Selected Publications

    2017

    Journal Papers & Book Chapters

  1. Alexios Koutsoukas, Keith J Monaghan, Xiaoli Li, Jun Huan , Deep-learning: investigating deep neural networks hyper-parameters and comparison of performance to shallow methods for modeling bioactivity data , Journal of Cheminformatics , Vol. 9, No. 42, 2017  PDF
  2. Xiaoyang Chen, Hongwei Huo, Jun Huan , Jeffrey Scott Vitter, Efficient Graph Similarity Search in External Memory , IEEE Access , Vol. 5, pp. 4551-4560, 2017  PDF
  3. Chao Lan, Yuhao Yang, Bo Luo, Jun Huan , Learning Social Circles in Ego-Networks based on Multi-View Network Structure , IEEE Transactions on Knowledge and Data Engineering , 2017  PDF
  4. Conference Papers

  5. Xiaoli Li, Jun Huan , Constructivism Learning: A Learning Paradigm for Transparent Predictive Analytics , Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (SIGKDD) , Halifax, Canada, August 2017  PDF
  6. Joseph St.Amand, Jun Huan , Sparse Compositional Local Metric Learning , Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (SIGKDD) , Halifax, Canada, August 2017  PDF
  7. 2016

    Journal Papers & Book Chapters

  8. Qiang Yu, Hongwei Huo, Ruixing Zhao, Dazheng Feng, Jeffery Vitter, Jun Huan , RefSelect: a reference sequence selection algorithm for planted (l, d) motif search , BMC Bioinformatics , Vol. 17, No. 9, S37, 2016  PDF
  9. Jingshan Huang, Karen Eilbeck, Barry Smith, Judith A. Blake, Dejing Dou, Weili Huang, Darren A. Natale, Alan Ruttenberg, Jun Huan , Michael T. Zimmermann, Guoqian Jiang, Yu Lin, Bin Wu, Harrison Strachan, Nisansa de Silva, Mohan Vamsi Kasukurthi, Vikash Kumar Jha, Yongqun He, Shaojie Zhang, Xiaowei Wang, Zixing Liu, Glen Borchert, Ming Tan, The Development of Non-Coding RNA Ontology , International Journal of Data Mining and Bioinformatics , 2016  PDF
  10. Jingshan Huang, Karen Eilbeck, Barry Smith, Judith A. Blake, Dejing Dou, Weili Huang, Darren A. Natale, Alan Ruttenberg, Jun Huan , Michael T. Zimmermann, Guoqian Jiang, Yu Lin, Bin Wu, Harrison J. Strachan, Yongqun He, Shaojie Zhang, Xiaowei Wang, Zixing Liu, Glen Borchert, Ming Tan The Non-Coding RNA Ontology (NCRO): A comprehensive resource for the unification of non-coding RNA biology , Journal of Biomedical Semantics , March 2016  PDF
  11. Xiaoqing Peng, Jianxin Wang Jun Huan , Fang-Xiang Wu, Double-layer clustering method to predict protein complexes based on power-law distribution and protein sublocalization , Journal of theoretical biology , 2016  PDF
  12. Alexios Koutsoukas, Joseph St. Amand, Meenakshi Mishra, Jun Huan , Predictive Toxicology: Modeling Chemical Induced Toxicological Response Combining Circular Fingerprints with Random Forest and Support Vector Machine , Frontiers in Environmental Science, section Environmental Informatics , March 2016, doi: http://dx.doi.org/10.3389/fenvs.2016.00011  PDF
  13. Xiang Chen Jun Huan , On-line Graph Partitioning with An Affine Message Combing Cost Function , Big Data Analytics: Methods and Applications , S. Pyne, B. L. S. Rao, S. B. Rao (eds.), Springer, 2016  
  14. Conference Papers

