个人概况：
beat365院长，博士，计算机科学与技术系全职讲席教授、博士生导师，“建筑大数据智能处理方法研究”北京市重点实验室主任；省杰出青年科学基金获得者、宝钢优秀教师奖获得者，曾留学瑞典、英国。主要研究领域：机器学习与人工智能、智能建造与智慧城市、生物信息学等。1997年博士毕业于哈尔滨工业大学计算机应用专业，2002年破格评为教授，2003 年评为“计算机科学与技术”、“软件工程”、“生物医学工程”学科博导，目前为北京建筑大学“智能建造与智慧城市”方向博士生导师。任中国计算机学会生物信息学专委会副主任、中国人工智能学会机器学习专委会常委、中国建筑学会计算性设计学术委员会常委、中华医学会医学信息学分会医学大数据与人工智能学组委员，国家自然基金委重大研究计划指导专家组成员。曾任第十二届、十三届基金委信息学部评审组专家、国家科学技术奖会评专家、中国机器学习会议大会主席。是国家自然科学基金重点项目、国家重点研发任务负责人，曾获教育部自然科学奖、省自然科学奖（均排名第1），发表论文200余篇。已指导毕业博士21人、硕士80余人。

教育经历：
1984 -1988：哈尔滨工程大学计算机应用专业，获学士学位
1988 -1991：哈尔滨工程大学计算机软件学科，获硕士学位
1994 -1997：哈尔滨工业大学计算机应用学科，获博士学位
2000 -2002：哈尔滨工业大学管理科学与工程学科，博士后

留学经历:
2002 -2003：瑞典，隆德（Lund）大学计算机科学系，国家公派访问学者
2010.8 -10：英国，利兹（Leeds）大学分子与细胞生物研究所，国家公派高级研究学者

工作经历：
1998 -2002：哈尔滨工业大学计算机科学与技术学院，副教授
2002 -2016：哈尔滨工业大学计算机科学与技术学院，教授（破格）
2003 -2016：哈尔滨工业大学“计算机科学与技术”、“软件工程”、“生物医学工程”学科，博导
2016-目前：beat365，院长；教授、博导

社会兼职：
（1）中国计算机学会生物信息学专委会副主任、中国人工智能学会机器学习专委会常委、中国建筑学会计算性设计学术委员会常委、中华医学会医学信息学分会医学大数据与人工智能学组委员
（2）中国机器学习会议大会主席；《软件学报》“大数据时代的机器学习研究”专刊，特约编委；《哈尔滨工业大学学报》、《计算机科学与探索》、《智能系统学报》、《光学精密工程》期刊编委
（3）国家自然科学基金委员会重大研究计划指导专家组成员；国家自然科学基金委员会信息科学部第十二、十三届专家评审组成员
（4）北京建筑大学学位委员会委员、学术委员会委员；控制科学与工程学科学位委员会主任

荣誉称号：
（1）省杰出青年科学基金获得者（2006年）
（2）教育部宝钢优秀教师奖获得者（2015年）
（3）教育部自然科学奖获得者（2019年）

研究方向:
（1）机器学习与人工智能
（2）智能建造与智慧城市、建筑导则计算性设计
（3）生物信息学

科研项目:
（1）个体-群体时空活动轨迹挖掘方法研究，国家自然科学基金面上项目，2019-2022
（2）大豆RNA结构与进化分析的信息处理方法研究，国家自然基金重点项目，2010-2013
（3）基于网络模型的癌症相关模式挖掘理论与方法，国家自然基金重点项目，2016-2020
（4）miRNA-基因双层网络的构建与分析方法研究，国家自然科学基金面上项目，2016-2019
（5）功能基因网络的重构与交叠模块识别方法，国家自然科学基金面上项目，2013-2016
（6）系统发生树构建方法研究，国家自然科学基金面上项目，2008-2009
（7）蛋白质相互作用和基因功能关联pairwise核对称性预测方法研究，教育部博士点基金，2012-2014
（8）精准医学文本知识发现与呈现，国家重点研发计划，2016-2020
（9）基于认知学习模型和半监督学习机制的图像语义理解研究，原国家“863”计划，2007-2009
（10）基于智能推理技术的信息处理平台，原国家“863”计划，2004-2005
（11）面向智慧城市中时空大数据的机器学习方法研究，北京市属高校高水平创新团队建设计划项目，2019-2021
（12）智慧城市中的时空数据深度学习研究，北京市教委科技计划重点项目，2018-2020
（13）基于异构计算的超大规模并行深度学习平台搭建，360公司实验室项目，2015-2016
（14）彩色喷墨打印机系统，国际合作项目，1996-2001
（15）生物膜计算模型研究，省自然基金重点，2008-2010
（16）计算生物学中的学习算法研究，省杰出青年基金，2007-2009

科研获奖:
（1）2019年，microRNA结构与功能的智能预测方法，教育部高等学校科学研究优秀成果自然科学二等奖
（1）2008年，机器学习算法及其应用研究，省自然科学三等奖
（2）2002年，农业专家系统及其开发工具研究，省科技进步二等奖
（3）2009年，计算生物学中的学习方法研究，省高校科技二等奖

