教育经历

2008.09~2012.07 中国农业大学理学院 博士
2001.09~2003.07 吉林大学数学所 硕士
1997.09~2001.07 吉林大学数学系 本科

工作经历

2003.07-至今 必赢nn699net数学系
2016.03-2017.03 美国加州大学洛杉矶分校访问
2018.07-2019.08 美国蒙特克莱尔州立大学统计系访问
2019.07-2019.07 英国邓迪大学数学系访问

学术兼职：
中国运筹学会第十一届理事、副秘书长
中国运筹学会青年工作委员会秘书长
中国运筹学会数学规划分会副秘书
中国运筹学会计算生物学分会理事

科研业绩

1. 2021.01-2024.12蛋白质翻译后修饰的深度特征学习及预测 国家自然科学基金面上项目 负责人 项目编号: 12071024
2. 2020.08-2023.07基于大数据智能的非公经济群体感知与服务辅助技术研究与应用 科技部重大项目2030计划“新一代人工智能（2030）” 子课题负责人，项目编号：2020AAA0105100
3. 2019.10-2020.06 基于机器学习的****软件 负责人
4. 2017.01-2020.12基于多标签学习的蛋白质翻译后修饰位点预测 国家自然科学基金面上项目 负责人 项目编号: 11671032
5. 2018.01-2018.12 深度学习前言与应用 引智项目，负责人 项目编号：C2018033
6. 2017.12-2018.11多示例多标签学习在蛋白质组学中的研究与应用，基础科研业务费 负责人 项目编号： FRF-TP-17-024A2
7. 2016.01-2016.12整合成多标签学习问题的蛋白质修饰研究，基础科研业务费 负责人 项目编号: FRF-BR-15-075A
8. 2014.01-2016.12 基于机器学习的蛋白质翻译后修饰位点预测的研究 国家自然科学青年基金 负责人 项目编号:11301024
9. 2017.01-2017.12计算生物学的若干问题研究，引智项目，负责人 项目编号：C2017021

