Refereed Journal Articles

1.     Transfer Learning across Ontologies for Phenome-Genome Association Prediction, Petegrosso, Raphael; Park, Sunho; Hwang, Tae Hyun; Kuang, RuiBioinformatics, pp. btw649, 2016

2.     Estimating KIR Haplotype Frequencies on a Cohort of 10,000 Individuals: A Comprehensive Study on Population Variations, Typing Resolutions, and Reference Haplotypes, Vierra-Green, Cynthia; Roe, David; Jayaraman, Jyothi; Trowsdale, John; Traherne, James; Kuang, Rui; Spellman, Stephen; Maiers, Martin, PloS one, 11 (10), pp. e0163973, 2016

3.     Meta-Analysis of EMT Datasets Reveals Different Types of EMT, Liang, Lining; Sun, Hao; Zhang, Wei; Zhang, Mengdan; Yang, Xiao; Kuang, Rui; Zheng, Hui. PloS one, 11 (6), pp. e0156839–e0156839, 2016

4.     Network-based Isoform Quantification with RNA-Seq Data for Cancer Transcriptome Analysis, Wei Zhang, Jae-Woong Chang, Lilong Lin, Kay Minn, Baolin Wu, Jeremy Chien, Jeongsik Yong, Hui Zheng, and Rui Kuang. PLoS Comput Biol, 2015. doi:10.1371/journal.pcbi.1004465

5.     mRNA 3'UTR shortening is a new mTORC1-activated molecular signature defining the specificity in ubiquitin-proteasome pathway, Jae-Woong Chang, Wei Zhang, Hsin-Sung Yeh, Ebbing de Jong, Semo Jun, Kwan-Hyun Kim, Sun Sik Bae, Kenneth Beckman, Tae Hyun Hwang, Kye-Seong Kim, Do-Hyung Kim, Timothy Griffin, Rui Kuang, Jeongsik Yong, Nature Communication, 6:7218, 2015

6.     Predicting and exploring network components involved in pathogenesis in the malaria parasite via novel subnetwork alignments, Hong Cai, Timothy G. Lilburn, Changjin Hong, Jianying Gu, Rui Kuang, Yufeng Wang, BMC Systems Biology, 2015 9(Suppl 4):S1

7.     Network-based Phenome-Genome Association Prediction by Bi-Random Walk, MaoQiang Xie, YingJie Xu, YaoGong Zhang, TaeHyun Hwang, Rui Kuang, Plos One, May 1, 2015

8.     TP53 Mutations, Tetraploidy, and Homologous Recombination Repair Defects in Early Stage High Grade Serous Ovarian Cancer, Chien, Jeremy; Sicotte, Hugues; Fan, Jian-Bing; Humphray, Sean; Cunningham, Julie; Kalli, Kimberly; Oberg, Ann; Hart, Steven; Li, Ying; Davila, Jaime; Baheti, Saurabh; Wang, Chen ,; Kocher, Jean-Pierre; Dietmann, Sabine.; Atkinson, Elizabeth; Asmann, Yan; Bell, Debra; Ota, Takayo; Tarabishy, Yaman; Kuang, Rui; Bibikova, Marina; Cheetham, R.; Grocock, Russell; Swisher, Elizabeth; Peden, John; Bentley, David; Kaufmann, Scott H.; Hartmann, Lynn; Shridhar, Viji; Goode, Ellen,  Nucleic Acids Research, 2015, Volume 43, Issue 14, Page. 6945-6958

9.     SubPatCNV: Approximate Subspace Pattern Mining for Mapping Copy-Number Variations, Nicholas Johnson, Huanan Zhang, Gang Fang, Vipin Kumar and Rui Kuang, BMC Bioinformatics, 201516:16

10.  Platinum-Sensitive Recurrence in Ovarian Cancer: The Role of Tumor Microenvironment, Jeremy R Chien, Rui Kuang, Charles Landen and Viji Shridhar, Front Oncol., 2013; 3: 251.

11.  A novel subnetwork alignment approach predicts new components of the cell cycle regulatory apparatus in Plasmodium falciparum, Hong Cai, Changjin Hong, Timothy G Lilburn3, Armando L Rodriguez1, Sheng Chen, Jianying Gu, Rui Kuang and Yufeng Wang, BMC Bioinformatics, 2013, 14(Suppl 12):S2.