在读研究生:
（1）田舜禹，男，博士生，2018级
（2）王鹏跃，女，博士生，2019级
（3）梁书彤，男，硕士生，2017级
（4）陆剑锋，男，硕士生，2017级
（5）李栋，男，硕士生，2018级
（6）刘开峰，男，硕士生，2018级
（7）邵首飞，男，硕士生，2018级
（8）杨倩楠，女，硕士生，2018级
（9）杨帅，男，硕士生，2018级
（10）张彬，男，硕士生，2018级
（11）王偲佳，女，硕士生，2019级
（12）李伯涵，男，硕士生，2019级
（13）陈加栋，男，硕士生，2019级
（14）马力，男，硕士生，2020级

目前讲授：
（1）本科生课程：“离散数学”
（2）研究生课程：“机器学习算法”
曾讲授：
（1）博士生课程：“机器学习理论与方法”、“机器学习”、“生物信息学”
（2）硕士生课程：“计算复杂性理论”、“自然计算专题”、“计算生物学”
（3）本科生课程：“组合数学”

教学获奖：
（1）宝钢教育基金优秀教师奖（2015年）
（2）《计算机技术领域工程硕士专业学位基本要求》及培养质量体系的研究与实践，省高等教育教学成果奖二等奖（2018年）

招生信息：
（1）目前在读博士生4人、硕士生12人
（2）每年可以招收博士生1-2人、硕士生3-4人
（3）欢迎计算机科学与技术、自动化（控制科学与工程）、人工智能、生物信息学等专业（学科）的同学报考

桃李满天：
已培养毕业博士21人、硕士80余人。其中，指导毕业博士情况：
（1）李建伏：毕业于2008年，中国民航大学，计算机科学与技术学院，副教授
（2）邓超：毕业于2009年，中国移动通信研究院，业务支撑研究所，研究员
（3）邹权：毕业于2009年，电子科技大学，基础与前沿研究院，教授，博士生导师
（4）王峻：毕业于2010年，西南大学，计算机与信息科学学院，副教授、硕士生导师
（5）于建涛：毕业于2011年，西北农林科技大学，信息工程学院，讲师
（6）李艳娟：毕业于2012年，东北林业大学，信息与计算机工程学院，副教授、硕士生导师
（7）玄萍：毕业于2012年，黑龙江大学，计算机科学技术学院，教授、硕士生导师
（8）吴伟宁：毕业于2013年，哈尔滨工程大学，计算机科学与技术学院, 副教授
（9）王娟：毕业于2014年，内蒙古大学，计算机学院，副教授、硕士生导师；曾获2013年度博士生“国家奖学金”
（10）徐云刚：毕业于2014年，美国Wake Forest University，博士后；曾获2013年度博士生“国家奖学金”
（11）王春宇：毕业于2015年，哈尔滨工业大学，计算机科学与技术学院，副教授、硕士生导师
（12）代启国：毕业于2015年，大连民族大学，计算机科学与工程学院，副教授；曾获2014年度博士生“国家奖学金”
（13）滕志霞：毕业于2016年，东北林业大学，信息与计算机工程学院，讲师
（14）李晋：毕业于2016年，哈尔滨医科大学，生物信息科学与技术学院，副教授、硕士生导师
（15）程爽：毕业于2016年，中国工程物理研究院，工程师
（16）田侦：毕业于2017年，郑州大学，信息工程学院，讲师
（17）邢林林：毕业于2018年，山东理工大学，计算机科学与技术学院，讲师
（18）潘智勇：毕业于2019年，北华大学，计算机科学与技术学院，实验师
（19）郭颖婕：毕业于2019年，电子科技大学，基础与前沿研究院，博士后
（20）余冬华：毕业于2019年，绍兴文理学院计算机科学与技术系，讲师
（21）李阳：毕业于2020年

学术论文:
2020
1. Predicting sub-Golgi apparatus resident protein with primary sequence hybrid features. IEEE Access, 2020, 8: 4442-4450（SCI, IF=4.098）
2. A cancer survival prediction method based on graph convolutional network. IEEE Transactions on Nanobioscience, 2020, 19(1): 117-126（SCI, IF=1.927）
3. 基于显著图的弱监督实时目标检测。自动化学报，2020, 46(2): 242-255（EI，一级学报）

2019
1. Variational inference with Gaussian mixture model and householder flow, Neural Networks, 2019, 109: 43–55（SCI, IF=5.785）
2. Density peaks clustering based on weighted local density sequence and nearest neighbor assignment. IEEE Access, 2019, 7: 34301-34317（SCI, IF=4.098）
3. OutDet: an algorithm for extracting the outer surfaces of building information models for integration with geographic information systems. International Journal of Geographical Information Science, 2019, 33(7): 1444-1470（SCI, IF=3.545）
4. Construction of complex features for computational predicting ncRNA-Protein interaction. Frontiers in Genetics, 2019, 10(article 18)1-10, 20190201（SCI, IF=3.517）
5. Combining sparse group lasso and linear mixed model improves power to detect genetic variants underlying quantitative traits. Frontiers in Genetics, 2019, 10:271（SCI, IF=3.517）
6. A new algorithm for identifying genome rearrangements in the mammalian evolution. Frontiers in Genetics, 2019, 10: 1020（SCI, IF=3.517）
7. Predicting MiRNA-disease association by latent feature extraction with positive samples. Genes, 2019, 10, 80: 1-14（SCI, IF=3.331）
8. Perspectives of Bioinformatics in Big Data Era. Current Genomics, 2019, 20(2): 79-80（SCI, IF=2.174）
9. Drug-target interaction data cluster analysis based on improving the density peaks clustering algorithm. Intelligent Data Analysis. 2019, 23(6): 1335-1353（SCI, IF=0.612）
10. Detecting transportation modes from GPS trajectories using recurrent neural network. 11th International Conference on Contemporary Problems of Architecture and Construction，438-446，Oct. 13-16, 2019, Yerevan, Armenia
11. 药物靶标作用关系预测结果评价及查询验证。计算机研究与发展，2019, 56(9): 1881-1888（EI，一级学报）
12. 基于深度学习的出行模式识别方法。哈尔滨工业大学学报，2019，51（11）：1-7（EI）
13. 基于Convolutional-LSTM的蛋白质亚细胞定位研究。计算机科学与探索, 2019,13(6): 982-989
14. 城市空气质量感知方法综述。计算机科学，2019，46（6A）：35-40，51
15. 基于机器学习的医疗决策支持系统综述。计算机工程与应用，2019， 55（19）：1-11

