杜朴风

个人简介

杜朴风
    天津大学,智能与计算学部,计算机科学与技术学院
    副教授,硕士研究生导师;
    中国计算机学会(CCF)高级会员,生物信息学专业委员会,常务委员;
    中国人工智能学会(CAAI)会员,生物信息学与人工生命专业委员会,常务委员;
    中国自动化学会(CAA)会员,智能健康与生物信息学专业委员会,委员;
    中国生物工程学会会员,计算生物学与生物信息学专业委员会,委员;
    天津市药理学会,网络药理学专业委员会,副主任;
    ACM会员,ACM SIGBIO中国执行委员会委员。
现招收2022年秋季入学硕士研究生(含专业学位),欢迎2023年秋季入学研究生提前联系 我要咨询
长期招收优秀本科生加盟课题组参与科研项目。

联系方式

地址:天津市津南区海河教育园内雅观路135号天津大学55楼B323。
邮政编码:300354
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推荐信相关

本科生出国留学推荐信
本科生申请国内学校研究生/直博生推荐信
外国留学生申请中国政府奖学金项目International Students CGS
研究生申请工作/读博/出国推荐信

主要经历

2020年11月-今: 天津大学,智能与计算学部,学科团队负责人(12. 生物信息学)
2018年09月-今: 天津大学,智能与计算学部,副教授(独立开展科研工作)
2013年07月-2018年08月: 天津大学,计算机科学与技术学院,副教授(独立开展科研工作)
2012年12月-2014年12月: 香港城市大学,计算机系,访问博士后(香江学者)。合作导师:王鲁生
2010年01月-2013年06月: 天津大学,计算机科学与技术学院,讲师(独立开展科研工作)
2008年09月-2010年01月: 清华大学,自动化系,李衍达院士秘书
2005年09月-2010年01月: 清华大学,自动化系/清华信息科学与技术国家实验室,博士研究生,2010年1月获博士学位。导师:李衍达(无副导师)
2001年09月-2005年07月: 清华大学,自动化系,本科生,2005年7月获学士学位

研究方向

基于机器学习的生物序列分类
蛋白质亚细胞定位预测
蛋白质翻译后修饰位点预测
RNA编辑位点预测
长非编码RNA的定位预测
分子网络系统行为分析
针对特定肿瘤的药物组合和药物重用发现
复杂疾病分子系统的定位标志物的识别
高效生物序列分析软件开发
蛋白质序列特征快速抽取软件
蛋白质序列特征可视化系统

部分科研项目

国家自然科学基金,蛋白质异常定位组的计算预测(面上,2019-2022),主持;
国家自然科学基金,基于信息融合的高分辨率蛋白质定位预测(青年,2011-2013),主持;
国家重点研发计划,精准医学大数据的有效挖掘与关键信息技术开发(课题5,2018-2021),骨干;
教育部新教师基金,利用蛋白质相关性网络融合多种信息的蛋白质动态定位预测(2011-2013),主持;
天津市自然科学基金,融合多种异质信息的高分辨率动态蛋白质定位预测(青年,2012-2015),主持;
北洋学者-青年骨干教师计划,蛋白质结构与功能计算预测(2014-2015),主持;
天津大学自主创新基金,在基因本体子空间中针对特定拓扑蛋白的定位预测(2015-2016),主持。

所获荣誉

2016年天津大学青年教师讲课大赛二等奖;
2014年天津大学“北洋学者-青年骨干教师”;
2013年“香江学者”奖;
2012年全国优秀博士学位论文(提名奖);
2011年北京市优秀博士学位论文;
2010年天津大学“十佳优秀青年教工”(提名奖);
2010年清华大学“优秀研究生”;
2007年全国百篇最具影响力的国际学术论文奖。