  15. Chao Lan, Jun Huan , Learning with Positive and Unknown Features , IEEE International Conference on Bioinformatics and Biomedicine , Shenzhen, China, December 2016  PDF
  16. Sai Nivedita Chandrasekaran, Jun Huan , Weighted Multi-view Learning for Predicting Drug-Disease Associations , IEEE International Conference on Bioinformatics and Biomedicine , Shenzhen, China, December 2016  PDF
  17. Chao Lan, Sai Nivedita Chandrasekaran, Jun Huan , A Distributed and Privatized Framework for Drug-Target Interaction Prediction , IEEE International Conference on Bioinformatics and Biomedicine , Shenzhen, China, December 2016  PDF
  18. Chao Lan, Xiaoli Li, Yujie Deng, Joseph St. Amand, Jun Huan , A PAC Bound for Joint Matrix Completion via Partially Collective Matrix Factorization , 23rd International Conference on Pattern Recognition , Cancun, Mexico, December 2016  PDF
  19. Yujie Deng, Chao Lan, Jun Huan , Co-Regularized Collective Matrix Factorization for Joint Matrix Completion , 23rd International Conference on Pattern Recognition , Cancun, Mexico, December 2016  PDF
  20. Xiaoli Li, Jun Huan , aptMTVL: Nailing Interactions in Multi-Task Multi-View Multi-Label Learning using Adaptive-basis Multilinear Factor Analyzers , The 24th ACM International Conference on Information and Knowledge Management , Indianapolis, USA, October 2016  PDF
  21. Joseph St.Amand, Jun Huan , Discriminative View Learning for Single View Co-Training , The 24th ACM International Conference on Information and Knowledge Management , Indianapolis, USA, October 2016  PDF
  22. Sai Nivedita Chandrasekaran, Alexios Koutsoukas, Jun Huan , Investigating Multiview and Multitask Learning Frameworks for Predicting Drug-Disease Associations , ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics , Seattle, USA, October 2016  PDF
  23. Gowtham Kumar, Jun Huan , Jordan Carlson, Developing Novel Machine Learning Algorithms to Improve Sedentary Assessment for Youth Health Enhancement , IEEE International Conference on Healthcare Informatics , Chicago USA, October 2016  PDF
  24. Chao Lan, Jianxing Wang, Jun Huan , Towards a Theoretical Understanding of Negative Transfer in Collective Matrix Factorization , the Conference on Uncertainty in Artificial Intelligence (UAI) , New York City, NY, June 2016, acceptance rate 85/275=31%.  PDF
  25. Chao Lan, Yujie Deng, Xiaoli Li, Jun Huan , Co-Regularized Least Square Regression for Multi-View Multi-Class Classification , the International Joint Conference on Neural Networks , Vancouver, Canada, July 2016  PDF
  26. Chao Lan, Yujie Deng, Jun Huan , A Disagreement-based Active Matrix Completion Approach with Provable Guarantee , the International Joint Conference on Neural Networks , Vancouver, Canada, July 2016  PDF
  27. 2015

    Journal Papers & Book Chapters

  28. Qiang Yu, Hongwei Huo, Jeffrey Scott Vitter, Jun Huan , and Yakov Nekrich, An Efficient Exact Algorithm for the Motif Stem Search Problem over Large Alphabets , IEEE/ACM Transactions on Bioinformatics and Computational Biology , Vol. 12, No. 2, pp. 384 - 397, 2015  PDF
  29. Conference Papers

  30. Qiang Yu, Hongwei Huo, Ruixing Zhao, Dazheng Feng, Jeffrey Scott Vitter, and Jun Huan , Reference sequence selection for motif searches , in proceedings of the IEEE International Conference on Bioinformatics and Biomedicine (BIBM'15) , Washington DC, November 2015, acceptance rate: 69/345=19%  PDF
  31. Meenakshi Mishra and Jun Huan , Learning Task Grouping using Supervised Task Space Partitioning in Lifelong Multitask Learning , in proceedings of the ACM Conference on Information and Knowledge Management (CIKM'15) , Melbourne, Australia, October 2015, acceptance rate: 87/484=18%  PDF
  32. Chao Lan and Jun Huan , Reducing the Unlabeled Sample Complexity of Semi-Supervised Multi-View Learning , in proceedings of the 21st ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD'15) , Sydney, Australia, August 2015, acceptance rate: 159/869= 18%  PDF
  33. 2014

    Journal Papers & Book Chapters

  34. Hongliang Fei and Jun Huan , Structured Sparse Boosting for Graph Classification , ACM Transactions on Knowledge Discovery from Data , Vol. 9, No. 1, 2014  PDF
  35. Conference Papers