2018
1．An improved K-medoids algorithm based on step increasing and optimizing medoids. Expert Systems With Applications. 2018,92:464-473（JCR:Q1, ESI, SCI. IF= 3.928）
2．Weakly supervised semantic segmentation based on EM algorithm with localization clues. Neurocomputing. 2018, 275: 2574–2587（SCI, IF=3.317）
3. Gene-based nonparametric testing of interactions using distance correlation coefficient in case-control association studies. Genes, 2018, 9: 608 (SCI，IF=3.242)
4. Gene regulatory networks reconstruction using the flooding-pruning hill-climbing algorithm. Genes, 2018, 9(7): 342 (SCI，IF=3.242)
5. Computational drug repositioning usingmeta-path-based semantic network analysis, BMC Systems Biology, 2018, 12(Suppl 9):134, 123-134 [From 29th International Conference on Genome Informatics Yunnan, China. 3-5 December 2018] (SCI, IF=2.213)
6. Identification and priorization of differentially expressed genes for time-series gene expression data. Frontiers of Computer Science. 2018, 12(4): 813-823 (SCI，IF=1.105；ESI；CCF 推荐期刊)
7. Figure-ground segmentation based on class-independent shape priors, Journal of Electronic Imaging, 2018, 27(1), 013018 (SCI, IF=0.780)
8. Topic network: topic model with deep learning for image classification, Journal of Electronic Imaging, Journal of Electronic Imaging 27(3), 033009 (SCI, IF=0.780)
9．Prediction of potential disease-associated microRNAs based on hidden conditional random field. Journal of Harbin Institute of Technology (New Series), 2018，25（1）：57-65（EI）
10.Multi-label answer aggregation based on joint matrix factorization, International Conference on Data Mining (ICDM) (CCF Rank B). pp. 517-526, Nov 17-20, 2018, Singapore（EI）
11.Weighted matrix factorization based data fusion for predicting lncRNA-disease associations, IEEE International Conference on Bioinformatics and Biomedicine (BIBM) (CCF B), 2018, pp. 572-577, 3-6 December 2018, Madrid（EI）
12.基于U统计量和集成学习的基因互作检测方法，计算机研究与发展，2018，55 (8): 1683-1693（EI，一级学报）
13.水稻组织特异性蛋白质相互作用网络构建方法. 哈尔滨工业大学学报, 2018, 50(11): 1~9 (EI)

2017
1．A comprehensive overview and evaluation of circular RNA detection tools. PLoS Computational Biology, 2017,13(6): e1005420 (SCI, IF=4.587)
2．An improved Bayesian network method for reconstructing gene regulatory network based on candidate auto selection. BMC Genomics, 2017, 18(Suppl 9):844[From IEEE BIBM International Conference on Bioinformatics & Biomedicine (BIBM) 2016, Shenzhen, China. 15-18 December 2016]( SCI，IF=4.397)
3．A metric on the space of kth-order reduced phylogenetic networks. Scientific Reports, 2017, 7(1):3189（JCR:Q2, SCI. IF=4.259）
4. Refine gene functional similarity network based on interaction networks. BMC Bioinformatics, 2017, 18(Suppl 16):550, 183-193[From 16th International Conference on Bioinformatics (InCoB 2017) Shenzhen, China. 20-22 September 2017, the Graduate School at Shenzhen, Tsinghua University, China]（SCI，IF=2.448）
5．Constructing an integrated gene similarity network for the identification of disease genes. Journal of Biomedical Semantics 2017, 8(Suppl 1):32[From Biological Ontologies and Knowledge bases workshop on IEEE BIBM 2016 Shenzhen, China. 16 December 2016](SCI, IF=1.826)
6. Revealing protein functions based on relationships of interacting proteins and GO terms. Journal of Biomedical Semantics 2017, 8(Suppl 1):27, 9-17[From Biological Ontologies and Knowledge bases workshop on IEEE BIBM 2016, Shenzhen, China. 16 December 2016] (SCI, IF=1.826)
7．一种基于多组学生物网络的癌症关键模块挖掘方法. 中国科学: 信息科学， 2017, 47（11）: 1510-1522（EI，一级学报）
8．基于降维的蛋白质不相关功能预测. 中国科学: 信息科学，2017, 47（10）: 1349-1368（EI，一级学报）
9．基于距离不等式的K-medoids 聚类算法. 软件学报，2017,28(12):3115-3128（EI，一级学报）
10．miRNA与疾病关联关系预测算法. 软件学报，2017,28(11):3094-3102（EI，一级学报）
11．基于标记与特征依赖最大化的弱标记集成分类. 软件学报，2017, 28(11): 2851-2864（EI，一级学报）
12．基于读分割最优匹配的indels识别算法. 软件学报，2017, 28(10): 2640-2653（EI，一级学报）