硕士研究生

2014级:焦亚森:独立指导,考研入学,获国家奖学金,优秀毕业生,校三好学生。毕业后去向:航天二院(物联网方向)。现工作单位:字节跳动。
2016级:张鸽:合作指导,保研入学。毕业后去向:澳大利亚Macquarie大学攻读博士学位。
2016级:杨晓飞:合作指导,保研入学。毕业后去向:石家庄市数据资源管理局(公务员)。
2017级:赵伟:独立指导,保研入学。毕业后去向:光大银行(总行信息科技部)。
2018级:单虹毓:合作指导,考研入学。毕业后去向:蚂蚁金服(搜索推荐平台)。
2018级:李光平:独立指导,考研入学,获校三好学生,毕业后去向:Bigo (live 后台开发)。
2018级:孙鉴:独立指导,考研入学,获校先进个人,优秀学生干部,优秀毕业生,毕业后去向:中国华录集团北京易华录信息技术有限公司(方案工程部)。
2018级:王俊:独立指导,考研入学,毕业后去向:百度(移动生态评估中心)。
2018级:周园科:独立指导,考研入学,毕业后去向:美团(智慧交通平台)。
2019级:刘航宇:独立指导,考研入学,在读。
2019级:于涵:独立指导,考研入学,在读。
2019级:沈子昂:合作指导,考研入学,在读,离校实习,腾讯。
2019级:张文雅:合作指导,考研入学,在读,离校实习,美团。
2019级:暨巧莹:合作指导,考研入学,在读。
2019级:闵慧:独立指导,考研入学,在读。
2019级:辛晓红:独立指导,考研入学,在读。
2019级:高楚翘:独立指导,考研入学,在读。
2020级:张颖颖:独立指导,保研入学,在读。
2020级:刘思凯:合作指导,保研入学,在读。
2020级:王仁华:合作指导,保研入学,在读。
2020级:吴杨:独立指导,考研入学,在读。

课题组本科生

缪阳洋,2015级,化工学院。毕业后去向:中国科学技术大学(合肥)读研。
李皓民,2018级,智能与计算学部(腾讯班)。

本科生教学

校必修基础课
C++程序设计与算法基础(英)(2017-2020);
大学计算机基础(2011,2012,2015-2020);
计算机软件技术基础(C++版)(2015, 2016, 2020);
校选修基础课
Python程设设计及应用(英)(2018);
Visual C++程序设计(2015-2018);
院选修专业课
开源技术及应用(2011, 2012, 2015-2018);

学术服务

期刊编委
高等教育出版社:Frontiers of Computer Science (青年编委)
MDPI出版社:Data(编委)
Bentham Science:Current Bioinformatics(Editorial Board Member / Section Editor)
Bentham Science: Current Chinese Computer Science (Editorial Board Member)
Bentham Science: Current Gene Therapy (Editorial Board Member)
Frontiers: Fronteirs in Genetics (Editorial Board Member / Review Editor)
专刊编委
Current Organic Chemistry, Thematic Issue:Computational Modelling of Biological Macromolecule (2019年4月30日截稿)
MDPI-Data, Special Issue: Benchmarking datasets in Bioinformatics (2020年7月31日截稿)
论文评阅人
Briefings in Bioinformatics; Bioinformatics; BMC Bioinformatics; BMC Genomics; BMC Supplements; BMC Medical Informatics and Decision Making; IEEE/ACM Transactions on Computational Biology and Bioinformatics; Journal of the Royal Statistical Society - Serial A; IEEE Access; Journal of Proteome Research; Expert Review of Proteomics; RNA Biology; Molecular Therapy - Nucleic Acids: Journal of Biotechnology; Journal of Cellular and Molecular Medicine; Current Bioinformatics; Current Genomics; Current Proteomics; Letters in Organic Chemistry; Evolutionary Bioinformatics; Genomics; Amino Acids; Plos ONE; Scientific Reports; Oncotarget; NeuroComputing; Molecular Informatics; Molecular BioSystems; Applied Sciences; Interdisciplinary Sciences: Computational Life Sciences; BioTechnologia; International Journal of Biomathematics; Acta BioTheoratica; Artificial Intelligence in Medicine; Computational and Mathematical Methods in Medicine; Computer Methods and Programs in Biomedicine; BioMed Research International; IET Biometrics; Chemometrics and Intelligent Laboratory Systems; PeerJ; Journal of Theoretical Biology; Protein and Peptides Letters; Frontiers in Genetics; Frontiers of Computer Sciences; Genomics, Proteomics & Bioinformatics; Quantitative Biology; Progress in Biochemistry and Biophysics; MDPI - Molecules; MDPI - Data; MDPI - Information; MDPI - Genes;
会议PC
WABI2012; APCIIT2013; ICSEA2016; GIW2016; BIIP2016; CBC2016; BIBM2016(Workshop); ICIC2017; BIIP2017; CBC2017; NCCA2017; ICIC2018; ISBRA2018; BIIP2018 (Org-Chair); CBC2018; NCCA2018; SMC2018; ISB2018; ISBRA2019; ICPCSEE2019; CBC2019; BIIP2019; ICBBE 2019; ICIC2020; ISBRA2020

