Cancer Genomics

Zhang, Wei, Jeremy Chien, Jeongsik Yong, and Rui Kuang. 2017. “Network-Based Machine Learning and Graph Theory Algorithms for Precision Oncology”. NPJ Precision Oncology 1. Nature Publishing Group UK London: 25.

Zhang, Wei, Jae-Woong Chang, Lilong Lin, Kay Minn, Baolin Wu, Jeremy Chien, Jeongsik Yong, Hui Zheng, and Rui Kuang. 2015. “Network-Based Isoform Quantification With RNA-Seq Data for Cancer Transcriptome Analysis”. PLoS Computational Biology 11. Public Library of Science San Francisco, CA USA: e1004465.

Johnson, Nicholas, Huanan Zhang, Gang Fang, Vipin Kumar, and Rui Kuang. 2015. “SubPatCNV: Approximate Subspace Pattern Mining for Mapping Copy-Number Variations”. BMC Bioinformatics 16. Springer: 1-12.

Chien, Jeremy, Hugues Sicotte, Jian-Bing Fan, Sean Humphray, Julie M Cunningham, Kimberly R Kalli, Ann L Oberg, et al. 2015. “TP53 Mutations, Tetraploidy and Homologous Recombination Repair Defects in Early Stage High-Grade Serous Ovarian Cancer”. Nucleic Acids Research 43. Oxford University Press: 6945-58.

Chien, Jeremy, Rui Kuang, Charles Landen, and Viji Shridhar. 2013. “Platinum-Sensitive Recurrence in Ovarian Cancer: The Role of Tumor Microenvironment”. Frontiers in Oncology 3. Frontiers Media SA: 251.

Hwang, Tae Hyun, Gowtham Atluri, Rui Kuang, Vipin Kumar, Timothy Starr, Kevin AT Silverstein, Peter M Haverty, Zemin Zhang, and Jinfeng Liu. 2013. “Large-Scale Integrative Network-Based Analysis Identifies Common Pathways Disrupted by Copy Number Alterations across Cancers”. BMC Genomics 14. Springer: 1-13.

Zhang, Huanan, Ze Tian, and Rui Kuang. 2013. “Transfer Learning across Cancers on DNA Copy Number Variation Analysis”. In 2013 IEEE 13th International Conference on Data Mining, 1283-88. IEEE.

Zhang, Wei, Takayo Ota, Viji Shridhar, Jeremy Chien, Baolin Wu, and Rui Kuang. 2013. “Network-Based Survival Analysis Reveals Subnetwork Signatures for Predicting Outcomes of Ovarian Cancer Treatment”. PLoS Computational Biology 9. Public Library of Science San Francisco, USA: e1002975.

Tian, Ze, Huanan Zhang, and Rui Kuang. 2012. “Sparse Group Selection on Fused Lasso Components for Identifying Group-Specific DNA Copy Number Variations”. In 2012 IEEE 12th International Conference on Data Mining, 665-74. IEEE.

Zhang, Wei, Nicholas Johnson, Baolin Wu, and Rui Kuang. 2012. “Signed Network Propagation for Detecting Differential Gene Expressions and DNA Copy Number Variations”. In Proceedings of the ACM Conference on Bioinformatics, Computational Biology and Biomedicine, 337-44.

Johnson, Nicholas, Gang Fang, and Rui Kuang. 2012. “Approximate Subspace Pattern Mining for Mapping Copy-Number Variations”. In Proceedings of the ACM Conference on Bioinformatics, Computational Biology and Biomedicine, 616-16.

Tian, Ze, and Rui Kuang. 2010. “Integrative Classification and Analysis of Multiple ArrayCGH Datasets With Probe Alignment”. Bioinformatics 26. Oxford University Press: 2313-20.

Zhang, Wei, Baryun Hwang, Baolin Wu, and Rui Kuang. 2010. “Network Propagation Models for Gene Selection”. In 2010 IEEE International Workshop on Genomic Signal Processing and Statistics (GENSIPS), 1-4. IEEE.

Tian, Ze, Taehyun Hwang, and Rui Kuang. 2009. “A Hypergraph-Based Learning Algorithm for Classifying Gene Expression and ArrayCGH Data With Prior Knowledge”. Bioinformatics 25. Oxford University Press: 2831-38.

Tian, Ze, Taehyun Hwang, and Rui Kuang. 2009. “A Hypergraph-Based Learning Algorithm for Classifying Arraycgh Data With Spatial Prior”. In 2009 IEEE International Workshop on Genomic Signal Processing and Statistics, 1-4. IEEE.

Hwang, Taehyun, Ze Tian, Rui Kuangy, and Jean-Pierre Kocher. 2008. “Learning on Weighted Hypergraphs to Integrate Protein Interactions and Gene Expressions for Cancer Outcome Prediction”. In 2008 Eighth IEEE International Conference on Data Mining, 293-302. IEEE.

Hwang, Taehyun, Hugues Sicotte, Ze Tian, Baolin Wu, Jean-Pierre Kocher, Dennis A Wigle, Vipin Kumar, and Rui Kuang. 2008. “Robust and Efficient Identification of Biomarkers by Classifying Features on Graphs”. Bioinformatics 24. Oxford University Press: 2023-29.