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教师信息

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徐岩

教授
  • 姓名:

    徐岩
  • 性别:

  • 职称:

    教授
  • 所在系所:

    信息与计算科学系
  • 所在梯队:

    控制理论及应用梯队
  • 办公地点:

    理化楼208
  • 办公电话:

    62332589
  • 电子邮件:

    xuyan@ustb.edu.cn
  • 本科生课程:

    机器学习与应用,线性代数,概率论与数理统计,文科数学等
  • 研究生课程:

    实用机器学习技术
  • 研究领域:

    生物信息学、深度学习、蛋白质翻译后修饰、机器学习

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 北京科技大学数学系
    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

科研业绩

    主持或参与的项目:
    1. 2019.10-2020.06 基于机器学习的****软件 某研究所 负责人
    2. 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
    3. 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
    4. 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
    5. 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
    6. 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
    7. 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
    8. 2012.01-2014.12 微分算子环上的机械化算法与应用研究 国家自然科学青年基金 参与者 项目编号:11101029

    科研文章:
    1. 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
    2. Chun-NaLi,Meng-QiShang, Yuan-HaiShao,YanXu*,Li-MingLiu,ZhenWang. Sparse L1-norm two dimensional linear discriminant analysis via the generalized elastic net regularization. Neurocomputing. 2019.April.14.Vol.337: 80-96.
    3. 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.
    4. 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.
    5. Hongli Fu, Yingxi Yang, Hui Wang, Yan Xu*. DeepUbi:adeep learning framework for prediction of ubiquitination sites in proteins. BMC Bioinformatics. 2019, Feb.18. Vol.20(1):86.
    6. Yan Xu, Yingxi Yang, Hui Wang, Yuanhai Shao*. Lysine Malonylation Identification in E.coli withMultiple Features. Current Proteomics. 2019. Feb.Vol.16(3).166-174.
    7. Meiqi Wu, Yingxi Yang, Hui Wang, Yan Xu*.A deep learning method to more accurately recall known lysine acetylation sites.BMC Bioinformatics. 2019, Jan. 23. Vol.20(1):49.
    8. 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.
    9. 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.
    10. 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.
    11. 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, July. Vol.100:144-151.
    12. 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.
    13. 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.
    14. Yan Xu, Li Li, Jun Ding, Ling-Yun Wu,Guoqin Mai*, Fengfeng Zhou*. Gly-PseAAC: identifying protein lysine glycationthrough sequences. Gene. 2017 Feb.20.602:1-7.
    15. Yan Xu, Ya-Xin Ding, Jun Ding, Ling-Yun Wu, Yu Xue*. Mal-Lys: prediction of lysine malonylationsites in proteins integrated sequence-based features with mRMR feature selection. Scientific Reports. 2016.12.02, Vol6.38318.
    16. 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.
    17. Yan Xu*, Kuo-Chen Chou. Recent progress in predicting posttranslational modification sites in proteins. Current Topics in Medicinal Chemistry. 2016.16(6),591-603.
    18. Yan Xu, Ya-Xin Ding, Nai-Yang Deng, Li-Ming Liu*. Prediction of Sumoylation Sites in Proteins Using Linear Discriminant Analysis. Gene. 2016. Jan.15576:99-104.
    19. 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.
    20. 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.
    21. 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.
    22. 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.
    23. 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.
    24. 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.
    25. 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, 8(2), e55844, 2013.Feb.
    26. 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.

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