李雪玲，中国科学院合肥智能机械研究所，副研究员。1995/09-1999/07, 烟台师范大学（鲁东大学），本科。1999/09 —2002/06，华东师范大学生命科学学院，硕士；2002/07 —2004/06，在合肥工业大学，生物与食品工程学院，助教；2004/07 —2007/06，中国科学院上海微系统与信息技术研究所，博士；2005/03 —2007/04，香港城市大学，深圳药用芯片重点实验室，研究助理；2007/07 —2010/02，中国科学院合肥智能机械研究所，助理研究员；2010/03 —至今，中国科学院合肥智能机械研究所，副研究员；2011/03 —2014/02，美国University of Texas Medical Branch，博士后。发表SCI/EI文章20多篇，并为多个国际期刊审稿人。

发表文章：

[1]    XuelingLi, Min Zhu, Xiao-Lai Li, Hongqiang Wang, Shulin Wang, “Protein-protein bindingaffinity prediction based on an SVR Ensemble, Lecture Notes in ComputerScience”, vol. 7389, pp. 145–151, 2012 (EI index).

[2]    XuelingLi, Min Zhu, Xiao-Lai Li, Hongqiang Wang, Shulin Wang, “Protein-protein bindingaffinity prediction based on interface properties and machine learning”,Lecture Notes in  ArtificialIntelligence, vol. 7390, pp. 205–212, 2012 (EI index).

[3]    Xue-LingLi, Shu-Lin. Wang, Mei-Ling Hou, “Specificity of transporter associated withantigen processing protein as revealed by feature selection method, ” Protein andPeptide Letters, vol. 17, pp.1129-1135, 2010 (SCI).

[4]    Xue-LingLi, Shu-Lin Wang, “A Comparative Study on Feature Selection in Regression forPredicting the Affinity of TAP Binding Peptides,” Lecture Notes in ArtificialIntelligence, vol. 6216, pp. 69-75, 2010 (EI)

[5]    Xue-LingLi, Mei-Ling Hou, Shu-Lin Wang, “A Residual Level Potential of Mean Force BasedApproach to Predict Protein-Protein Interaction Affinity,” Lecture Notes inComputer Science, vol. 6215, pp. 680-686, 2010 (EI)

[6]    Shu-LinWang, Xueling Li, Shanwen Zhang, Jie Gui, and Deshuang Huang, "TumorClassification by Combining PNN Classifier Ensemble with Neighborhood Rough SetBased Gene Reduction," Computer in biology and medicine, vol.40, no.2,pp.179-189, 2010 (SCI, EI).

[7]    Shu-LinWang, Xue-Ling Li, Jun-Feng Xia, Xiao-Ping Zhang, “Weighted NeighborhoodClassifier for the Classification of Imbalanced Tumor Dataset,” Journal ofCircuits Systems and Computers, vol.19, pp.259-273, 2010 (SCI, EI)

[8]    Mei-LingHou, Shu-Lin.Wang, Xue-Ling Li, Ying-Ke Lei, “Neighborhood Rough SetReduction-Based Gene Selection and Prioritization for Gene Expression ProfileAnalysis and Molecular Cancer Classification,” Journal of Biomedicine andBiotechnology, Article ID 726413, 2010.

[9]    Shu-LinWang, Jie Gui, Xue-Ling Li, “Factor Analysis for Cross-Platform TumorClassification Based on Gene Expression Profiles,” Journal of Circuits Systemsand Computers, vol.19, pp.243-258, 2010 (SCI, EI)

[10]  Ming-GuangShi, Jun-Feng Xia, Xue-Ling Li and D.S.Huang, ”Predicting protein-proteininteractions from sequence using correlation coefficient and high-qualityinteraction dataset,” Amino Acids, vol. 38, no.3, pp.891-899, 2010 (SCI, EI)

[11]  Jun-FengXia, Min Wu, Zhu-Hong You, Xing-Ming Zhao, Xue-Ling Li, “Prediction of beta-hairpinsin proteins using physicochemical properties and structure information,”Protein and Peptides letters, vol.7, pp.1123-1128, 2010 (SCI)

[12]  Shu-LinWang, Zhu-Hong You, Ying-Ke Lei, Xue-Ling Li, “Performance comparison of tumorclassification based on linear and non-linear dimensionality reductionmethods,” Lecture Notes in Computer Science, vol. 6215, pp.291-300, 2010 (EI)

[13]  Ming-GuangShi, Min Wu, De-Shuang Huang, Xue-Ling Li, “Inferring Protein Interactions fromSequence using Support Vector Machine,” The 2009 International Joint Conferenceon Neural Networks, IJCNN 2009, Atlanta, Georgia, USA, 14-19 June 2009,pp.2903-2907 (EI).