  36. Qiang Yu, Hongwei Huo, Xiaoyang Chen, Haitao Guo, Jeffrey Scott Vitter, and Jun Huan , An Efficient Motif Finding Algorithm for Large DNA Data Sets , 2014 IEEE International Conference on Bioinformatics and Biomedicine (BIBM'14) , Belfast, UK, November 2014, acceptance rate: 56/286= 19%  PDF
  37. Yuhao Yang, Chao Lan, Xiaoli Li, Bo Luo, and Jun Huan , Automatic Social Circle Detection Using Multi-View Clustering , the 23rd ACM International Conference on Information and Knowledge Management (CIKM'14) , Shanghai, China, November 2014, acceptance rate: 54/257= 21%  PDF
  38. 2013

    Journal Papers & Book Chapters

  39. Said Bleik, Meenakshi Mishra, Jun Huan , and Min Song, Biomedical Text Categorization with Concept Graph Representations Using a Controlled Vocabulary , IEEE/ACM Transactions on Computational Biology and Bioinformatics , Accepted, 2013  PDF
  40. Ruoyi Jiang, Hongliang Fei, Jun Huan , A Family of Joint Sparse PCA Algorithms for Anomaly Localization in Network Data Streams , IEEE Transactions on Knowledge and Data Engineering , Accepted, 2013  PDF
  41. Jintao Zhang, Jun Huan , Predicting Drug-Induced QT Prolongation Effects Using Multi-View Learning , IEEE Transactions on NanoBioscience , Accepted, 2013  PDF
  42. Hongliang Fei and Jun Huan , Structured Feature Selection and Task Relationship Inference for Multi-Task Learning , Knowledge and Information Systems (invited to the KAIS special issue of selected papers from ICDM'11) , Vol. 35, No. 2, pp. 345-364, 2013  PDF
  43. Conference Papers

  44. Meenakshi Mishra, Jun Huan , Multitask Learning with Feature Selection for Groups of Related Tasks , IEEE International Conference on Data Mining (ICDM'12) , Dallas, TX, December 2013  PDF
  45. Qiang Yu, Hongwei Huo, Jeffrey Scott Vitter, Jun Huan , and Yakov Nekrich, StemFinder: An Efficient Algorithm for Searching Motif Stems over Large Alphabets , IEEE International Conference on Bioinformatics and Biomedicine (BIBM) , Shanghai, China, December 2013  PDF
  46. Jingshan Huang, Jun Huan , Alexander Tropsha, Jiangbo Dang, Min Xiong, and Weijian Jiang, Semantics-Driven Frequent Data Pattern Mining on Electronic Health Records for Effective Adverse Drug Event Monitoring , IEEE International Conference on Bioinformatics and Biomedicine (BIBM) , industry track, Shanghai, China, December 2013  PDF
  47. 2012

    Journal Papers & Book Chapters

  48. Brian Quanz, Jun Huan , and Meenakshi Mishra, Knowledge Transfer with Low-Quality Data: a Feature Extraction Issue , IEEE Transactions on Knowledge and Data Engineering , Accepted, 2012 (invited to the TKDE special issue of selected papers from ICDE'11)  PDF
  49. Mohammad Al Hasan, Jun Huan , Jake Yue Chen, and Mohammed J. Zaki, Biological Knowledge Discovery and Data Mining , Scientific Programming , Vol. 20, No. 1, pp.1-2, 2012  PDF
  50. Meenakshi Mishra, Hongliang Fei, and Jun Huan , Computational Prediction of Toxicity , Int. J. of Data Mining and Bioinformatics , 2012  PDF
  51. J. Huang, D. Dou, J. Dang, J.H. Pardue, X. Qin, J. Huan , W.T. Gerthoffer, and M. Tan, Knowledge Acquisition, Semantic Text Mining, and Security Risks in Health and Biomedical Informatics , World Journal of Biological Chemistry , 3(2), 2012  PDF
  52. Conference Papers

