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Clustering on Sparse Data in Non-overlapping Feature Space with Applications to Cancer Subtyping.

T. Kang, K. Zarringhalam, M. Kuijjer, P. Chen, J. Quackenbush, and W. Ding. ICDM, page 1079-1084. IEEE Computer Society, (2018)

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A biological network-based regularized artificial neural network model for robust phenotype prediction from gene expression data.T. Kang, W. Ding, L. Zhang, D. Ziemek, and K. Zarringhalam. BMC Bioinformatics, 18 (1): 565:1-565:11 (2017)Interpreting transcriptional changes using causal graphs: new methods and their practical utility on public networks.C. Fakhry, P. Choudhary, A. Gutteridge, B. Sidders, P. Chen, D. Ziemek, and K. Zarringhalam. BMC Bioinformatics, (2016)Sequential adaptive compressed sampling via Huffman codesA. Aldroubi, H. Wang, and K. Zarringhalam. CoRR, (2008)A Free Energy Based Approach for Distance Metric Learning.S. Inaba, C. Fakhry, R. Kulkarni, and K. Zarringhalam. KDD, page 5-13. ACM, (2019)Robust clinical outcome prediction based on Bayesian analysis of transcriptional profiles and prior causal networks.K. Zarringhalam, A. Enayetallah, P. Reddy, and D. Ziemek. Bioinformatics, 30 (12): 69-77 (2014)Biomedical relation extraction using stochastic difference equations.C. Fakhry, K. Zarringhalam, and P. Chen. HPEC, page 1-6. IEEE, (2015)Molecular causes of transcriptional response: a Bayesian prior knowledge approach.K. Zarringhalam, A. Enayetallah, A. Gutteridge, B. Sidders, and D. Ziemek. Bioinformatics, 29 (24): 3167-3173 (2013)Clustering on Sparse Data in Non-overlapping Feature Space with Applications to Cancer Subtyping.T. Kang, K. Zarringhalam, M. Kuijjer, P. Chen, J. Quackenbush, and W. Ding. ICDM, page 1079-1084. IEEE Computer Society, (2018)

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Clustering on Sparse Data in Non-overlapping Feature Space with Applications to Cancer Subtyping.

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copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Clustering on Sparse Data in Non-overlapping Feature Space with Applications to Cancer Subtyping.

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Clustering on Sparse Data in Non-overlapping Feature Space with Applications to Cancer Subtyping.