2016
1. Identify bilayer modules via pseudo-3D clustering: applications to miRNA-gene bilayer networks, Nucleic Acids Research, 2016, 44(20):e152(SCI, IF=10.162)
2. eSNPO: An eQTL-based SNP Ontology and SNP functional enrichment analysis platform. Scientific Reports, 2016，6, 30595; doi: 10.1038/srep30595 (SCI, IF=5.228)
3. SGFSC: speeding the gene functional similarity calculation based on hash tables. BMC Bioinformatics. 2016, 17:445(SCI, IF=2.435)
4. A robust local sparse coding method for image classification with Histogram Intersection Kernel. Neurocomputing, 2016, 184: 36–42 (SCI, IF=2.005)
5. MiRTDL: a deep learning approach for miRNA target prediction. IEEE/ACM Transactions on Computational Biology and Bioinformatics(TCBB), 2016, 16(3): 1161-1169 (SCI, IF=1.955)
6. EnPC: an ensemble clustering framework for detecting protein complexes in protein-protein interaction network, Current Proteomics, 2016, 13(2): 143-150(SCI, IF=0.59)
7. Construct Protein-Protein Interaction Network based on domain-domain interactions. Journal of Harbin Institute of Technology(New Series), 2016, 23(4): 27-36(EI)
8. Reconstructing gene regulatory network based on candidate auto selection method. In the Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine (BIBM 2016). Shenzhen, China, 2016(EI)
9. Constructing an integrated gene similarity network for the identification of disease genes. In the Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine (BIBM 2016). Shenzhen, China, 2016(EI)
10. Epistasis detection using a permutation-based gradient boosting machine. In the Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine (BIBM 2016). Shenzhen, China, 2016:1-6(EI)
11. 基于正负样例的蛋白质功能预测. 计算机研究与发展. 2016, 53 (8): 1753-1765 (EI)
12. 动态-静态混合的时序蛋白质网络构建方法. 哈尔滨工业大学学报. 2016,48(11):41-46(EI)

2015
1. HAlign: Fast multiple similar DNA/RNA sequence alignment based on the centre star strategy. Bioinformatics, 2015, 31(15): 2475-2481 (SCI, IF=4.981)
2. A gene-based information gain method for detecting gene-gene interactions in case-control studies. European Journal of Human Genetics, 2015, 23: 1566-1572 (SCI, IF=4.349)
3. SeedsGraph: an efficient assembler for next generation sequencing data. BMC Medical Genomics, 2015, 8(Suppl 2): S13 (SCI, IF=3.91)
4. An overview of SNP interactions in genome-wide association studies. Briefings in Functional Genomics. 2015, 14(2): 143-155 (SCI, IF=3.427)
5. Integrating multiple networks for protein function prediction, BMC Systems Biology, 2015, 9(Suppl 1): S3(SCI, IF=2.853)
6. Harmonious competition learning for Gaussian mixtures. Neurocomputing, 2015, 170: 228-239(SCI, IF=2.005)
7. Actively constructing an effective training set by expected gain maximization criterion. Neurocomputing, 2015, 158: 62-72(SCI, IF=2.005)
8. Mining disease genes using integrated protein-protein interaction and gene-gene co-regulation information. FEBS Open Bio, 2015, 5: 251-256(SCI, IF=1.515)
9. 非负局部约束线性编码图像分类算法. 自动化学报, 2015, 41(7): 1235-1243(EI)
10. 基于加性噪声模型的基因调控网络构建算法[J]. 哈尔滨工业大学学报, 2015, 47(11)：22-26(EI)
11. 基于信息增益理论的整体基因中基因互作挖掘方法. 中国科技论文. 2015, 10(2)：186-191

2014
1. Inferring the soybean (Glycine max) microRNA functional network based on target gene network. Bioinformatics, 2014, 30(1): 94-103 (SCI, IF=5.323)
2. SoyFN: a knowledge database of soybean functional networks. DATABASE - The Journal of Biological Databases and Curation(Oxford), 2014: bau019 (SCI, IF=4.200)
3. A least square method based model for identifying protein complexes in protein-protein interaction network. BioMed Research International, 2014, 720960:1-9(SCI, IF:2.706)
4. Computational prediction of protein function based on weighted mapping of domains and GO terms. BioMed Research International, 2014, 641469: 1-9 (SCI, IF=2.706)
5. CPL: Detecting protein Complexes by Propagating Labels on protein-protein interaction network. Journal of Computer Science and Technology, 2014, 29(6): 1083-1093(SCI, IF=0.642)
6. Identification of functional miRNA regulatory modules and their associations via dynamic miRNA regulatory function. BIBM 2014
7. 一种蛋白质复合体模块度函数及其识别算法. 计算机研究与发展. 2014, 51(10): 2178-2186(EI)
8. SVM与主动学习方法相结合的蛋白质相互作用预测. 计算机科学, 2014, 41(2): 82-86