  53. Jintao Zhang and Jun Huan , Multi-target protein-chemical interaction prediction using task-regularized and boosted multi-task learning , ACM Conference on Bioinformatics, Computational Biology and Biomedicine (ACM BCB'12) , Orlando, FL, October 2012, acceptance rate 33/159=20%  PDF
  54. Jintao Zhang and Jun Huan , Drug-induced QT Prolongation Prediction Using Co-regularized Multi-view Learning , The IEEE International Conference on Bioinformatics and Biomedicine (BIBM'12) , Philadelphia, Pennsylvania, October 2012, acceptance rate 59/299=20%  PDF
  55. Brian Quanz and Jun Huan , CoNet: Feature Generation for Multi-View Semi-Supervised Learning with Partially Observed Views , the 21st ACM Conference on Information and Knowledge Management (CIKM'12) , Maui, Hawaii, October 2012, acceptance rate 146/1088=13%  PDF
  56. Yi Jia, Wenrong Zeng and Jun Huan , Non-stationary bayesian networks based on perfect simulation , the 21st ACM Conference on Information and Knowledge Management (CIKM'12) , Maui, Hawaii, October 2012, acceptance rate 146/1088=13%  PDF
  57. Jintao Zhang and Jun Huan , Inductive Multi-Task Learning with Multiple View Data , The 18th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD'12) , Beijing, China, August 2012  PDF
  58. Xin Huang, Hong Cheng, Jiong Yang, Jeffrey Xu Yu, Hongliang Fei, and Jun Huan , Semi-Supervised Clustering of Graph Objects: A Subgraph Mining Approach , The 17th International Conference on Database Systems for Advanced Applications (DASFAA'12) , Busan, South Korea, April 2012, acceptance rate 44/159=27.6%  PDF
  59. 2011

    Journal Papers & Book Chapters

  60. Jun Huan , Jake Chen, and Mohammed Zaki, Special Issue: Selected Articles from the 9th International Workshop on Data Mining in Bioinformatics (BIOKDD) , BMC Bioinformatics , Vol. 12, Suppl 12, 2011  PDF
  61. Jintao Zhang, Gerald Lushington and Jun Huan , The BioAssay Network and Its Implications to Future Therapeutic Discovery , BMC Bioinformatics , Vol. 12, Suppl 5:S1, 2011  PDF
  62. Yi Jia, Jintao Zhang, and Jun Huan , An efficient graph-mining method for complicated and noisy data with real-world applications , Knowledge and Information Systems , Vol. 28, No. 4, 423-447, 2011  PDF
  63. Jintao Zhang, Gerald Lushington and Jun Huan , Characterizing the Diversity and Biological Relevance of the MLPCN Assay Manifold and Screening Set , Journal of Chemical Information and Modeling , ACS Publication, 2011  PDF
  64. Xiaohong Wang, Jun Huan , Aaron Smalter, and Gerald Lushington, G-hash: Towards Fast Kernel-based Similarity Search in Large Graph Databases , Graph Data Management: Techniques and Applications , Sherif Sakr and Eric Pardede edt, IGI Global, ISBN 161350053X, 2011  PDF
  65. Fang-Xiang Wu and Jun Huan , Guest Editorial: Special Focus on Bioinformatics and Systems Biology , IEEE/ACM Transaction on Computational Biology and Bioinformatics , Vol 8, No. 2, pp. 292-293, 2011  PDF
  66. Conference Papers

  67. Hongliang Fei and Jun Huan , Structured Feature Selection and Task Relationship Inference for Multi-Task Learning , in Proceedings of the IEEE International Conference on Data Mining (ICDM'11) , Vancouver, Canada, December 2011, acceptance rate 12%, The Best Student Paper (1/101 accepted papers)  PDF
  68. Meenakshi Mishra, Brian Potetz, and Jun Huan , Bayesian Classifier for Chemical Toxicity Prediction , in Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine (BIBM'11) , Atlanta, GA, November 2011, short paper, acceptance rate 40%  PDF
  69. Hongliang Fei, Ruoyi Jiang, Yunhao Yang, Bo Luo, and Jun Huan , Content based Social Behavior Prediction: A Multi-task Learning Approach , in Proceedings of the 20th ACM Conference on Information and Knowledge Management (CIKM'11) , Glasgow, UK, October 2011, acceptance rate 35%  PDF
  70. Ruoyi Jiang, Hongliang Fei, and Jun Huan , Anomaly Localization for Network Data Streams with Graph Joint Sparse PCA , in Proceedings of the 17th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (SIGKDD'11) , San Diego, CA, August 2011, acceptance rate 125/714 = 17.5%  PDF
  71. Aaron Smalter, Jun Huan , and Gerald Lushington, Similarity Boosting for Label Noise Tolerance in Protein-Chemical Interaction Prediction , in Proceedings of the 2nd ACM Conference on Bioinformatics, Computational Biology and Biomedicine (ACM BCB'11) , Chicago, IL, August 2011, regular paper, acceptance rate 29/153 = 19%  PDF
  72. Brian Quanz, Jun Huan , and Meenakshi Mishra, Knowledge Transfer with Low-Quality Data: a Feature Extraction Issue , in Proceedings of the IEEE International Conference on Data Engineernig (ICDE'11) , Hannover, Germany, April 2011, regular paper, acceptance rate 98/494 = 19.8%  PDF
  73. 2010

