王顺芳

教授

  • 教授,博士生导师。
  • 联系方式:sfwang_66@ynu.edu.cn;1940219519@qq.com
  • 地址:信息学院1515室

个人简介

云南大学信息学院教授、理学博士、计算机科学与技术专业博士生导师。2009年破格聘为云南大学教授、2015年聘为博士生导师。云南省中青年学术和技术带头人、美国Texas A&M 大学访问学者。

中国计算机学会高级会员、中国计算机学会生物信息学专委会执行委员、中国人工智能学会不确定性人工智能专委委员、中国人工智能学会生信与人工生命专委委员、中国生物工程学会计算与生信专委会委员、中国现场统计研究会统计交叉科学研究分会常务理事。

担任Briefings in Bioinformatics、IEEE/ACM Transactions on Computational Biology and Bioinformatics、ACM Transactions on Knowledge Discovery from Data、PLOS Computational Biology、BMC Genomics、Journal of Medicinal Chemistry等十多个国际权威期刊审稿人。

承担省部级纵向科研项目20余项,其中先后主持 5 项国家自然科学基金项目。在IEEE/ACM Transactions on Computational Biology and Bioinformatics、BMC Bioinformatics、BMC Genomics、 Computers in Biology and Medicine、 Computational Statistics & Data Analysis、Biomedical Signal Processing and Control、 BIBM等国际权威期刊和会议上以第一作者或者通讯作者发表 SCI/EI 收录学术论文 100 余篇,授权发明专利 6 项。

曾获得红云园丁奖、伍达观优秀教师奖。2022年排名第一获得云南省自然科学奖三等奖(项目名称:“生物信息预测中的数据降维方法研究”)。

研究方向:复杂高维数据分析、机器学习、计算生物信息、生物医学图像分析等。


主持的部分科研项目

1、 国家自然科学基金项目,高维稀疏蛋白质数据的特征整合和分类预测,(62062067,2021/01-2024/12

2、    国家自然科学基金项目,临床数据交叉设计下的复杂等效性评价及统计推断,(11661081,2017/01-2020/12

3、    国家自然科学基金项目:生物特征识别中高维数据的统计降维及算法研究,(11261068,2013/01-2016/12)

4、    国家自然科学基金项目:治疗方案评价中的统计推断和算法研究(10901135,2010/01-2012/12)

5、    国家自然科学基金项目:2×2 表中基于风险差和风险比的统计推断,(10626048,2007/01-2007/12)。

6、    云南省应用基础研究重点项目:蛋白质分类预测中的数据降维算法研究,(2017FA032,2017/06-2020/5)



指导研究生、合作研究

1、招收博士后:

http://www.rsc.ynu.edu.cn/info/1006/3237.htm

http://www.ise.ynu.edu.cn/annunciations/190

2、招收博士生(三种方式:申请考核制、硕博连读、直博)


3、招生(硕士生、博士生)方向:

(1)机器学习方法研究、智能计算方法研究

(2)基于机器学习和深度学习的生物医学数据分析

  1. 基于深度学习的医学图像处理和多模态影像融合分析

  2. 基于机器学习的生物多组学数据分析

  3. 基于注意力机制的生物序列数据分析

  4. 基于图卷积神经网络的蛋白质空间结构预测

  5. 基于网络表示学习和拓扑结构的复杂生物系统分析 

(3)复杂高维数据降维和分类预测


  研究方案举例:通过挖掘常用生物医学数据库:NCBIGEOTCGAGenbankSWISS-PROTPDBKEGG等,获得多组学数据并进行数据分析和推断、机器学习和智能算法创新,得到基因、药物、疾病关联的分析结论并推荐。

  

4、对研究生的要求:编程和算法、英语读写、数学

(优秀硕士生在二年级或三年级可申请转为本人所带硕博连读生)


5、部分已毕业研究生获奖

(1)云南省优秀硕士学位论文:曹子成(2020)、聂冰(2019)、雷振风(2019)、刘树慧(2018)

