Selected Publications

    2016

    Journal Papers & Book Chapters

  1. 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
  2. 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
  3. 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
  4. 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
  5. 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
  6. Conference Papers

  7. 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%.
  8. 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
  9. Chao Lan, Yujie Deng, Jun Huan , A Provably Correct Disagreement based Active Matrix Completion Method , the International Joint Conference on Neural Networks , Vancouver, Canada, July 2016
  10. 2015

    Journal Papers & Book Chapters

  11. 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
  12. Conference Papers

  13. 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%
  14. 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%
  15. 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%
  16. 2014

    Journal Papers & Book Chapters

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

  19. 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%
  20. 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%
  21. 2013

    Journal Papers & Book Chapters

  22. Said Bleik, Meenakshi Mishra, Jun Huan , and Min Song, Text Categorization of Biomedical Data Sets using Graph Kernels and a Controlled Vocabulary , IEEE/ACM Transactions on Computational Biology and Bioinformatics , Accepted, 2013
  23. 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
  24. Jintao Zhang, Jun Huan , Predicting Drug-Induced QT Prolongation Effects Using Multi-View Learning , IEEE Transactions on NanoBioscience , Accepted, 2013
  25. 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
  26. Conference Papers

  27. 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
  28. 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
  29. 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
  30. 2012

    Journal Papers & Book Chapters

  31. 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)
  32. 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
  33. Meenakshi Mishra, Hongliang Fei, and Jun Huan , Computational Prediction of Toxicity , Int. J. of Data Mining and Bioinformatics , 2012
  34. 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
  35. Conference Papers

  36. 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%
  37. 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%
  38. 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%
  39. Jia Yi, 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%
  40. 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
  41. 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%
  42. 2011

    Journal Papers & Book Chapters

  43. 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
  44. 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
  45. 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
  46. 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
  47. 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
  48. 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
  49. Conference Papers

  50. 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)
  51. 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%
  52. 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%
  53. 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%
  54. 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%
  55. 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%
  56. 2010

    Journal Papers & Book Chapters

  57. 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
  58. Yi Jia, Jun Huan ,"Constructing Non-Stationary Dynamic Bayesian Networks with a Flexible Lag Choosing Mechanism", BMC Bioinformatics, Vol. 11 (Suppl 6):S27, 2010
  59. 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
  60. 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
  61. 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
  62. 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
  63. 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
  64. Conference Papers

  65. 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%
  66. 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
  67. 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
  68. 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
  69. 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
  70. 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%
  71. 2009

    Journal Papers & Book Chapters

  72. 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
  73. 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
  74. 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
  75. 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
  76. Jun Huan , Frequent Subgraph Mining, in Encyclopedia of Database Systems, pp. 1170-1175 , 2009
  77. Conference Papers

  78. 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%
  79. 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)
  80. 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%
  81. 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%.
  82. 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%
  83. 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  
  84. Brian Quanz and Jun Huan , Aligned Graph Classification with Laplacian Regularized Logistic Regression , in Proceedings of the SIAM Data Mining (SDM'09) , Sparks, NV, April 2009, pp. 353-364
  85. 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%
  86. 2008

    Conference Papers

  87. 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
  88. 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%, PDF Appendix
  89. Aaron Smalter, Jun Huan , and Gerald Lushington. A Graph Pattern Diffusion Kernel for Chemical Compound Classification . in Proceedings of the 8th IEEE International Conference on Bioinformatics and BioEngineering ( BIBE'08 ), 2008.
  90. 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.
  91. 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
  92. 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
  93. 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
  94. 2007

    Conference Papers

  95. 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
  96. 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
  97. 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
  98. 2006

    Journal Papers & Book Chapters

  99. 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.
  100. 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
  101. Conference Papers

  102. Jun Huan , "Graph Based Pattern Discovery in Protein Structures", Ph.D. Dissertation , Department of Computer Science, University of North Carolina, 2006
  103. 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
  104. 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
  105. 2005

    Journal Papers & Book Chapters

  106. 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
  107. Conference Papers

  108. 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
  109. 2004

    Conference Papers

  110. 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 PDF , Tech Report
  111. 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. PDF , Presentation
  112. 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
  113. 2003

    Conference Papers

  114. 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. PDF , Tech Report Presentation
  115. 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
  116. 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
  117. 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
  118. 2002 & Before

  119. 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
  120. Mark G. D'Souza, Jun Huan , Samantha Sutton, Margie Romine, and Natalia Maltsev, " PUMA2 -- An Environment for Comparative Analysis of Metabolic Subsystems and Automated Reconstruction of Metabolism of Microbial Consortia and Individual Organisms from Sequence Data " Technical Memorandum ANL/MCS-TM-240 , December 1999.  Link