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Publications

• Ze Tian, TaeHyun Hwang and Rui Kuang. A Hypergraph-based Learning Algorithm for Classifying Gene Expression and ArrayCGH Data with Prior Knowledge, [Paper] [Download] Bioinformatics, In Press, 2009

• Rui Kuang, Jianying Gu, Hong Cai and Yufeng Wang. Improved Prediction of Malaria Degradomes by Supervised Learning with SVM and Profile Kernel, [Paper] Genetica 36(1):189-209, 2009

• Renqiang Min, Rui Kuang, Anthony Bonner and Zhaolei Zhang. Learning Random-Walk Kernels for Protein Remote Homology Identification and Motif Discovery, [Paper] Proc. of SIAM International Conference on Data Mining (SDM), 2009

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

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

• TaeHyun Hwang, Ze Tian, Jean-Pierre Kocher, and Rui Kuang. Learning on Weighted Hypergraphs to Integrate Protein Interactions and Gene Expressions for Cancer Outcome Prediction, [Paper] [Download]  Proc. of Eighth IEEE International Conference on Data Mining (ICDM), pages 293-302, 2008

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

• TaeHyun Hwang, Hugues Sicotte, Dennis Wigle, Jean-Pierre Kocher, Vipin Kumar and Rui Kuang. Identifying Clinical and Genetic Markers of Human Disease by Classifying Features on Graphs, [Paper] Technical Report UMN-CS-07-021, Sept. 2007

• Iain Melvin, Eugene Ie, Rui Kuang, Jason Weston, William Stafford Noble and Christina Leslie, SVM-fold: a tool for discriminative multi-class protein fold and superfamily recognition [Paper], BMC Bioinformatics 2007, 8 (Suppl 4) : S2

• Rui Kuang, Inferring Protein Structure with Discriminative Learning and Network Diffusion [Manuscript], Ph.D. Thesis (Columbia University), 2006 

• Jason Weston, Rui Kuang, Christina Leslie and William Stafford Noble, Protein Ranking by Semi-Supervised Network Propagation[Paper], BMC Bioinformatics 2006, 7 (Suppl 1) : S10

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

• Rui Kuang ,Eugene Ie, Ke Wang, Kai Wang,Mahira Siddiqi, Yoav Freund and Christina Leslie, Profile-based String Kernels for Remote Homology Detection and Motif Extraction[Paper ][Download], Journal of Bioinformatics and Computational Biology Vol. 3, No. 3 527-550, 2005 (Journal version of CSB 2004 paper)

• William Stafford Noble, Rui Kuang , Christina Leslie and Jason Weston, Identifying Remote Protein Homologs by Network Propagation [Paper], The FEBS Journal. 272(20):5119-5128, 2005

• Rui Kuang ,Eugene Ie, Ke Wang, Kai Wang,Mahira Siddiqi, Yoav Freund and Christina Leslie, Profile-based String Kernels for Remote Homology Detection and Motif Extraction [Paper][Download] [Slides], Proc. of the Computational Systems Bioinformatics Conference (IEEE CSB), 2004

• Christina Leslie and Rui Kuang, Fast String Kernels Using Inexact Matching for Protein Sequences [Paper] [Download], Journal of Machine Learning Research Vol. 5, pages 1435--1455, 2004 (Journal version of COLT/KW 2003 paper)

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

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

• Christina Leslie and Rui Kuang, Fast Kernels for Inexact String Matching [Paper][Download], Proc. of Conference on Learning Theory and Kernel Workshop (COLT/KW), 2003