[14]  Shu-LinWang, Xue-Ling Li, Shan-Wen Zhang, “Neighborhood Rough Set Model Based GeneSelection for Multi-subtype Tumor Classification,” In Huang, D.-S. (ed),Advanced Intelligent Computing Theories and Applications. With Aspects ofTheoretical and Methodological Issues. Springer Berlin / Heidelberg,pp.146-158, 2008 (EI).

[15]  Kun-HongLiu, Jun-Feng Xia, Xue-Ling Li, Efficient ensemble schemes for proteinsecondary structure prediction, Protein and Peptide Letters, vol.15,pp.488-493, 2008 (EI).

[16]  Ming-GuangShi, De-Shuang Huang, Xue-Ling Li, “A protein interaction network analysis foryeast integral membrane protein,” Protein and Peptide Letters, vol. 15, no. 7,pp. 692-699, 2008 (SCI).

[17]  PengChen, Kyungsook Han, Xueling Li, and D.S.Huang, ”Predicting key long-rangeinteraction sites by B-factors,” Protein and Peptide Letters, vol. 15, no. 5,pp.478-483, 2008 (SCI).

[18]  PengChen, D.S.Huang, Xing-Ming Zhao, and Xueling Li, ”Predicting contact map usingradial basis function neural network with conformational energy function,”International Journal of Bioinformatics Research and Applications, vol. 4, no.2,pp.123-136, 2008.

[19]  Shan-WenZhang, Shu-Lin Wang, Xue-Ling Li, Palmprint Linear Feature Extraction andIdentification Based on Ridgelet Transforms and Rough Sets. Lecture Notes inArtificial Intelligence, vol. 5227, pp. 1101–1108, 2008 (EI).

[20]  XuelingLi, Chi-chun Fong, Minghui Huang, Huimin Cao, Jianlong Zhao, Mengsu Yang,“Measurement of binding kinetics between PI3-K and phosphorylated IGF-1R bysurface plasmon resonance biosensor,” Microchimica Acta, vol. 162, pp. 253-260,2008 (SCI)

[21]  XuelingLi, Chi-chun Fong, Minghui Huang, Huimin Cao, Yao Chen, Jianlong Zhao, MengsuYang, “Phosphorylation of Receptor-mimic Tyrosine Peptide on Surface PlasmonResonance Sensor Chip Surface and Its Interaction with Downstream Proteins,”Chinese Journal of Analytical Chemistry, vol. 36, pp. 1327-1332, 2008 (SCI)

[22]  XuelingLi, Minghui Huang, Huimin Cao, Jianlong Zhao, Mengsu Yang, “Effects of lowweight molecular effectors on the binding between membrane receptor IGF-1R andits substrate IRS-1 studied by SPR biosensor,” Sensors and Actuators B:Chemical, 2007, vol.124, no.1, pp.227–236(SCI, EI)

本人主持及参加项目:

1    项目主持（本人为项目负责人）：

（1）国家自然科学基金面上项目，“基于概率模型的调节因子-转录因子-靶基因的三元调控通路建模”，项目编号31271412，经费15万，2013.1-2013.12。

（2）安徽省自然科学基金面上项目：基于机器学习的蛋白质相互作用亲和力预测方法研究，项目编号1208085MF96，经费5万，2012.05-2014.04。

（3）中科院合肥物质科学研究院院长基金火花项目：蛋白质相互作用亲和力预测研究，项目编号0823A16121，经费11万，2008.11-2010.12（中期考核优秀，结题良好）；

2    项目参与（本人为项目主要成员）：

（1）国家自然科学基金重点项目：基于机器学习的蛋白质相互作用及功能预测方法研究，项目编号61133010，负责人黄德双，经费280万，2012.01-2016.12。

（2）国家自然科学基金青年基金：基于隐马尔科夫模型的癌症关联基因调控通道建模研究，项目编号30900321，负责人王红强，经费21万，2010.1-2012.12。（已结题，优秀）