董启文
联系电话：62224960
电子邮箱：qwdong@dase.ecnu.edu.cn
办公地点：数学馆东114室
通讯地址：

  • 详细信息

  • 学术研究

职称

教授，博士生导师。

 

个人经历

2008年毕业于哈尔滨工业大学获计算机应用技术专业工学博士学位，并进入复旦大学计算机科学技术学院从事博士后研究工作。

2010年出站后留校任教，期间于2014年在美国密歇根大学进行访学。

2016年起任职于华东师范大学。

 

社会兼职

担任中国计算机学会生物信息学专委会委员。

曾作为Plos one, BMC Bioinformatics等刊物的特约审稿人、IJCBS程序委员会委员、IDT会议分会主席。

 

研究兴趣

研究兴趣为数据科学应用技术，包括智慧教育、网络信息学、机器学习、计算广告、生物信息学和信息系统等。


  • Jing XiaoYang,Dong Qiwen, Lu \nRruqian. RRCRank: a fusion method using rank strategy forresidue-residue\n contact prediction. BMC Bioinformatics 2017, 18(1):390.

  • Jing\n Xiaoyang,Dong Qiwen. MQAPRank: improved global protein model quality \nassessment bylearning-to-rank. BMC Bioinformatics 2017, 18(1):275.

  • 金丽娇, 傅云斌, 董启文. 基于卷积神经网络的自动问答. 华东师范大学学报(自然科学版). 2017, 195 (5):66-79.

  • 李彦斌, 潘妍虹, 顾航, 王雷, 史兵, 孙晨, 夏帆, 董启文,宋树彬. 研究生学籍系统的设计与实现. 华东师范大学学报(自然科学版). 2017, 195 (05):213-24.

  • 史兵, 夏帆, 宋树彬, 肖李敏, 董启文, 周傲英, and 徐林昊. 研究生信息平台中运维系统的设计与实现. 华东师范大学学报(自然科学版). 2017,195(05):225-35.

  • 肖垚, 毕军芳, 韩易, 董启文.在线广告中点击率预测研究. 华东师范大学学报(自然科学版),2017, 195 (05):80-6+100.

  • 郁可人, 傅云斌, 董启文. 基于神经网络语言模型的分布式词向量研究进展. 华东师范大学学报(自然科学版). 2017, 195 (05):52-65

  • Liu\n B., Wang S.Y., Dong Q.W., Li S.M.and Liu X. Identification of  \nDNA-Binding Proteins by Combining Auto-CrossCovariance Transformation  \nand Ensemble Learning. Ieee Transactions on Nanobioscience, 2016, 15(4):\n  328-334.

  • JingX., Wang K., Lu R. and Dong Q. Sorting protein decoys bymachine-learning-to-rank. Sci Rep,2016, 6: 31571.

  • JingX.\n  and Dong Q. Improved protein residue-residue contacts prediction  \nusinglearning-to-rank. in 2016 IEEE International Conference on  \nBioinformatics andBiomedicine (BIBM). 2016, Shenzhen, China116-121.

  • HuX.,\n  Wang K. and Dong Q. Protein ligand-specific binding residue \npredictions  byan ensemble classifier. BMCBioinformatics, 2016, 17(1): \n470.

  • DongQ.,  Wang K. and Liu X. Identifying the missing \nproteins in human proteome  bybiological language model. BMCSystems \nBiology, 2016, 10(4): 393-399.

  • DongQ.,  Wang K., Liu B. \nand Liu X. Characterization and Prediction of  ProteinFlexibility Based \non Structural Alphabets.BioMed Research  International, 2016, 2016: \n4628025.

  • HuX., Dong Q., Yang J. and  Zhang Y. Recognizing\n metal and acid radicalion-binding sites by  integrating ab initio \nmodeling with template-basedtransferals.  Bioinformatics, 2016,32(21): \n3260-3269.

  • Qiwen Dong, Rajasree,  Menon, Gilbert, Omenn, \nYang Zhang, A Structural Bioinformatics  Inspection ofneXtProt PE5 \nProteins in the Human Proteome. J Proteome  Res, 2015, 14, (9),pp. \n3750-3761.

  • QiwenDong, Shanyi Wang, Kai  Wang, Xuan Liu, \nand Bin Liu, Identification of DNA-binding proteins by  auto-cross \ncovariancetransformation. 2015 IEEE International Conference  on \nBioinformatics andBiomedicine (IEEE BIBM 2015) pp. 470-475

  • XiaoyangJing,\n  Qiwen Dong*, Xuan Liu, and Bin Liu, Proteinmodel quality assessment by\n  learning-to-rank. 2015 IEEE InternationalConference on Bioinformatics \n and Biomedicine (IEEE BIBM 2015) pp. 91-96

  • Qiwen Dong \nand Kai  Wang, Identifying the missing protein in humanproteome by \nstructure and  function prediction. The 9th InternationalConference on \nBioinformatics  and Biomedical Engineering (iCBBE 2015).

  • BinLiu,\n Deyuan Zhang,  Ruifeng Xu, Jinghao Xu, Xiaolong Wang, Qingcai Chen, \nQiwenDong, and  Kuo-Chen Chou, Combiningevolutionary information \nextracted from  frequency profiles with sequence-basedkernels for \nprotein remote  homology detection. Bioinformatics, 2014. 30(4): p. \n472-479.

  • BinLiu,  Xiaolong Wang, Quan Zou, Qiwen Dong, \nand Qingcai Chen, Protein Remote  Homology Detection byCombining Chou’s \nPseudo Amino Acid Composition and  Profile‐Based Protein Representation.\n molecular informatics, 2013.  32(9‐10): p.775-782.

  • BinLiu,\n Xiaolong Wang, Qingcai Chen, Qiwen  Dong, and Xun Lan, Using amino acid\n physicochemical distance  transformation for fastprotein remote \nhomology detection. Plos One,  2012. 7(9): p. e46633.

  • XinGeng,\n Jihong Guan, Qiwen Dong, and  Shuigeng Zhou, An Improved Genetic \nAlgorithm for Statistical Potential  Function Designand Protein \nStructure Prediction. Internal journal of  datamining andbioinformatics,\n 2012. 6(2): p.162-177.

  • YanfengZhang,  Bin Liu, Qiwen \nDong, and Victor X. Jin, An Improved Profile-Level  Domain Linker \nPropensity Index for ProteinDomain Boundary Prediction.  Protein and \nPeptide Letters, 2011. 18(1): p. 7-16.

  • Xuan Liu,  Lijie \nZhao, and Qiwen Dong*, Protein remote homology detection based  \nonauto-cross covariance transformation. Comput Biol Med, 2011. 41(8): p.\n  640-7.

  • Qiwen Dong and Shuigeng Zhou, Novel nonlinear  \nknowledge-based mean forcepotentials based on machine learning. IEEE/ACM\n  Trans Comput Biol Bioinform,2011. 8(2): p. 476-486.

  • Qiwen\n  Dong, Yufei Chen, and Shuigeng Zhou, A machine learning-based method \nfor  proteinglobal model quality assessment. Internal journal of general\n  system, 2011. 40(4): p. 417-425.

  • Lei Deng, Jihong Guan,\n Qiwen  Dong,and Shuigeng Zhou, SemiHS: An IterativeSemi-Supervised \nApproach for  Predicting Protein-protein Interaction Hot Spots \nProteinand Peptide  Letters, 2011. 18(9): p.896-905.