Publications

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Petegrosso, Raphael; Park, Sunho; Hwang, Tae Hyun; Kuang, Rui (2016): Transfer Learning across Ontologies for Phenome-Genome Association Prediction . In: Bioinformatics, pp. btw649, 2016. (Type: Journal Article | Abstract | Links | Tags: Phenome-genome Association, Semi-supervised Learning, Transfer Learning)
Xie, MaoQiang; Xu, YingJie; Zhang, YaoGong; Hwang, TaeHyun; Kuang, Rui (2015): Network-based Phenome-Genome Association Prediction by Bi-Random Walk . In: PloS one, 10 (5), pp. e0125138, 2015. (Type: Journal Article | Abstract | Links | Tags: Phenome-genome Association, Semi-supervised Learning)
Sharma, Ankit; Kuang, Rui; Srivastava, Jaideep; Feng, Xiaodong; Singhal, Kartik (2015): Predicting small group accretion in social networks: A topology based incremental approach . In: 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), pp. 408–415, IEEE 2015, ISBN: 978-1-4503-3854-7/15/08. (Type: Inproceedings | Abstract | Links | Tags: Semi-supervised Learning, Social Network)
Zhang, Wei; Johnson, Nicholas; Wu, Baolin; Kuang, Rui (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, pp. 337–344, ACM 2012. (Type: Inproceedings | Abstract | Links | Tags: DNA Copy Number Variation, Gene Expression, Semi-supervised Learning)
Hwang, TaeHyun; Atluri, Gowtham; Xie, MaoQiang; Dey, Sanjoy; Hong, Changjin; Kumar, Vipin; Kuang, Rui (2012): Co-clustering phenome--genome for phenotype classification and disease gene discovery . In: Nucleic acids research, 40 (19), pp. e146–e146, 2012. (Type: Journal Article | Abstract | Links | Tags: Co-clustering, Network-based Learning, Phenome-genome Association, Semi-supervised Learning)
Xie, Maoqiang; Hwang, Taehyun; Kuang, Rui (2012): Prioritizing disease genes by bi-random walk . In: Pacific-Asia Conference on Knowledge Discovery and Data Mining, pp. 292–303, Springer 2012. (Type: Inproceedings | Abstract | Links | Tags: Phenome-genome Association, Semi-supervised Learning)
Tian, Ze; Kuang, Rui (2012): Global Linear Neighborhoods for Efficient Label Propagation. . In: SDM, pp. 863–872, SIAM 2012, ISBN: 978-1-61197-232-0. (Type: Inproceedings | Abstract | Links | Tags: Lowrank Learning, Semi-supervised Learning)
Hwang, TaeHyun; Zhang, Wei; Xie, Maoqiang; Liu, Jinfeng; Kuang, Rui (2011): Inferring disease and gene set associations with rank coherence in networks . In: Bioinformatics, 27 (19), pp. 2692–2699, 2011. (Type: Journal Article | Abstract | Links | Tags: Phenome-genome Association, Semi-supervised Learning)
Zhang, Wei; Hwang, Baryun; Wu, Baolin; Kuang, Rui (2010): Network propagation models for gene selection . In: 2010 IEEE International Workshop on Genomic Signal Processing and Statistics (GENSIPS), IEEE, 2010, ISBN: 978-1-61284-791-7. (Type: Inproceedings | Abstract | Links | Tags: Cancer Genomics, Gene Expression, Semi-supervised Learning)
Hwang, TaeHyun; Kuang, Rui (2010): A Heterogeneous Label Propagation Algorithm for Disease Gene Discovery . In: Society for Industrial and Applied Mathematics. Proceedings of the SIAM International Conference on Data Mining, pp. 583, Society for Industrial and Applied Mathematics 2010. (Type: Inproceedings | Abstract | Links | Tags: Phenome-genome Association, Semi-supervised Learning)
Tian, Ze; Hwang, TaeHyun; Kuang, Rui (2009): A hypergraph-based learning algorithm for classifying gene expression and arrayCGH data with prior knowledge . In: Bioinformatics, 25 (21), pp. 2831–2838, 2009, ISSN: 1460-2059. (Type: Journal Article | Abstract | Links | Tags: DNA Copy Number Variation, Gene Expression, Semi-supervised Learning)
Tian, Ze; Hwang, TaeHyun; Kuang, Rui (2009): A hypergraph-based learning algorithm for classifying arraycgh data with spatial prior . In: 2009 IEEE International Workshop on Genomic Signal Processing and Statistics, pp. 1–4, IEEE IEEE, 2009, ISBN: 978-1-4244-4761-9. (Type: Inproceedings | Abstract | Links | Tags: DNA Copy Number Variation, Semi-supervised Learning)
Hwang, TaeHyun; Tian, Ze; Kuang, Rui; Kocher, Jean-Pierre (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, pp. 293–302, IEEE 2008, ISBN: 978-0-7695-3502-9. (Type: Inproceedings | Abstract | Links | Tags: Cancer Genomics, Gene Expression, Protein-Protein Interaction Network, Semi-supervised Learning)
Hwang, TaeHyun; Kuang, Rui (2008): A Comparative Study of Breast Cancer Microarray Gene Expression Profiles using Label Propagation . In: Proceedings of the Workshop on Data Mining for Biomedical Informatics, held in conjunction with SIAM International Conference on Data Mining (SDM), 2008. (Type: Inproceedings | Abstract | Links | Tags: Cancer Genomics, Semi-supervised Learning)
Hwang, TaeHyun; Sicotte, Hugues; Tian, Ze; Wu, Baolin; Kocher, Jean-Pierre; Wigle, Dennis; Kumar, Vipin; Kuang, Rui (2008): Robust and efficient identification of biomarkers by classifying features on graphs . In: Bioinformatics, 24 (18), pp. 2023–2029, 2008, ISBN: 1460-2059. (Type: Journal Article | Abstract | Links | Tags: Cancer Genomics, Gene Expression, Semi-supervised Learning)
Weston, Jason; Kuang, Rui; Leslie, Christina; Noble, William Stafford (2006): Protein ranking by semi-supervised network propagation . In: BMC bioinformatics, 7 (1), pp. 9, 2006. (Type: Journal Article | Abstract | Links | Tags: Protein Remote Homology Detection, Semi-supervised Learning)
Noble, William Stafford; Kuang, Rui; Leslie, Christina; Weston, Jason (2005): Idetifying remote protein homologs by network propagation . In: FEBS J, 272 (20), 2005. (Type: Journal Article | Abstract | Links | Tags: Protein Remote Homology Detection, Semi-supervised Learning)
Kuang, Rui; Weston, Jason; Noble, William Stafford; Leslie, Christina (2005): Motif-based protein ranking by network propagation . In: Bioinformatics, 21 (19), 2005. (Type: Journal Article | Abstract | Links | Tags: Motif, Protein Remote Homology Detection, Semi-supervised Learning)