(2)雷振风:云南大学学业奖学金一等奖、国家奖学金、第六届研究生东陆英才奖学金、云南大学优秀毕业生

(3)郭磊:云南大学学业奖学金二等奖、国家奖学金


6、研究生主持科研项目:

(1)李兆锋:2020云南大学生科研创新项目(院内资助)“基于卷积神经网络的DNA修饰预测”

(2)马娟:2017云南大学生科研创新项目“三阶段交叉设计临床试验的等效性检验”

(3)阮小利:2016云南大学生科研创新项目(院内资助)“基于核熵复合核函数的低分辨率多结构化人脸特征的提取与表达”

(4)郭磊:2017云南大学生科研创新项目(院内资助)“蛋白质组学数据中不平衡问题的新型机器学习研究”


7、在读研究生

(1)在读博士生:邵昊、赵澈、余丽、郑伟华、张翔

(2)在读硕士生:杨鑫、叶峻华、唐贤俊、董诗琪、张蝶、李兆锋、周楠、何雨、杨子航、赵常、董浩然、王颖韬、封凡、王国凯、罗龙飞、谭卓昆、余子民、李怀虎


8、已毕业研究生:60余人


带领研究生团队参加学术会议

1、参加2019中国计算机学会生物信息学会议(CBC2019、广州、CCF生物信息学专委会&华南理工大学)

2、参加2018智能计算与生物医学大数据学术会议(上海、同济大学)

3、参加2018GIW国际学术会议

主讲课程

研究生:工程数学

本科:概率论与数理统计、高等数学、线性代数、数值计算、数学实验、工程数学



部分 SCI 收录学术论文

1.       Weihua Zheng, Wenwen Min and Shunfang Wang. TsImpute: An accurate two-step imputation method for single-cell RNA-seq data. Bioinformatics, 2023, 39(12)1-8.

2.       Che Zhao, Shunfang Wang*. AttCON: With better MSAs and attention mechanism for accurate protein contact map prediction. Computers in Biology and Medicine, 169 (2024) 107822.

3.       Zimin Yu, Li Yu, Weihua Zheng, Shunfang Wang*. EIU-Net: Enhanced feature extraction and improved skip connections in U-Net for skin lesion segmentation. Computers in Biology and Medicine, 162(2023), 107081.

4.       Chang Zhao, Wenbing Lv, Xiang Zhang, Zimin Yu, Shunfang Wang*. MMS-Net: Multi-level multi-scale feature extraction network for medical image segmentation. Biomedical Signal Processing and Control 86 (2023) 105330.

5.       Huaihu Li, Shunfang Wang, Weihua Zheng, Li Yu. Multi-dimensional search for drug–target interaction prediction by preserving the consistency of attention distribution. Computational Biology and Chemistry 107 (2023) 107968.

6.       Xianjun Tang, Longfei Luo, Shunfang Wang. TSE-ARF: An adaptive prediction method of effectors across secretion system types. Analytical Biochemistry, 686 (2024), 115407.

7.    Shunfang Wang*, Zicheng Cao, Mingyuan Li, Yaoting Yue . "G-DipC: An Improved Feature Representation Method for Short Sequences to Predict the Type of Cargo in Cell-Penetrating Peptides," IEEE/ACM Transactions on Computational Biology and Bioinformatics, 202017(3):739-747.

8.    Yu He , Shunfang Wang *. SE-BLTCNN: A channel attention adapted deep learning model based on PSSM for membrane protein classification. Computational Biology and Chemistry 98 (2022) 107680.

9.    Die Zhang, Shunfang Wang*. A protein succinylation sites prediction method based on the hybrid architecture of LSTM network and CNN[J]. Journal of Bioinformatics and Computational Biology, 20(2):2250003,2022.

10. Shunfang Wang*, Lin Deng, Xinnan Xia, Zicheng Cao and Yu Fei. Predicting antifreeze proteins with weighted generalized dipeptide composition and multi‑regression feature selection ensemble. BMC Bioinformatics(2021) 22:340.