代表论文

完整列表请参阅 Google Scholar页面
[30]   Zi-Ang Shen, Tao Luo, Yuan-Ke Zhou, Han Yu, Pu-Feng Du*; NPI-GNN: Predicting ncRNA–protein interactions with deep graph neural networks, Briefings in Bioinformatics, 2021, DOI:10.1093/bib/bbab051. (SCI)
[29]   Wen-Ya Zhang; Junhai Xu*; Jun Wang; Yuan-Ke Zhou; Wei Chen*; Pu-Feng Du*; KNIndex: a comprehensive database of physicochemical properties for k-tuple nucleotides, Briefings in Bioinformatics, 2021, DOI:10.1093/bib/bbaa284. (SCI)
[28]   Guang-Ping Li; Pu-Feng Du*; Zi-Ang Shen; Hang-Yu Liu; Tao Luo*; DPPN-SVM: Computational Identification of Mis-Localized Proteins in Cancers by Integrating Differential Gene Expressions With Dynamic Protein-Protein Interaction Networks, Frontiers in Genetics, 2020, 11: 600454. (SCI)
[27]   Jian Sun; Pu-Feng Du*; Predicting protein subchloroplast locations: the 10th anniversary, Frontiers of Computer Science,2021, 15(2): 152901. (SCI)
[26]  Jun Wang; Pu-Feng Du*; Xin-Yu Xue; Guang-Ping Li; Yuan-Ke Zhou; Wei Zhao; Hao Lin; Wei Chen*; VisFeature: a stand-alone program for visualizing and analyzing statistical features of biological sequences, Bioinformatics, 2020, 36(4): 1277-1278. (SCI)
[25]  Yuan-Ke Zhou; Zi-Ang Shen; Han Yu; Tao Luo*; Yang Gao*; Pu-Feng Du*; Predicting lncRNA–Protein Interactions With miRNAs as Mediators in a Heterogeneous Network Model, Frontiers in Genetics, 2020, 10: 1341. (SCI)
[24]  Yang-Yang Miao; Wei Zhao; Guang-Ping Li; Yang Gao*; Pu-Feng Du*; Predicting endoplasmic reticulum resident proteins using auto-cross covariance transformation with U-shaped residue weight transfer function, Frontiers in Genetics, 2019, 10: 1231. (SCI)
[23]  Wei Zhao; Guang-Ping Li; Jun Wang; Yuan-Ke Zhou; Yang Gao*; Pu-Feng Du*; Predicting protein sub-Golgi locations by combining functional domain enrichment scores with pseudo-amino acid compositions, Journal of Theoretical Biology, 2019, 473: 38-43. (SCI)
[22]  Wei Zhao; Likun Wang; Tian-Xiang Zhang; Ze-Ning Zhao; Pu-Feng Du*; A brief review on software tools in generating Chou's pseudo-factor representations for all types of biological sequences, Protein and Peptide Letters, 2018, 25(9): 822-829. (SCI)
[21]  Pu-Feng Du; Wei Zhao; Yang-Yang Miao; Le-Yi Wei; Likun Wang*; UltraPse: a universal and extensible software platform for representing biological sequences, International Journal of Molecular Sciences, 2017, 18(11): 2400. (SCI)
[20]  Pu-Feng Du*; Predicting protein submitochondrial locations: The 10th Anniversary, Current Genomics, 2017, 18(4): 316-321. (SCI)
[19]  Ya-Sen Jiao; Pu-Feng Du*; Predicting protein submitochondrial locations by incorporating the positional-specific physicochemical properties into Chou's general pseudo-amino acid compositions, Journal of Theoretical Biology, 2017, 416: 81-87. (SCI)
[18]  Yasen Jiao; Pufeng Du*; Performance measures in evaluating machine learning based bioinformatics predictors for classifications, Quantitative Biology, 2016, 4(4): 320-330.
[17]  Ya-Sen Jiao; Pu-Feng Du*; Prediction of Golgi-resident protein types using general form of Chou's pseudo-amino acid compositions: Approaches with minimal redundancy maximal relevance feature selection, Journal of Theoretical Biology, 2016, 402: 38-44. (SCI)
