董启文

数据科学应用技术；信息系统开发；在线教育；网络信息学；生物信息学

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

• Jing Xiaoyang,Dong Qiwen. MQAPRank: improved global protein model quality assessment 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 B., Wang S.Y., Dong Q.W., Li S.M.and Liu X. Identification of DNA-Binding Proteins by Combining Auto-CrossCovariance Transformation and Ensemble Learning. Ieee Transactions on Nanobioscience, 2016, 15(4): 328-334.

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

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

• HuX., Wang K. and Dong Q. Protein ligand-specific binding residue predictions byan ensemble classifier. BMCBioinformatics, 2016, 17(1): 470.

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

• DongQ., Wang K., Liu B. and Liu X. Characterization and Prediction of ProteinFlexibility Based on Structural Alphabets.BioMed Research International, 2016, 2016: 4628025.

• HuX., Dong Q., Yang J. and Zhang Y. Recognizing metal and acid radicalion-binding sites by integrating ab initio modeling with template-basedtransferals. Bioinformatics, 2016,32(21): 3260-3269.

• Qiwen Dong, Rajasree, Menon, Gilbert, Omenn, Yang Zhang, A Structural Bioinformatics Inspection ofneXtProt PE5 Proteins in the Human Proteome. J Proteome Res, 2015, 14, (9),pp. 3750-3761.

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

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

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

• BinLiu, Deyuan Zhang, Ruifeng Xu, Jinghao Xu, Xiaolong Wang, Qingcai Chen, QiwenDong, and Kuo-Chen Chou, Combiningevolutionary information extracted from frequency profiles with sequence-basedkernels for protein remote homology detection. Bioinformatics, 2014. 30(4): p. 472-479.

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

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

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

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

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

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

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

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