DataX Lab

- Publications (with DataX's students)

  • Book Chapters (in reverse chronological order)
    1. D. Gharana, S. Suh, and M. Kang, "Gender classification using deep learning", Big Data and Visual Analytics, pp 55-69, 2017
  • Journals (in reverse chronological order)
    1. Y. Kim, J. Park, J. Hao, T. Mallavarapu, and M. Kang, "Hi-LASSO: High-dimensional LASSO", Accepted in IEEE Access
    2. J. Hao, Y. Kim, T. Kim, M. Kang, "PASNet: Pathway-Associated Sparse Deep Neural Network for Prognosis Prediction from High-throughput Data", BMC Bioinformatics, 19:510, 2018 [Source code]
    3. Y. Kim, J. Hao, Y. Gautam, T. Mersha, M. Kang, "DiffGRN: Differential gene regulatory network analysis", International Journal of Data Mining and Bioinformatics (IJDMB), Accepted, 2018
    4. N. Zarayeneh, E. Ko, J.H. Oh, S. Suh, C. Liu, J. Gao, D. Kim, and M. Kang, "Integration of Multi-omics Data for Integrative Gene Regulatory Network Inference," International Journal of Data Mining and Bioinformatics (IJDMB), Vol.18, No.3, pp.223 - 239, 2017
  • Conference Proceedings (in reverse chronological order)
    1. J. Hao, M. Masum, J.H. Oh, and M. Kang, "Gene- and Pathway-based Deep Neural Network for Multi-omics Data Integration to Predict Cancer Survival Outcomes", International Symposium on Bioinformatics Research and Applications (ISBRA), Barcelona, Spain, 3-6 June. 2019 - Regular paper (Acceptance rate: 22.6%) [Source code]
    2. S. Kosaraju, N. Z. Tsaku, P. Patel, T. Bayramoglu, G. Modgil, and M. Kang, "Table of Contents Recognition in OCR Documents Using Image-based Machine Learning," ACM Southeast Conference (ACM-SE 2019), Accepted
    3. J. Hao, Y. Kim, T. Mallavarapu, J.H. Oh, and M. Kang, "Cox-PASNet: Pathway-based Sparse Deep Neural Network for Survival Analysis", IEEE International Conference on Bioinformatics & Biomedicine (IEEE BIBM 2018), Accepted as a regular paper (Acceptance rate: 19.6%, 105 out of 534) [Source code]
    4. T. Mallavarapu, J. Hao, Y. Kim, J.H. Oh, M. Kang, "PASCL: Pathway-based Sparse Deep Clustering for Identifying Unknown Cancer Subtypes", IEEE International Conference on Bioinformatics & Biomedicine (IEEE BIBM 2018), Accepted as a regular paper (Acceptance rate: 19.6%, 105 out of 534)
    5. J. Son, E. Ko, U. Boyanapalli, D. Kim, Y. Kim, and M. Kang, "Fast and Accurate Machine Learning-based Malware Detection via RC4 Ciphertext Analysis," International Conference on Computing, Networking and Communications (ICNC 2019), Accepted - acceptance rate 28%
    6. M. Masum, S. Kosaraju, T. Bayramoglu, G. Modgil, and M. Kang, "AUTOMATIC KNOWLEDGE EXTRACTION FROM OCR DOCUMENTS USING HIERARCHICAL DOCUMENTS ANALYSIS," ACM Research in Adaptive and Convergent Systems (ACM RACS 2018), Accepted
    7. T. Mallavarapu, Y. Kim, J.H. Oh, and M. Kang, "R-PathCluster: Identifying Cancer Subtype of Glioblastoma Multiforme Using Pathway-Based Restricted Boltzmann Machine," Proceedings of IEEE International Conference on Bioinformatics & Biomedicine (IEEE BIBM 2017), International Workshop on Deep Learning in Bioinformatics, Biomedicine, and Healthcare Informatics, pp. 1183-1188, 2017
    8. E. Ko, M. Kang, H. Chang, and D. Kim, "Graph-theory Based Simplification Techniques for Efficient Biological Network Analysis," Proceedings of Big Data Security, A IEEE BigDataService 2017 Workshop, pp. 277-280, 2017
    9. N. Zarayeneh, J. H. Oh, D. Kim, C. Liu, J. Gao, S. C. Suh, and M. Kang, "Integrative Gene Regulatory Network Inference Using Multi-omics Data," Proceedings of IEEE International Conference on Bioinformatics & Biomedicine (IEEE BIBM 2016), pp. 1336-1340, 2016
corresponding author