[16]  Pu-Feng Du*; A brief review on software implementations and algorithm enhancements of Chou’s pseudo-amino acid compositions, Current Proteomics, 2016, 13(2): 105-112. (SCI)
[15]  Ya-Sen Jiao; Pu-Feng Du*; Predicting Golgi-resident protein types using pseudo amino acid compositions: Approaches with positional specific physicochemical properties, Journal of Theoretical Biology, 2016, 391: 35-42. (SCI)
[14]  Pufeng Du*; Lusheng Wang*; Predicting human protein subcellular locations by the ensemble of multiple predictors via protein-protein interaction network with edge clustering coefficients, PLoS ONE, 2014, 9(1): e86879. (SCI)
[13]  Pufeng Du*; Shuwang Gu; Yasen Jiao; PseAAC-General: fast building various modes of general form of Chou’s pseudo-amino acid composition for large-scale protein datasets, International Journal of Molecular Sciences, 2014, 15(3): 3495-3506. (SCI)
[12]  Pu-Feng Du; Chao Xu*; Predicting multisite protein subcellular locations: progress and challenges, Expert Review of Proteomics, 2013, 10(3): 227-237. (SCI)
[11]  Pufeng Du*; Tingting Li; Xin Wang; Chao Xu; SubChlo-GO: predicting protein subchloroplast locations with weighted gene ontology scores, Current Bioinformatics, 2013, 8(2): 193-199. (SCI)
[10]  Pufeng Du*; Yuan Yu; SubMito-PSPCP: predicting protein submitochondrial locations by hybridizing positional specific physicochemical properties with pseudoamino acid compositions, BioMed Research International, 2013, 2013: 263829. (SCI)
[9]    Pufeng Du*; Yang Tian; Yan Yan; Subcellular localization prediction for human internal and organelle membrane proteins with projected gene ontology scores, Journal of Theoretical Biology, 2012, 313: 61-67. (SCI)
[8]    Pufeng Du*; Xin Wang; Chao Xu; Yang Gao*; PseAAC-Builder: a cross-platform stand-alone program for generating various special Chou’s pseudo-amino acid compositions, Analytical Biochemistry, 2012, 425(2): 117-119. (SCI)
[7]    Pufeng Du*; Tingting Li; Xin Wang; Recent progress in predicting protein sub-subcellular locations, Expert Review of Proteomics, 2011, 8(3): 391-404. (SCI)
[6]    Pufeng Du#; Shengjiao Cao#; Yanda Li*; SubChlo: predicting protein subchloroplast locations with pseudo-amino acid composition and the evidence-theoretic K-nearest neighbor (ET-KNN) algorithm, Journal of Theoretical Biology, 2009, 261(2): 330-335. (SCI)
[5]    Pufeng Du#; Liyan Jia#; Yanda Li*; CURE-Chloroplast: a chloroplast C-to-U RNA editing predictor for seed plants, BMC Bioinformatics, 2009, 10(1): 135. (SCI)
[4]    Pufeng Du; Yanda Li*; Prediction of C-to-U RNA editing sites in plant mitochondria using both biochemical and evolutionary information, Journal of Theoretical Biology, 2008, 253(3): 579-586. (SCI)
[3]    Pufeng Du#; Tao He#; Yanda Li*; Prediction of C-to-U RNA editing sites in higher plant mitochondria using only nucleotide sequence features, Biochemical and Biophysical Research Communications, 2007, 358(1): 336-341. (SCI)
[2]    Tao He#; Pufeng Du#; Yanda Li*; dbRES: a web-oriented database for annotated RNA editing sites, Nucleic Acids Research, 2007, 35(Database Issue): D141-D144. (SCI)
[1]    Pufeng Du; Yanda Li*; Prediction of protein submitochondria locations by hybridizing pseudo-amino acid composition with various physicochemical features of segmented sequence, BMC Bioinformatics, 2006, 7(1): 518. (SCI)

*:通讯作者;#:贡献相同。