出版教材:
2014.05 《大学文科数学》(上、下册), 主编, 科学出版社

发表论文：
1. Meiqi Wu, Yingxi Yang, Hui Wang, Jun Ding, Huan Zhu, Yan Xu*. IMPMD: an integrated method for predicting potential associations between miRNAs and diseases. Current Genomics. 2019.December. Vol.20, No.8. 581-591.
2. Yuan-Hai Shao, Chun-Na Li, Ling-Wei Huang, Zhen Wang, Nai-Yang Deng, Yan Xu*. Joint sample and feature selection via sparse primal and dual LSSVM. Knowledge-Based System. 2019. December. Vol:185. 104915.
3. Chun-Na Li，Meng-Qi Shang, Yuan-Hai Shao，Yan Xu*，Li-Ming Liu，Zhen Wang. Sparse L1-norm two dimensional linear discriminant analysis via the generalized elastic net regularization. Neurocomputing. 2019.April.14.Vol.337: 80-96.
4. Yan Xu, Xingyan Li, Yingxi Yang, Chunhui Li*, Xiaojian Shao. Human age prediction based on DNA methylation of non-blood tissues. Computer Methods and Programs in Biomedicine. 2019. April. Vol.171: 11-18.
5. Yan Xu, Yingxi Yang, Zu Wang, Yuanhai Shao*. Prediction of Acetylation and Succinylation in Proteins based on Multi-label Learning RankSVM. Letters in Organic Chemistry. 2019, March. Vol. 16(4): 275-282
6. Hongli Fu, Yingxi Yang, Hui Wang, Yan Xu*. DeepUbi：a deep learning framework for prediction of ubiquitination sites in proteins. BMC Bioinformatics. 2019, Feb.18. Vol.20(1):86.
7. Yan Xu, Yingxi Yang, Hui Wang, Yuanhai Shao*. Lysine Malonylation Identification in E.coli with Multiple Features. Current Proteomics. 2019. Feb.Vol.16(3). 166-174.
8. Meiqi Wu, Yingxi Yang, Hui Wang, Yan Xu*. A deep learning method to more accurately entall known lysine acetylation sites. BMC Bioinformatics. 2019, Jan. 23. Vol.20(1):49.
9. Yan Xu, Yingxi Yang, Zu Wang, Chunhui Li, Yuanhai Shao*. A systematic review on posttranslational modification in proteins: feature construction, algorithm and webserver. Protein and Peptide Letters. 2018, Dec. Vol. 25(9): 807-814.
10. Yan Xu, Yingxi Yang, Jun Ding, Chunhui Li*. iGlu-Lys: A Predictor for Lysine Glutarylation through Amino Acid Pair Order Features. IEEE Transactions on NanoBioscience. 2018, Oct. Vol.17(4):394-401.
11. Xingyan Li，Weidong Li, Yan Xu*. Human Age Prediction Based on DNA Methylation Using a Gradient Boosting Regressor. Genes, 2018, (August. 21) Vol. 9. 424.
12. Yingxi Yang, Hui Wang, Jun Ding, Yan Xu*. iAcet-Sumo: identification of lysine acetylation and sumoylation sites in proteins by multi-class transformation methods. Computers in Biology and Medicine. 2018, Sep.1 Vol.100:144-151.
13. Yan Xu, Zu Wang, Chunhui Li*, Kuo-Chen Chou. iPreny-PseAAC: Identify C-terminal Cysteine Prenylation Sites in Proteins by Incorporating Two Tiers of Sequence Couplings into PseAAC. Medicinal Chemistry. 2017, May.Vol.13(6), 544-551.
14. Li-Ming Liu, Yan Xu*, Kuo-Chen Chou. iPGK-PseAAC: identify lysine phosphoglycerylation sites in proteins by incorporating four different tiers of amino acid pairwise coupling information into the general PseAAC. Medicinal Chemistry. 2017, May.Vol 13(6), 552-559.
15. Yan Xu, Li Li, Jun Ding, Ling-Yun Wu, Guoqin Mai*, Fengfeng Zhou*. Gly-PseAAC: identifying protein lysine glycation through sequences. Gene. 2017 Feb.20.602:1-7.
16. Yan Xu, Ya-Xin Ding, Jun Ding, Ling-Yun Wu, Yu Xue*. Mal-Lys: prediction of lysine malonylation sites in proteins integrated sequence-based features with mRMR feature selection. Scientific Reports. 2016.12.02, Vol6.38318.
17. Yan Xu*, Jun Ding, Ling-Yun Wu. iSulf-Cys: prediction of S-sulfenylation sites in proteins with physicochemical properties of amino acids. PloS One. 2016.11(4): e0154237. 2016. April.
18. Yan Xu*, Kuo-Chen Chou. Recent progress in predicting posttranslational modification sites in proteins. Current Topics in Medicinal Chemistry. 2016.16(6), 591-603.
19. Yan Xu, Ya-Xin Ding, Nai-Yang Deng, Li-Ming Liu*. Prediction of Sumoylation Sites in Proteins Using Linear Discriminant Analysis. Gene. 2016. Jan.15 576:99-104.
20. Yan Xu*, Ya-Xin Ding, Jun Ding, Ling-Yun Wu, Nai-Yang Deng. Phogly-PseAAC: prediction of lysine phosphoglycerylation in proteins incorporating with position-specific propensity. Journal of Theoretical Biology. 2015.08.21, (379)10-15.
21. Yan Xu*, Ya-Xin Ding, Jun Ding, Ya-Hui Lei, Nai-Yang Deng. iSuc-PseAAC: predicting lysine succinylation in proteins by incorporating peptide position-specific propensity. Scientific Reports. 2015.06.18 .Vol5.10184.
22. Yan Xu*, Xin Wen, Li-Shu Wen, Ling-Yun Wu, Nai-Yang Deng, Kuo-Chen Chou. iNitro-Tyr: Prediction of nitrotyrosine sites in proteins with general pseudo amino acid composition. PLoS ONE 9(8), e105018.
23. Yan Xu*, Xin Wen, Xiao-Jian Shao, Nai-Yang Deng, Kuo-Chen Chou. iHyd-PseAAC: predicting hydroxyproline and hydroxylysine in proteins by incorporating dipeptide position-specific propensity into pseudo amino acid composition. International Journal of Molecular Sciences. 2014, May, 5. 15:7594-7610.
24. Yan Xu*, Xiao-Bo Wang, Yong-Cui Wang, Ying-Jie Tian, Xiao-Jian Shao, Ling-Yun Wu, Nai-Yang Deng. Prediction of Posttranslational Modification Sites from Sequences with Kernel Methods. Journal of Theoretical Biology. 2014. March 7. 7:344, 78-87.
25. Yan Xu*, Xiao-Jian Shao, Ling-Yun Wu, Nai-Yang Deng, Kuo-Chen Chou. iSNO-AAPair: incorporating amino acid pairwise coupling into PseAAC for predicting cysteine S-nitrosylation sites in proteins. PeerJ. 2013 Oct 3. 1:e171.
26. Yan Xu*, Jun Ding, Ling-Yun Wu, Kuo-Chen Chou. iSNO-PseAAC: Predict Cysteine S-nitrosylation Sites in Proteins by Incorporating Position Specific Amino Acid Propensity into Pseudo Amino Acid Composition, PLoS One, 2013.Feb. 8(2), e55844.
27. Yan Xu*, Jun Ding, Qiang Huang, Nai-Yang Deng. Prediction of Protein Methylation Sites using Conditional Random Field. Protein and Peptide Letters, 2013, 20(1), 71-77.