    Journal Papers & Book Chapters

  74. The MicroArray Quality Control (MAQC) Consortium, The MAQC-II Project: A Comprehensive Study of Common Practices for the Development and Validation of Microarray-based Predictive Models, Nature Biotechnology, Vol. 28, No. 8, pp. 827-838, 2010  PDF
  75. Yi Jia, Jun Huan , Constructing Non-Stationary Dynamic Bayesian Networks with a Flexible Lag Choosing Mechanism , BMC Bioinformatics, Vol. 11 (Suppl 6):S27, 2010  PDF
  76. Deepak Bandyopadhyay, Jun Huan , Jinze Liu, Jan Prins, Jack Snoeyink, Wei Wang, and Alexander Tropsha, Functional Neighbors: Relationships between Non-homologous Protein Families Inferred Using Family-Specific Fingerprints , IEEE Transaction on Information Technology in Biomedicine, Vol. 14, No. 5, pp. 1137-1143, 2010  PDF
  77. Xiaohong Wang, Jun Huan , Aaron Smalter, Gerald Lushington, Application of Kernel Functions for Accurate Similarity Search in Large Chemical Databases , BMC Bioinformatics Vol. 11 (Suppl 3):S8, 2010  PDF
  78. Jintao Zhang and Jun Huan , Comparison of Chemical Descriptors for Protein-Chemical Interaction Prediction , International Journal of Computational Bioscience , Vol. 1, No. 1, pp.13-21, 2010  PDF
  79. Aaron Smalter, Jun Huan ,and Gerald Lushington, GPD: A Graph Pattern Diffusion Kernel for Accurate Graph Classification with Applications in Cheminformatics, IEEE/ACM Transactions on Computational Biology and Bioinformatics , Vol. 7, No.2, pp. 197-207, 2010  PDF
  80. Seak Fei Lei and Jun Huan , Towards Site-based Protein Functional Annotations , the International Journal of Data Mining in Bioinformatics , Vol. 4, No. 4, pp. 458-470, 2010  PDF
  81. Conference Papers

  82. Meenakshi Mishra, Hongliang Fei, and Jun Huan , Computational Prediction of Toxicity, in Proceedings of the IEEE International Conference on Bioinformatics & Biomedicine (BIBM'10) , Hong Kong, China, December 2010, pp.686-691, regular paper, acceptance rate 61/355 = 17%  PDF
  83. Jintao Zhang, Gerald Lushington, and Jun Huan , Exploratory Analysis of the BioAssay Network with Implications to Therapeutic Discovery , in Proceedings of the IEEE International Conference on Bioinformatics & Biomedicine (BIBM'10) , Hong Kong, China, December 2010, pp. 569-572, short paper  PDF
  84. Jintao Zhang and Jun Huan, Novel Biological Network Feature Discovery for In Silicon Identification of Drug Targets , in Proceedings of the 1st ACM International Health Informatics Symposium , Arlington, VA, November 2010, pp. 144-152  PDF
  85. Hongliang Fei and Jun Huan, Boosting with Structure Information in the Functional Space: an Application to Graph Classification, in Proceedings of the 16th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (SIGKDD'10) , Washington DC, July 2010, pp.643-652, acceptance rate 101/578 = 17%  PDF
  86. Ruoyi Jiang, Hongliang Fei, and Jun Huan, Anomaly Localization by Joint Sparse PCA and Its Implementation in Sensor Network, in Proceedings of the 4th International Workshop on Knowledge Discovery from Sensor Data (SensorKDD), in conjunction with the 16th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (SIGKDD'10) , Washington DC, July 2010  PDF
  87. Hongliang Fei, Brian Quanz, and Jun Huan , Regularization and Feature Selection for Networked Features , in Proceedings of the 19th ACM Conference on Information and Knowledge Management (CIKM'10) , Toronto, Canada, October 2010, pp.1893-1896, acceptance rate 296/945 = 31%  PDF
  88. 2009