12.  Network-based Survival Analysis Reveals Subnetwork Signatures fro Predicting Outcomes of Ovarian Cancer Treatment, Wei Zhang, Takayo Ota, Viji Shridhar, Jeremy R Chien, Baolin Wu and Rui Kuang, PLoS Computational Biology, 9(3):e1002975, 2013

13.  Large-scale Integrative Network-based analysis Identifies Common Pathways Disrupted by Copy Number Alterations across Cancers, Tae Hyun Hwang, Gowtham Atluri, Rui Kuang, Timothy Starr, Kevin AT Silverstein, Peter Haverty, Zemin Zhang, and Jinfeng Liu, BMC Genomics, 2013 14:440, 2013

14.  Co-clustering Phenome-genome for Phenotype Classification and Disease Gene Discovery, TaeHyun Hwang, Gowtham Atluri, Maoqiang Xie, Sanjoy Dey, Changjin Hong, Vipin Kumar and Rui Kuang, Nucleic Acids Research, 40(19):e146, 2012

15.  Community Engagement and Outreach as Curricular and Pedagogical Tools for Consortial Delivery of Health Informatics Curricula, Julie A. Jacko, Layne M. Johnson, Terrence J. Adam, Adel L. Ali, Daniel Chan, Rui Kuang, Andrew F. Nelson, Amy Watters, Bonnie Westra, Sally Fauchald, Sandra Potthoff and Marty Witrak, Int. J. of Information and Operations Management Education, Vol. 4, No. 3/4, pages: 284-308, 2011

16.  Proteases in Malaria Parasites - a Phylogenomic Perspective, Hong Cai, Rui Kuang, Jianying Gu and Yufeng Wang, Current Genomics, Vol. 12, No. 6, pages: 417-427, 2011

17.  Inferring Disease and Gene Set Associations with Rank Coherence in Networks, TaeHyun Hwang, Wei Zhang, MaoQiang Xie and Rui Kuang, Bioinformatics, Vol. 27, No. 19, pages: 2692-2699, 2011 

18.  Integrative Classification and Analysis of Multiple ArrayCGH Datasets with Probe Alignment, Ze Tian and Rui Kuang, Bioinformatics, Vol. 26, No. 18, pages: 2313-2320, 2010

19.  Improved Prediction of Malaria Degradomes by Supervised Learning with SVM and Profile Kernel, Rui Kuang, Gujian Ying, Hong Cai and Yufeng Wang, Genetica, Vol. 36, No. 1, pages: 189-209, 2009

20.  A Hypergraph-based Learing Algorithm for Classifying Gene Expression and ArrayCGH Data with Prior Knowledge, Ze Tian, TaeHyun Hwang and Rui Kuang, Bioinformatics, Vol. 25, No. 21, pages: 2831-2838, 2009

21.  Robust and Efficient Identification of Biomarkers by Classifying Features on Graphs, TaeHyun Hwang, Hugues Sicotte, Ze Tian, BaolinWu, Dennis Wigle, Jean-Pierre Kocher, Vipin Kumar and Rui Kuang, Bioinformatics, Vol. 24, No. 18, pages 2023-2029, 2008

22.  SVM-fold: a Tool for Discriminative Multi-class Protein Fold and Superfamily Recognition, Iain Melvin, Eugene Ie, Rui Kuang, Jason Weston, William Stafford Noble and Christina Leslie, BMC Bioinformatics, 8(Suppl 4):S2, 2007

23.  Protein Ranking by Semi-Supervised Network Propagation, JasonWeston, Rui Kuang, Christina Leslie and William Stafford Noble, BMC Bioinformatics, 7(Suppl 1):S10, 2006

24.  Identifying Remote Protein Homologs by Network Propagation, William Stafford Noble, Rui Kuang, Christina Leslie and Jason Weston, The FEBS Journal, Vol. 272, Issue 20, pages: 5119-5128, 2005

25.  Profile-based String Kernels for Remote Homology Detection and Motif Extraction, Rui Kuang, Eugene Ie, Ke Wang, Kai Wang, Mahira Siddiqi, Yoav Freund and Christina Leslie, Journal of Bioinformatics and Computational Biology, Vol. 3, No. 3, pages: 527-550, 2005

26.  Motif-based Protein Ranking by Network Propagation, Rui Kuang, Jason Weston, William Stafford Noble and Christina Leslie, Bioinformatics, Vol. 21, No. 19, pages: 3711-3718, 2005

27.  Fast String Kernels Using Inexact Matching for Protein Sequences, Christina Leslie and Rui Kuang, Journal of Machine Learning Research, Vol. 5, pages: 1435-1455, 2004

28.  Protein Backbone Angle Prediction with Machine Learning Approaches, Rui Kuang, Christina Leslie and An-Suei Yang, Bioinformatics, Vol. 20. No. 10, pages: 1612-1621, 2004


Refereed Conference Proceedings

1.     Predicting Small Group Accretion in Social Networks: A topology based incremental approach, Ankit Sharma, Rui Kuang, Jaideep Srivastava, Xiaodong Feng, Kartik Singhal, ASONAM 2015: 408-415

2.     Transfer Learning Across Cancers on DNA Copy Number Variation Analysis, Huanan Zhang, Ze Tian  and Rui Kuang, IEEE International Conference on Data Mining (ICDM), 2013. Short paper: 159/809 [19.7%]

3.     Sparse Group Selection on Fused Lasso Components for Identifying Group-specific DNA Copy Number Variations, Ze Tian, Huanan Zhang and Rui Kuang, Proc. of IEEE International Conference on Data Mining (ICDM), page 665-674, 2012 (Best Student Paper), Full paper and oral presentation: 76/756 [11%] 152 accepted