2013
1. LNETWORK: an efficient and effective method for constructing phylogenetic networks. Bioinformatics, 2013, 29(18): 2269-2276 (SCI, IF=5.323)
2. Measuring gene functional similarity based on group-wise comparison of GO terms. Bioinformatics, 2013, 29(11): 1424-1432 (SCI, IF=5.323)
3. Prediction of microRNAs associated with human diseases based on weighted k most similar neighbors. PLoS ONE, 2013, 8(8) : e70204 (SCI, IF=4.411)
4. A novel insight into gene ontology semantic similarity. Genomics, 2013, 101(6): 368-375 (SCI, IF=2.958)
5. Computational approaches on detecting non-coding RNA. Current Genomics. 2013, 14(6): 371-377(SCI, IF=2.408)
6. BIMLR: A method for constructing rooted phylogenetic networks from rooted phylogenetic trees, Gene, 2013, 527(Issue 1): 344-351 (SCI, IF=2.196)
7. A probabilistic model of active learning with multiple noisy oracles. Neurocomputing, 2013, 118: 253-262 (SCI, IF=1.634)
8. MLPA: Detecting overlapping communities by multi-label propagation approach, accepted 2013 IEEE Congress on Evolutionary Computation(IEEE CEC 2013), June 20-23, Cancún, México: 681-688(EI)
9. Effective constructing training sets for object detection. 2013 IEEE International Conference on Image Processing. Sep. 15-18, 2013, Melbourne, Australia: 3377-3380 (EI)
10. A new distance computing method for DNA sequences in phylogenetic analysis. 2013 10th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD 2013), July 23-25, 2013, Shenyang, China: 713-717(EI)

2012
1. Understanding microRNA regulation: A computational perspective. IEEE Signal Processing Magazine, 2012, 29(1):77-88(SCI, IF=5.86)
2. A Bayesian decision fusion approach for microRNA target prediction．BMC Genomics, 2012, 13(Suppl 8):S13: 1-11(SCI, IF=4.397)
3. Feature selection for monotonic classification. IEEE Transactions on Fuzzy Systems, 2012, 20(1): 69-81(SCI, IF=3.34)
4. A new relational Tri-training system with adaptive data editing for inductive logic programming. Knowledge-Based Systems, 2012, 35(11): 173-185(SCI, IF=2.422)
5. DBGSA: a novel method of distance-based gene set analysis. Journal of Human Genetics, 2012,57(10)：642-653(SCI, IF=2.4)
6. Rank entropy-based decision trees for monotonic classification．IEEE Transactions on Knowledge and Data Engineering, 2012, 24(11): 2052-2064(SCI, IF=1.657)
7. A relational learning algorithm combining relational tri-training and relational instance-based learning. Journal of information and computational science, 2012, 9(2): 425-436(EI)
8. Phase transition and new fitness function based genetic inductive loigc programming algorithm. In Xiaodong Li editor, Proceedings of the 2012 IEEE Congress on Evolutionary Computation：956-963, Brisbane, Australia(EI)
9. Connection of the beam width and the learning success rate in the phase transition framework for relational learning, 2012 9th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD 2012), 29-31 May 2012, Chongqing, China: 865-869(EI)
10. Fitness function based on binding and recall rate for genetic inductive logic programming, the 2012 International Conference on Swarm Intelligence(ICSI 2012), June 17 -20, 2012, Shenzhen, China(EI)
11. Constructing training distribution by minimizing variance of risk criterion for visual category learning. 2012 IEEE International Conference on Image Processing ICIP 2012, Sep. 30 - Oct. 3, 2012 ,Orlando, Florida, U.S.A.: 101-104(EI)
12. The ROIs segmentation method of the lungs based on adaptive EM algorithm and edge gradient information. The 16th International Conference on Image Processing, Computer Vision, & Pattern Recognition (IPCV'12: July 16-19, 2012, USA) (EI)
13. 基于采样策略的主动学习算法研究进展. 计算机研究与发展. 2012, 49(6): 1162?1173(EI)
14. 植物抗性基因识别中的随机森林分类方法. 计算机科学与探索. 2012, 6(1): 67?77
15. 关系tri-training: 利用无标记数据学习一阶规则. 计算机科学与探索, 2012, 6(5): 430-442

2011
1. PlantMiRNAPred: efficient classification of real and pseudo plant pre-miRNAs. Bioinformatics, 2011, 27 (10): 1368-1376(SCI, IF=5.323)
2. MaturePred: efficient identification of microRNAs within novel plant pre-miRNAs. PLoS ONE, 2011, 6(11): e27422(SCI, IF=4.411)
3. QTL underlying resistance to two HG types of Heterodera glycines found in soybean cultivar 'L-10'. BMC Genomics 2011, 12:233(SCI, IF=4.397)
4. A new co-training-style random forest for computer aided diagnosis. Journal of Intelligent Information Systems, 2011, 36(3): 253-281(SCI, IF=0.875)
5. Tri-training and MapReduce-based massive data learning. International Journal of General Systems, 2011, 40(4): 355-380(SCI, IF=0.826)
6. Web page classification using relational learning algorithm and unlabeled data. Journal of Computers, 2011, 6(3): 474-479(EI)
7. Detection of playfield with shadow and its application to player tracking. 2011 IEEE International Workshop on Machine Learning for Signal Processing, September 18-21, 2011, Beijing, China(EI)
8. Active learning with optimal distribution for image classification. The 2nd International Conference on Multimedia Technology (ICMT2011), July 26-28, 2011, Hangzhou, China: 132-136(EI)