    Journal Papers & Book Chapters

  89. Deepak Bandyopadhyay, Jun Huan , Jan Prins, Jack Snoeyink, Wei Wang, Alexander Tropsha, Identification of Family-Specific Residue Packing Motifs and their use for Structure-Based Protein Function Prediction, I. Method Development , Journal of Computer-Aided Molecular Design , Vol. 23, No. 11, pp. 773-784, 2009  PDF
  90. Deepak Bandyopadhyay, Jun Huan , Jan Prins, Jack Snoeyink, Wei Wang, Alexander Tropsha, Identification of Family-Specific Residue Packing Motifs and their use for Structure-Based Protein Function Prediction: II. Case Studies and Applications , Journal of Computer-Aided Molecular Design , Vol. 23, No. 11, pp. 785-797, 2009  PDF
  91. Aaron Smalter, Jun Huan , Gerald Lushington, Graph Wavelet Alignment Kernels for Drug Virtual Screening , Journal of Bioinformatics and Computational Biology , Vol. 7 (3), pp. 473-497, 2009  PDF
  92. Yi Jia, Jun Huan , Vincent Buhr, Jintao Zhang, and Leonidas N. Carayannopoulos, "Towards Comprehensive Structural Motif Mining for Better Fold Annotation in the “Twilight Zone” of Sequence Dissimilarity", BMC Bioinformatics , Vol. 10 (Suppl 1): S46, 2009   PDF
  93. Jun Huan , Frequent Subgraph Mining, in Encyclopedia of Database Systems, pp. 1170-1175 , 2009  PDF
  94. Conference Papers

  95. Aaron Smalter, Jun Huan , Gerald Lushington, Feature Selection in the Feature Tensor Product Space , in Proceedings of the 9th IEEE International Conference on Data Mining (ICDM'09) , Miami, FL, December 2009, pp. 1004-1009, short paper, acceptance rate 18%  PDF
  96. Hongliang Fei, Jun Huan, L2 Norm Regularized Feature Kernel Regression For Graph Data , in Proceedings of the  ACM 18th Conference on Information and Knowledge Management ( CIKM'09 ), Hong Kong, China, November 2009, pp.593-600, acceptance rate 123/847=15%, Best Paper Runner-up (6/123 accepted papers)  PDF
  97. Brian Quanz, Jun Huan, Large Margin Transductive Transfer Learning , in Proceedings of the   ACM 18th Conference on Information and Knowledge Management ( CIKM'09 ), Hong Kong, China, November 2009, pp. 1327-1336, acceptance rate 123/847=15%  PDF
  98. Xiaohong Wang, Jun Huan , Aaron Smalter, Gerald Lushington, Application of Kernel Functions for Accurate Similarity Search in Large Chemical Databases , in Proceedings of the IEEE International Conference on Bioinformatics & Biomedicine (BIBM'09) , Washington DC, November 2009, pp. 356-361, regular paper, acceptance rate 44/233 = 19%.  PDF
  99. Yi Jia, Jun Huan , The Analysis of Arabidopsis Thaliana Circadian Network Based on Non-stationary DBNs Approach with Flexible Time Lag Choosing Mechanism , in Proceedings of the IEEE International Conference on Bioinformatics & Biomedicine (BIBM'09) , Washington DC, November 2009, pp. 178-181, short paper, acceptance rate 81/233= 35%  PDF
  100. Brian Quanz, Hongliang Fei, Jun Huan, Joseph Evans, Victor Frost, Gary Minden, Daniel Deavours, Leon Searl, Daniel DePardo, Martin Kuehnhausen, Daniel Fokum, Matt Zeets, Angela Oguna, Anomaly Detection with Sensor Data for Distributed Security , in Proceedings of the International Workshop on Sensor Networks, in conjuctions with the 18th International Conference on Computer Communications and Networks (ICCCN 2009), 2009    PDF
  101. Brian Quanz and Jun Huan , Aligned Graph Classification with Regularized Logistic Regression , in Proceedings of the SIAM Data Mining (SDM'09) , Sparks, NV, April 2009, pp. 353-364  PDF
  102. Xiaohong Wang, Aaron Smalter, Jun Huan , and Gerald Lushington, G-Hash: Towards Fast Kernel-based Similarity Search in Large Graph Databases, in Proceedings of the 12th International Conference on Extending Database Technology (EDBT'09) , Saint-Petersburg, Russia, March 2009, pp. 472-480, acceptance rate 92/283 = 32%  PDF
  103. 2008

