] Chengchao Wu#, Jin Chen#, Yunxia Liu, Xuehai Hu*. Improved Prediction of Regulatory Element Using Hybrid Abelian Complexity Features with DNA Sequences. International Journal of Molecular Sciences, 2019, 20, 1704. doi: 10.3390/ijms20071704.
[9] Chengchao Wu, Shixin Yao, Xinghao Li, Chujia Chen and Xuehai Hu*. Genome-Wide Prediction of DNA Methylation Using DNA Composition and Sequence Complexity in Human.  International Journal of Molecular Sciences, 2017, 18, 420.
[10] Xiaohui Niu, Xuehai Hu*. Improved prediction of DNA-binding proteins using chaos game representation and random forest. Current Bioinformatics, 2016, 11(2): 156-163.
[11] Hongchu Wang, Xuehai Hu*. Accurate prediction of nuclear receptors with conjoint triad feature. BMC Bioinformatics, 2015, 16:402. doi: 10.1186/s12859-015-0828-1.
[12] Guoping Nie, Yong Li, Feichi Wang, Siwen Wang, Xuehai Hu*. A novel fractal approach for predicting G-protein–coupled receptors and their subfamilies with support vector machines. Bio-Medical Materials and Engineering, 2015, 26, s1, 1829-1836. doi: 10.3233/BME-151485.
[13] Yaping Lu, Yemao Liu, Xiaohui Niu, Qingyong Yang, Xuehai Hu, HongYu Zhang and Jingbo Xia*. Systems Genetic Validation of the SNP-Metabolite Association in Rice Via Metabolite-Pathway-Based Phenome-Wide Association Scans.  Frontiers in Plant Science, 2015, Nov 27; 6:1027.
[14] Xiaohui Niu, Xuehai Hu*, Feng Shi and Jingbo Xia. Predicting DNA binding proteins using support vector machine with hybrid fractal features. Journal of Theoretical Biology, 2014, 343, 186-192. doi: 10.1016/j.jtbi.2013.10.009.
[15] Jinlong Lu, Xuehai Hu* and Donggang Hu. A new hybrid fractal algorithm for predicting thermophilic nucleotide sequences.  Journal of Theoretical Biology, 2012, 293, 74-81. doi: 10.1016/j.jtbi.2011.09.028.
[16] Xiaohui Niu, Xuehai Hu*, F Shi and J. B. Xia. Predicting protein solubility by the general form of Chou's pseudo amino acid composition: approached from chaos game representation and fractal dimension.  Protein & Peptide Letters, 2012, 19 (9), 940-948. doi: 10.2174/092986612802084492.
[17] Xiaolei Liu, Jinlong Lu, and Xuehai Hu*. Predicting thermophilic proteins with pseudo amino acid composition: approached from chaos game representation and principal component analysis, Protein & Peptide Letters, 2011, 18 (12), 1244-1250. doi: 10.2174/092986611797642661.
[18] Jingbo Xia, Silan Zhang*, Feng Shi, Huijuan, Xuehai Hu, Xiaohui Niu, Zhi Li. Using the concept of pseudo amino acid composition to predict resistance gene against Xanthomonas oryzae pv. oryzae in rice: an approach from chaos games representation.  Journal of Theoretical Biology, 2011, 284(1), 16-23.
[19] Jingbo Xia*, Xuehai Hu, Feng Shi, Xiaohui Niu, Chengjun Zhang. Support vector machine method on predicting resistance gene against Xanthomonas oryzae pv. oryzae in rice. Expert Systems with Applications, 2010, 37(8), 5946–5950.
[20] Xiaohui Niu, Nana Li, Feng Shi, Xuehai Hu, Jingbo Xia*. Predicting protein solubility with a hybrid method by support vector machine and BP neural network. Protein & Peptide Letters, 2010, 17(12), 1466-1472.
[21] Xuehai Hu*, Baowei Wang, Jun Wu, Yueli Yu. Cantor sets determined by partial quotients of continued fractions of Laurent series. Finite Fields and Their Applications, 2008, 14, 417-437.
[22] Xuehai Hu and Jun Wu*. Continued fractions with sequences of partial quotients over the field of Laurent series. Acta Arithmetica, 2009, 136(3), 201-211.
[23] Donggang Hu and Xuehai Hu*. Arbitrarily long arithmetic progressions for continued fractions of Laurent series.  Acta Mathematica Scientia, 2013, 33 (4): 943-949.  
[24] Xuehai Hu*, Jian Xu and Bing Li. Metric theorem and Hausdorff dimension on recurrence rate of Laurent series. Bulletin of the Korean Mathematical Society, 2014, 51(1), 157-171.  
[25] Xuehai Hu* and Luming Shen.  A note on Continued fractions with sequences of partial quotients of Laurent series. Bulletin of the Korean Mathematical Society, 2012, 49, 875-883.


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