2010
1. Simple sequence-based kernels do not predict protein-protein interactions. Bioinformatics, 2010, 26(20): 2610-2614(SCI, IF=5.323)
2. Fuzzy preference based rough sets. Information Sciences, 2010, 180(10): 2003-2022(SCI, IF=3.291；EI)
3. Information entropy for ordinal classification. Science in China Series F-Information Sciences. 2010, 53(6): 1188-1200(SCI)
4. DuplexFinder: Predicting the miRNA-miRNA* duplex from the animal precursors. Int. J. Bioinformatics Research and Applications, 2010, 6 (1): 69-81
5. Sequence analysis based adaptive hierarchical clustering approach for admixture population structure inference. Journal of Information & Computational Science, 2010, 7(13): 2589-2597(EI)
6. Genomic analysis of microRNA promoters and their cis-acting elements in soybean. Agricultural Sciences in China, 2010, 9(11): 1561-1570(SCI)
7. A graph and hierarchical clustering based approach for population structure inference. 2010 ACM International Conference on Bioinformatics and Computational Biology, ACM-BCB 2010, August 2-4, Niagara Falls, New York, USA：346-349(EI)
8. Two-stage clustering based effective sample selection for classification of premiRNAs. IEEE International Conference on Bioinformatics & Biomedicine 2010 (IEEE BIBM 2010), 18-21 Dec 2010, Hong Kong
9. SNPs and entropy based hierarchical clustering method for genetic phylogeny analysis. 2010 Seventh International Conference on Fuzzy Systems and Knowledge Discovery (FSKD 2010): 2229-2233, 10-12 August, 2010, Yantai, Shandong, China(EI, ISTP)
10. EST clustering in large dataset with MapReduce. 2010 First International Conference on Pervasive Computing, Signal Processing and Applications (PCSPA2010): 968-971, September 17-19, 2010, Harbin, China(EI)
11. Automatically Detecting Lung Nodules Based on Shape Descriptor and Semi-Supervised Learning. 2010 International Conference on Computer Application and System Modeling (ICCASM 2010), Taiyuan, China. October 22-24, 2010, v1647-650(EI)
12. A Novel Center Star Multiple Sequence Alignment Algorithm Based on Affine Gap Penalty and K-Band. 2010 International Conference on Services Science, Management and Engineering(SSME2010), Dec 26-28, 2010, Tianjin, China: 50-52
13. 类别不平衡的分类方法及在生物信息学中的应用. 计算机研究与发展, 2010, 47(8): 1407-1414(EI)
14. 多序列比对算法的研究进展. 生物信息学, 2010, 8(4)：311-315

2009
1. A hybrid clustering and graph based algorithm for tagSNP selection. Soft Computing, 2009,13(12):1143-1151(SCI, IF=1.328；EI)
2. A new co-training-style random forest for computer aided diagnosis. Journal of Intelligent Information Systems, 2009, 33(3) (SCI, IF=1.07)
3. A site-clustering graph based tagSNP selection algorithm in genotype data. BMC Bioinformatics, 2009, 10 (Suppl 1):S71-82(SCI, IF=3.78；EI)
4. Predicting RNA secondary structure based on the class information and Hopfield network. Computers in Biology and Medicine. 2009,39(3):206-214(SCI, IF=1.27；EI)
5. Sea battle-filed simulation based on Vega. Journal of Harbin Institute of Technology, 2009, 16(1): 1-4(EI)
6. Novel H/ACA box snoRNA Mining and Secondary Structure Prediction Algorithms. The 4th International Conference on Rough Sets and Knowledge Technology (RSKT2009), Gold Coast, Australia, 14th-16th July, 2009. LNAI, 5589: 538-546(EI, ISTP)
7. A study on autonomous video navigation in close range with a cooperative target. 6th International Symposium on Multispectral Image Processing and Pattern Recognition (MIPPR 2009) v 7496, October 30 - November 1, 2009, Yichang, China(EI)
8. A novel superresolution algorithm based on standard displacements. 6th International Symposium on Multispectral Image Processing and Pattern Recognition (MIPPR 2009) v 7498, October 30 - November 1, 2009, Yichang, China(EI)
9. 一种快速的多序列星比对算法. 电子学报, 2009,37(8): 1746-1750(EI)
10. 基于直推式支持向量机的图像检索研究. 模式识别与人工智能, 2009, 22(5)：774-779 (EI)
11. 质心法：受类别驱动的RNA二级结构预测方法. 南京大学学报. 2009, 45(5): 677-688
12. 生物信息学中的学习问题. 山东大学学报. 2009, 39(3):1-6
13. 基于线粒体SNP的疾病人群分类方法研究. 2009中国计算机大会.CNCC 2009
14. 一种适合大豆MicroRNA鉴定的RT-PCR方法. 大豆科学, 2009, 28(4)：600-604