    Conference Papers

  104. Deepak Bandyopadhyay, Jun Huan , Jinze Liu, Jan Prins, Jack Snoeyink, Wei Wang, and Alexander Tropsha, Functional Neighbors: Relationships between Non-homologous Protein Families Inferred Using Family-Specific Fingerprints , in Proceedings of the IEEE International Conference on Bioinformatics and  Biomedicine ( BIBM'08 ), Philadelphia, PA, December 2008, pp. 199-206, acceptance rate 38/156 = 24%,  PDF
  105. Seak Fei Lei, Jun Huan , Towards Site-based Function Annotations for Protein Structures . in Proceedings of the IEEE International Conference on Bioinformatics and  Biomedicine ( BIBM'08 ), Philadelphia, PA, December 2008, pp. 193-198, acceptance rate 38/156 = 24%, ,  Appendix  PDF
  106. Aaron Smalter, Jun Huan , and Gerald Lushington. GPM: A Graph Pattern Matching Kernel with Diffusion for Chemical Compound Classification Classification . in Proceedings of the 8th IEEE International Conference on Bioinformatics and BioEngineering ( BIBE'08 ), 2008.  PDF
  107. Hongliang Fei, Jun Huan , Structure Feature Selection for Chemical Compound Classification, in Proceedings of the 8th IEEE International Conference on Bioinformatics and BioEngineering ( BIBE'08 ), 2008.  PDF
  108. Hongliang Fei, Jun Huan , Structure Feature Selection for Graph Classification, in Proceedings of the  ACM 17th Conference on Information and Knowledge Management ( CIKM ), Napa, CA, November 2008, pp. 991-1000, acceptance rate 132/772=17%,  PDF
  109. Aaron Smalter, Jun Huan , Gerald Lushington, Graph Wavelet Alignment Kernels for Drug Virtual Screening, to appear in Proceedings of the 7th Annual International Conference on Computational Systems Bioinformatics ( CSB ), Stanford, CA, July 2008, pp. 327-338, acceptance rate 30/135=22%,  PDF
  110. Aaron Smalter, Jun Huan , Gerald Lushington, Structure-based Pattern Mining For Chemical Compound Classification, in Proceedings of the 6th Asia Pacific Bioinformatics Conference ( APBC ), Kyoto, Japan, January 2008, pp. 39-48.  PDF
  111. 2007

    Conference Papers

  112. Xueyi Wang, Jun Huan , Jack Snoeyink,Wei Wang, Mining RNA Tertiary Motifs with Structure Graphs , in Proceedings of the 19th International Conference on Scientific and Statistical Database Management ( SSDBM ), Banff, Canada, July 2007, pp. 31-39  PDF
  113. Xiang Zhang, Wei Wang, Jun Huan , " On demand Phenotype Ranking through Subspace Clustering ", in Proceedings of SIAM International Conference on Data Mining (SDM) , Minneapolis, MN, April 2007, pp. 623-628  PDF
  114. David Williams, Jun Huan , Wei Wang, Graph Database Indexing Using Structured Graph Decomposition , in Proceedings of the 23rd IEEE International Conference on Data Engineering (ICDE) , Istanbul, Turkey, April 2007, pp. 976-985,  PDF
  115. 2006

    Journal Papers & Book Chapters

  116. Jun Huan , Wei Wang, and Jan Prins, Protein Local Structure Comparison: Methods and Future Directions , in Advances in Computers by Chau-Wen Tseng (eds.), Elsevier, 2006.  PDF
  117. Deepak Bandyopadhyay, Jun Huan , Jinze Liu, Jan Prins, Jack Snoeyink, Wei Wang, Alexander Tropsha, " Structure-based Function Inference Using Protein Family-specific Fingerprints ", Journal of  Protein Science , Vol. 15, Page: 1537–1543. 2006. PubMed link  PDF
  118. Conference Papers