4.     Signed Network Propagation for Detecting Differential Gene Expressions and DNA Copy Number Variations, Wei Zhang, Nicholas Johnson, Baolin Wu and Rui Kuang, ACM Conference on Bioinformatics, Computational Biology and Biomedicine (ACM BCB), 2012. Acceptance rate: 64/159 [40%]

5.     Disease Gene Prioritization by Bi-Random Walk, Maoqiang XieTaeHyun Hwang and Rui Kuang, Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), pages: 292-303, 2012. Acceptance rate: 88/241 [36.5%]

6.     Global Linear Neighborhoods for Efficient Label Propagation, Ze Tian and Rui Kuang, SIAM International Conference on Data Mining (SDM), 2012. Acceptance rate: 99/363 [27%]

7.     Launching: University Partnership for Health Informatics, Julie A. Jacko, Terrence Adam, Bonnie Westra, Marty Witrak, Ron Berkeland, Andrew F. Nelson, Adel L. Ali, Layne Johnson, Rui Kuang, Kathy LaTour, Sandra Potthoff and Amy Watters, Proceedings of the ACM International Health Informatics Symposium, Arlington, VA, pages: 521-525, 2011

8.     Integrative Biomarker Discovery for Breast Cancer Metastasis from Gene Expression and Protein Interaction Data Using Error-tolerant Pattern Mining, Rohit Gupta, Smita Agrawal, Navneet Rao, Ze Tian, Rui Kuang and Vipin Kumar, International Conference on Bioinformatics and Computational Biology (BICoB), 2010

9.     Subspace Differential Coexpression Analysis: Problem Definition and a General Approach, Gang Fang, Rui Kuang, Gaurav Pandey, Michael Steinbach, Chad L. Myers and Vipin Kumar, Pacific Symposium on Biocomputing (PSB), Vol. 15, pages: 145-156, 2010. Acceptance rate: About 20%

10.  A Heterogeneous Label Propagation Algorithm for Disease Gene Discovery, TaeHyun Hwang and Rui Kuang, SIAM International Conference on Data Mining (SDM), 2010. Acceptance rate: 82/351 [23%]

11.   Learning Random-Walk Kernels for Protein Remote Homology Identification and Motif Discovery, Renqiang Min, Rui Kuang, Anthony Bonner and Zhaolei Zhang, SIAM International Conference on Data Mining (SDM), pages: 132-143, 2009. Full paper and oral presentation 57/346 [16%], 100 accepted

12.  Learning on Weighted Hypergraphs to Integrate Protein Interactions and Gene Expressions for Cancer Outcome Prediction, TaeHyun Hwang, Ze Tian, Jean-Pierre Kocher and Rui Kuang, International Conference on Data Mining (ICDM), pages: 293-302, 2008. Full paper 70/724 [10%], 144 accepted

13.  Profile-based String Kernels for Remote Homology Detection and Motif Extraction, Rui Kuang, Eugene Ie, Ke Wang, Kai Wang, Mahira Siddiqi, Yoav Freund and Christina Leslie, The Computational Systems Bioinformatics Conference (IEEE CSB), pages: 152-160, 2004. Oral Presentation 30/202 [15%], 41 accepted

14.  Fast Kernels for Inexact String Matching, Christina Leslie and Rui Kuang, Conference on Learning Theory and Kernel Workshop (COLT/KW), pages: 114-128, 2003. Oral Presentation 26/92 [28%], 49 accepted

Books or Monographs

1.     Inexact Matching String Kernels for Protein Classification. Christina Leslie, Rui Kuang and Eleazar Eskin. Kernel Methods in Computational Biology. B. Schoelkopf, K. Tsuda and J.-P. Vert, ed. MIT Press, 2004

Referred Workshop Papers

1.     Network Propagation Models for Gene Selection, Wei Zhang, Baryun Hwang, Baolin Wu and Rui Kuang, Proc. of IEEE International Workshop on Genomic Signal Processing and Statistics (GENSIPS), 2010

2.     Partial Profile Alignment Kernels fro Protein Classification, Thanh Ngo and Rui Kuang, Proc. of IEEE International Workshop on Genomic Signal Processing and Statistics (GENSIPS), 2009

3.     A Hypergraph-based Learing Algorithm for Classifying ArrayCGH Data with Spatial Prior, Ze Tian, TaeHyun Hwang and Rui Kuang, Proc. of IEEE International Workshop on Genomic Signal Processing and Statistics (GENSIPS), 2009

Non-refereed Journal Articles, Essays, or Book Chapters

1.     A Comparative Study of Breast Cancer Microarray Gene Expression Profiles Using Label Propagation, TaeHyun Hwang and Rui Kuang, Workshop on Data Mining for Biomedical Informatics held in conjunction with SIAM International Conference on Data Mining, 2008