2008
1. A topological transformation in evolutionary tree search methods based on maximum likelihood combining p-ECR and neighbor joining. BMC bioinformatics, 2008, 9(Suppl 6):S4(SCI, IF=3.78；EI)
2. A new approach to evolutionary tree reconstruction combining particle swarm optimization with p-ECR. International Journal of Computational Intelligence Research(Special issue on Particle swarm optimization), 2008, 4(2): 187-195
3. Research on machine learning model and algorithm based on human cognition. In Proceedings of 2008 International Conference on Advanced Intelligence (ICAI2008), Beijing, China, Oct,2008: 59-64
4. TagSNPs selection using maximum density subgraph. In the 4 th International Conference on Natural Computation (ICNC'08, Oct.18-20, 2008), Jinan, China, v5: 128-132(EI, ISTP)
5. Participatory learning based semi-supervised classification. In the 4 th International Conference on Natural Computation (ICNC'08, Oct.18-20, 2008), Jinan, China, v4: 207-216(EI, ISTP)
6. An improved diverse density algorithm for multiple overlapped instances. In the 4 th International Conference on Natural Computation (ICNC'08, Oct.18-20, 2008), Jinan, China, v3: 88-91(EI, ISTP)
7. Prediction of protein-protein interactions from secondary structures on binding motifs using the statistic method. In the 4 th International Conference on Natural Computation (ICNC'08, Oct.18-20, 2008), Jinan, China, v5: 100-103(EI, ISTP)
8. A novel comparative sequence analysis method for ncRNA secondary structure prediction without multiple sequence alignment. In the 4 th International Conference on Natural Computation (ICNC'08, Oct.18-20, 2008), Jinan, China, v5: 29-33(EI, ISTP)
9. A new method for simulating protein folding process-snake algorithm. Proceedings ICICSE 2008 - 2008 International Conference on Internet Computing in Science and Engineering, January 28-29, 2008: 39-42(EI, ISTP)
10. The inverse protein folding process by artificial life approaches. Proceedings ICICSE 2008 - 2008 International Conference on Internet Computing in Science and Engineering, January 28-29, 2008: 35-38(EI, ISTP)
11. Research on knowledge-based intelligent agent model. WMSCI 2008: 12th World Multi-Conference on Systemics, Cybernetics and Informatics, Vol Vii, Proceedings, 2008: 276-281(ISTP)
12. 基于Tri-train ing和数据剪辑的半监督聚类算法. 软件学报, 2008, 19(3)：663-673(EI)
13. 一种基于Quartet Puzzling 和邻接法的进化树构建算法. 计算机研究与发展, 2008, 45(11)：1965-1973(EI)
14. RNA二级结构预测方法综述. 电子学报, 2008, 36(2)：331-337(EI)
15. 基于智能Agent的农业智能决策系统研究. 高技术通讯, 2008, 18(4)：392-399(EI)
16. 参数序列比对算法研究. 生物信息学, 2008, 6(2)：65-67, 84

2007
1. Improving the efficiency of p-ECR moves in evolutionary tree search methods based on Maximum Likelihood by neighbor joining. In The Symposium of Computations in Bioinformatics and Bioscience (SCBB'07: Aug. 13-15, 2007), Iowa, USA: 60-67(SCI, EI, ISTP)
2. Simulations of protein folding process. In The 2007 International Conference on Bioinformatics and Computational Biology (BIOCOMP'07: June 25-28, 2007), Las Vegas, Nevada, USA：387-391
3. Methods and simulations for the protein folding. In The 2007 International Conference on Bioinformatics and Computational Biology (BIOCOMP'07: June 25-28, 2007), Las Vegas, Nevada, USA：383-386
4. A MAS Communication Model Based on Star-Ring Structure. Proceedings of 2007 International Conference on Machine Learning and Cybernetics, Hongkong, vol.6:3184-3188(EI, ISTP)
5. An Extended Contract-Net Negotiation Model Based on Task Coalition and Genetic Algorithm. Proceedings of 2007 International Conference on Machine Learning and Cybernetics, Hongkong, vol.2:879-884(EI)
6. RNA secondary structure prediction based on forest representation and Genetic Algorithm. In The 3rd International Conference on Natural Computation (ICNC'07), 2007: 370-374(EI)
7. An improved quick algorithm for aligning DNA/RNA sequences. CIS Workshops 2007, 2007 International Conference on Computational Intelligence and Security, Dec 15-19, 2007 Harbin, China: 825-828(EI, ISTP)
8. An edge-detection method for moving objects. Proceedings of the IEEE International Conference on Automation and Logistics (ICAL2007) August 18 - 21, 2007, Jinan, China：1157-1560(EI, ISTP)
9. Computer Simulation for protein folding. The 2007 International Conference on Modeling, Simulation & Visualization Methods(MSV2007). 2007, USA：128-131
10. Real-time Competition Simulation System, International Multi-Symposiums on Computer and Computational Sciences (IMSCCS|07) August,13-15,2007,Iowa, USA：318-321(EI)
11. 基于自适应数据剪辑策略的Tri-training算法. 计算机学报, 2007, 30(8)：1213-1226(EI)
12. 转录因子结合位点识别算法的研究. 电子学报, 2007, 35(12A)：83-89(EI)
13. 蛋白质相互作用及其网络预测方法研究进展. 电子学报, 2007, 35(12A)：1-7(EI)
14. 基于支持向量机和竞争学习的图像配准方法. 哈尔滨工业大学学报, 2007, 39(7)：1114-1116(EI)

2006
1. Research of immune system response simulation based on cell automata. Chinese Journal of Electronics, 2006, 15(4A): 785-788 (SCI, EI)
2. Tri-training and data editing based semi-supervised clustering algorithm. In 5th Mexican InternationalConferenceon Artificial Intelligence (MICAI 2006), Lecture Notes in Artificial Intelligence, 2006, Volume 4293: 641-651(EI, ISTP)
3. A permutation-based genetic algorithm for predicting RNA secondary structure-a practicable approach,” The 2nd International Conference on Fuzzy Systems and Knowledge Discovery (FSKD), Lecture Notes in Artificial Intelligence (LNAI) 3614. 2006, 861-864(SCI, EI, ISTP)
4. An ontology-based method for similarity calculation of concepts in the semantic web. 5th International Conference on Machine Learning and Cybernetics, AUG 13-16, 2006 .Proceedings of 2006 International Conference on Machine Learning and Cybernetics, Vols 1-7 : 1538-1542, 2006(EI, ISTP)
5. 系统发生树构建技术综述. 电子学报, 2006, 34(11)：2047-2052(EI)
6. 基于熟人联盟及扩充合同网协议的多智能体协商模型. 计算机研究与发展, 2006, 43(7)：1155-1160(EI)