11. Huan Yang, Shunfang Wang*.iEnhancer -RD Identification of enhancers and their  strength using RKPK features and deep neural networks. Analytical Biochemistry. 2021630114318.

12. Xu Wang, Shunfang Wang*, Haoyi Fu, Xiaoli Ruan and Xianjun TangDeepFusion-RBP: Using Deep Learning to Fuse Multiple Features to Identify RNA-binding Protein Sequences. Current Bioinformatics, 2021, 16, 1089-1100.

13. Juan Ma, Shunfang Wang*. Confidence intervals for the common odds ratio based on the inverse sinh transformation, Journal of Biopharmaceutical Statistics,20212021, 315):583–602.

14. Shiqi Dong, Shunfang Wang*. Assembled graph neural network using graph transformer with edges for protein model quality assessment. Journal of Molecular Graphics and Modelling, 110 (2021),108053.

15. Junhua Ye, Shunfang Wang*, Xin Yang and Xianjun Tang. Gene prediction of aging-related diseases based on DNN and Mashup. BMC Bioinformatics 22, 597 (2021).

16. Shunfang Wang*, Yuan Fang, Xu Wang. Multi-feature fusion and dimensional reduction based on the two-step deep ontology and the conjoint triad for the identification of cancerlectins. 2020 IEEE International Conference on Bioinformatics and Biomedicine (BIBMCCF B) 978-1-7281-6215-7/20/, pp1687-1692.

17.  Haoyi Fu, Zicheng Cao, Mingyuan Li and Shunfang Wang*. ACEP: improving antimicrobial peptides recognition through automatic feature fusion and amino acid embedding. BMC Genomics 21,597 (2020).

18. Shunfang Wang & Xiaoheng WangPrediction of protein structural classes by different feature  expressions based on 2-D wavelet denoising and fusion. BMC Bioinformatics 20, 701 (2019) doi:10.1186/s12859-019-3276-5. Published 24 December 2019.

19. Shunfang Wang, Mingyuan Li, Lei Guo, Zicheng Cao, Yu Fei. Efficient utilization on PSSM combining with recurrent neural network for membrane protein types prediction. Computational Biology and Chemistry 81 (2019) 9–15.

20.  Lei Guo, Shunfang Wang(*), Mingyuan Li & Zicheng Cao. Accurate classification of membrane protein types based on sequence and evolutionary information using deep learning. BMC Bioinformatics 20, 700 (2019).

21. Fang Yuan, Gan Liu, Xiwen Yang, Shunfang Wang(*), Xueren Wang. Prediction of Oxidoreductase Subfamily Classes Based on RFE-SND-CC-PSSM and Machine Learning Methods. Journal of Bioinformatics and Computational Biology.

22. Shunfang Wang(*), Wenjia Li, Yu Fei, Zicheng Cao, Dongshu Xu, Huanyu Guo. An improved process for generating uniform PSSMs and its application in protein subcellular localization via various global dimension reduction  techniques. IEEE ACCESS, 2019,7:42384-42395.

23. Shunfang Wang(*), Yaoting Yue. Protein subnuclear localization based on a new effective  representation and intelligent kernel linear discriminant analysis by  dichotomous greedy genetic algorithm. PLoS ONE 13(4): e0195636, 2018.

24. LEI GUO, SHUNFANG WANG(*),  ZHENFENG LEI, XUEREN WANG. Prediction for Membrane Protein Types Based  on Effective Fusion Representation and MIC-GA Feature Selection. IEEE  ACCESS, 2018,6(1):75669-75681.

25. Shunfang Wang(*), Bing Nie, Kun Yue, Yu Fei, Wenjia Li, Dongshu Xu. Protein  Subcellular Localization with Gaussian Kernel Discriminant Analysis and  Its Kernel Parameter Selection. International Journal of Molecular Sciences, 2017, 182718):1-16.

26. Shunfang Wang(*), Shuhui Liu. Protein Sub-Nuclear Localization Based on  Effective Fusion Representations and Dimension Reduction Algorithm LDA. International Journal of Molecular Sciences, 2015, 16, 30343–30361.