  119. Jun Huan , "Graph Based Pattern Discovery in Protein Structures", Ph.D. Dissertation , Department of Computer Science, University of North Carolina, 2006  PDF
  120. Stephen Olivier, Jun Huan , Jinze Liu, Jan Prins, James Dinan, P Sadayappan and Chau-Wen Tseng. " UTS: An Unbalanced Tree Search Benchmark " . in Proceedings of the 19th Intl. Workshop on Languages and Compilers for Parallel Computing (LCPC 2006). New Orleans, LA, November 2-4, 2006.  PDF
  121. Jun Huan , Deepak Bandyopadhyay, Jack Snoeyink, Jan Prins, Alex Tropsha, Wei Wang, " Distance-based Identification of Spatial Motifs in Proteins Using Constrained Frequent Subgraph Mining ", in Proceedings of the IEEE Computational Systems Bioinformatics (CSB) , 2006.  PDF
  122. 2005

    Journal Papers & Book Chapters

  123. Jun Huan , Deepak Bandyopadhyay, Wei Wang, Jack Snoeyink, Jan Prins, and Alexander Tropsha. " Comparing Graph Representations of Protein Structure for Mining Family-Specific Residue-Based Packing Motifs ", Journal of Computational Biology (JCB) ,  Vol. 12, No. 6: 657-671, 2005.  PDF
  124. Conference Papers

  125. Jun Huan , Deepak Bandyopadhyay, Jinze Liu, Jan Prins, Jack Snoeyink, Alexander Tropsha, and Wei Wang. " Rapid Determination of Local Structural Features Common to a Set of Proteins ", Intelligent Systems for Molecular Biology (ISMB) (demo) ,  2005.  PDF
  126. 2004

    Conference Papers

  127. Jun Huan , Wei Wang, Jan Prins, and Jiong Yang. " SPIN: Mining Maximal Frequent Subgraphs from Graph Databases ", in Proceedings of the 10th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining , Seattle, WA, August 2004, pp. 581-586 , Tech Report  PDF
  128. Jun Huan , Wei Wang, Deepak Bandyopadhyay, Jack Snoeyink, Jan Prins, and Alexander Tropsha. " Mining Family Specific Residue Packing Patterns from Protein Structure Graphs ", in Proceedings of the 8th Annual International Conference on Research in Computational Molecular Biology (RECOMB) , San Diego, CA, March 2004, pp. 308-315. , Presentation  PDF
  129. Jun Huan , Wei Wang, Angliana Washington, Jan Prins, Ruchir Shah, and Alexander Tropsha. " Accurate Classification of Protein Structural Families using Coherent Subgraph Analysis ", in Proceedings of the Pacific Symposium on Biocomputing (PSB) , pp. 411-422, 2004.  PDF
  130. 2003

    Conference Papers

  131. Jun Huan , Wei Wang, and Jan Prins. " Efficient Mining of Frequent Subgraph in the Presence of Isomorphism ", in Proceedings of the 3rd IEEE International Conference on Data Mining (ICDM) , pp. 549-552, 2003. , Tech Report Presentation  PDF
  132. Jun Huan , Jan Prins, Wei Wang, and Todd Vision. " Reconstructing of Ancestral Gene Order After Segmental Duplication and Gene Loss ", in Proceedings of the IEEE Computer Society Bioinformatics Conference (CSB) , pp. 484-485, 2003.  PDF
  133. K. Berlin, J. Huan , M. Jacob, G. Kochhar, J. Prins, W. Pugh, P. Sadayappan, J. Spacco, C.-W. Tseng, " Evaluating the Impact of Programming Language Features on the Performance of Parallel Applications on Cluster Architectures ", in Proceedings of Languages and Compilers for Parallel Computing (LCPC) , 2003  PDF
  134. Jan Prins, Jun Huan , Bill Pugh, Chau-Wen Tseng, and P Sadayappan. " UPC Implementation of an Unbalanced Tree Search Benchmark ", in Technical Reports produced by the Department of Computer Science at the University of North Carolina, Chapel Hill , 2003.  PDF
  135. 2002 & Before

  136. Jingmei Liu, Yuan Yuan, Jun Huan & Zhiyuan Shen. " Inhibition of Breast and Brain Cancer Cell Growth by BCCIP, an Evolutionarily Conserved Nuclear Protein that Interacts with BRCA2 ", in Oncogene , Volume 20, Number 3. pp. 336-345, January 2001.  PDF
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