2005
1. Improving retrieval performance with the combination of thesauri. and automatic relevance feedback. Advances in Machine Learning and Cybernetics, Lecture Notes in Computer Science, 2005, Volume 3930: 322-328(SCI, EI, ISTP)
2. Simulating the mutation of antibody of human immune system. In Proceeding of 2005 International Conference on Neural Networks and Brain (ICNN&B 2005), Beijing, P. R. China, 2005: 240-244(EI, ISTP)
3. A new approach to query expansion. Proceedings of the Fourth International Conference on Machine Learning and Cybernetics (ICMLC2005), Guangzhou, 18-21 August 2005. page:2302-2306(EI, ISTP)
4. Evaluation criteria on down-compatibility degree of fuzzy inference mechanism. Proceedings of the Fourth International Conference on Machine Learning and Cybernetics (ICMLC2005), Guangzhou, 18-21 August 2005. page:2418-2423(EI, ISTP)
5. The research and application of the self-learning expert system based on BP network. Proceedings of the Fourth International Conference on Machine Learning and Cybernetics (ICMLC2005), Guangzhou, 18-21 August 2005. page:4153-4157(EI, ISTP)
6. Middleware-based expert system platform for agriculture production decisions. In Proceeding of the Third International Symposium on Intelligent Information Technology in Agriculture (ISIITA2005), Beijing, P. R. China, 2005
7. 基于progressive多序列比对方法求解多序列比对得启发式算法. 生物信息学, 2005, 3(4)：171-174

2004
1. A new Q-learning algorithm based on the metropolis criterion. IEEE Transactions On Systems, Man, And Cybernetics—Part B: Cybernetics, 2004, 34 (5): 2140- 2143 (SCI, IF=2.36；EI)
2. Q_learning based on active backup and memory mechanism. In Proceeding of the Third International Conference on Machine Learning and Cybernetics (ICMLC 2004), Shanghai, P. R. China, 2004: 271-275(EI, ISTP)
3. 基于规则和模糊线性规划表示的专家系统研究. 高技术通讯, 2004, 14(7)：1- 4(EI)
4. 一种快速的间接关联挖掘算法. 高技术通讯, 2004, 14(7)：49- 52(EI)
5. 一种新的面向属性归纳中概念层次技术研究. 管理科学学报, 2004, 7(1)：65-72

2003之前
1. Application of nonlinear color matching model to four-color ink-jet printing. Journal of Harbin Institute of Technology (New Series). 2002, 9(3): 270-275(EI)
2. A simulated annealing-based algorithm for traveling salesman problem. Journal of Harbin Institute of Technology (New Series). 1997, 4(4): 35-38(EI)
3. Research on knowledge representation and inference based on extended weighted fuzzy logic. In Proceeding of the Second International Symposium on Intelligent Information Technology in Agriculture (ISIITA), Beijing, P. R. China, 2003: 95-98
4. Research of dithering pattern based on evolutionary algorithm and space_filling curve. In Proceedings of 2001 International Conference on Management Science & Engineering, Harbin, P. R. China, 2001: 590-594(ISTP)
5. 基于BP网络的色彩匹配方法研究. 计算机学报, 2000, 23(8)：819-823(EI)
6. 评价函数驱动的抖动模式的研究.软件学报, 1998, 9(5)：383-389 (EI)
7. 一种基于信息增益与费用评价函数的特征选择准则. 计算机研究与发展, 1999, 36(7)：788-793(EI)
8. 基于样本空间学习算法的彩色匹配方法研究. 自动化学报, 2001, 27(2)：186-193(EI)
9. 基于偏最小二乘回归分析的混色数据学习算法研究. 电子学报, 2001, 29(3)：429-431(EI)
10. 基于划分策略和填充曲线的抖动模式研究. 计算机辅助设计与图形学学报, 2001, 13(4)：319-323(EI)
11. 基于BACON系统实现彩色图像黑白打印方法的自动化. 计算机辅助设计与图形学学报, 2001, 13(8)：747-751(EI)
12. 专家系统中知识库组织与维护技术的研究. 高技术通讯, 2002, 12(2)：1- 4, 9(EI)
13. 加强学习中决策准则的选择. 清华大学学报, 1998, 38(S2)：165-168
14. 题库系统试卷自动生成算法研究. 哈尔滨工业大学学报, 2003, 35(3)：342-346(EI)
15. 一个新的基于扩张矩阵的规则抽取覆盖算法. 哈尔滨工业大学学报, 2000, 32(4)：123-126(EI)
16. 连续属性空间的规则学习算法. 哈尔滨工业大学学报, 2000, 32(3)：42-47(EI)
17. 示例学习的扩张图方法. 哈尔滨工业大学学报, 1998, 30(1)：65-67(EI)
18. 基于机器学习的手写汉字特征选择. 哈尔滨工业大学学报, 1998(2), 30(1)：57-60(EI)
19. 基于模拟退火算法的抖动模式的研究与实现. 哈尔滨工业大学学报, 1997, 29(3)：65-67(EI)

出版书籍：
[1]（美）卢格（Luger，G. F.）著；郭茂祖等译。人工智能：复杂问题求解的结构和策略（原书第6版），北京：机械工业出版社，2009. 12
[2]（英）罗杰斯（Rogers，S.），（英）吉罗拉米（Girolami，M.）著；郭茂祖等译。机器学习教程，北京：机械工业出版社，2013. 10