27.  Shunfang Wang(*)Ping  Liu A New Feature Extraction Method Based on the Information Fusion of  Entropy Matrix and Covariance Matrix and Its Application in Face  Recognition. Entropy, 17, pp 4664-4683, 2015/7.

28. Shun-Fang Wang(*)Xue-Ren WangStatistical inference of risk ratio in a correlated 2 × 2 table with structural zeroComputational Statistics2013284):1599-1615.

29. Shun-Fang Wang(*)Xue-Ren WangStratified studies about risk ratios in 2 × 2 tables with structural zeroStatistica Neerlandica2012662):183-202.

30. R. Fan(*)M.  ZhongS. WangY. ZhangA. AndrewM. KaragasH. ChenC.I. AmosM.  XiongJ.H.MooreEntropy-Based Information Gain Approaches to Detect and  to Characterize Gene-Gene and Gene-Environment Interactions/Correlations  of Complex DiseasesGenetic Epidemiology2011357):706-721.

31. TIAN  XIA, FANCHAO KONG, SHUNFANG WANG*, AND XUEREN WANG. Asymptotic  Properties of the Maximum Quasi-Likelihood Estimator in Quasi-Likelihood Nonlinear Models. Communications in Statistics—Theory and Methods, 37:  2358–2368, 2008.

32. NS TangML TangSF Wang. Sample size determination for matched-pair equivalence trials  using rate ratio. Biostatistics, 2007 , 8 (3) :625-631.

33. TIAN XIA, SHUN-FANG WANG, XUE-REN WANG. Convergence Rate of Strong Consistency of the Maximum  Likelihood Estimator in Exponential Family Nonlinear Models.  Communications in Statistics—Theory and Methods, 36: 103–115, 2007.

34. SHUN-FANG WANG, XUE-REN WANG. Homogeneity Test of Risk Differences of Marginal and  Conditional Probabilities in Several Incomplete Correlated 2 × 2 Tables.  Communications in Statistics—Theory and Methods, 36: 2877–2890, 2007.

35. Shun-Fang Wang, Nian-Sheng Tang,  Xue-Ren Wang. Analysis of the risk difference of marginal and  conditional probabilities in an incomplete correlated 2×2 table. Computational Statistics & Data Analysis 50 (2006) 1597 – 1614.

36. Tian XiaShun-fang  Wang(*)Xue-ren WangConsistency and Asymptotic Normality of the  Maximum Quasi-likelihood Estimator in Quasi-likelihood Nonlinear Models  with Random RegressorsActa Mathematicae Applicatae Sinica-English  Series2010262):241-250.

37. Shun-Fang  Wang, Nian-Sheng Tang*, Bo Zhang, and Xue-Ren Wang Statistical  inference of risk difference in K correlated 2*2 tables with structural  zero. PHARMACEUTICAL STATISTICS 2009; 8: 317–332.



发明专利

1、王顺芳,邓琳,房园,郭磊,曹子成.一种从生物医学文本中挖掘蛋白质亚细胞定位信息的方法. 2021.08授权.中国,ZL201810436260.1

2、曹子成,王顺芳,李维华,阮小利.一种基于三阶段组合推荐技术的党建视频推送方法;2021.05授权,中国,ZL201711266644.5

3、李维华;郭延哺;金宸;姬晨;邓春云;王顺芳;一种基于贝叶斯网的短文本特征扩展方法, 2020.10授权,中国,ZL201710815644.X.

4、郭延哺;金宸;姬晨;邓春云;李维华;王顺芳;一种融合文本语气的中文文本特征提取方法,2020.10授权,中国,ZL201710752000.0.

5、李维华;王兵益;郭延哺;王顺芳;何敏;一种定量分析党建数据的建模方法,2020.09授权,中国,ZL201710751678.7.

6、李维华;王顺芳;一种影响图的期望效用的并行计算方法, 2018.03授权,中国, ZL201510568841.7