Publications

- Underline indicates myself and students in DataX.
- † indicates corresponding author.
- [E]: editorial; [B]: book chapter; [J]: journal; [C]: conference; [P] Preprint;
    In preparation or Under review
    1. S. Parsa, B. Baek, E. Ko, S. Kosaraju†, and M. Kang†, "PINT: Pathway-pathway interactions for predicting interpretable clinical outcomes from gene expression", Under review
    2. E. Ko, S. Kosaraju, E. López, R. Topol, A. Mangla, J. Shen, and M. Kang†, "Explainable Machine Learning to Identify Risk Factors for Adverse COVID-19 Healthcare Outcomes by Race/Ethnicity in Southern Nevada", In preparation
    2026
    1. [P] S. Lee, G. Wang, K. Kang, J. Chen†, and M. Kang†, "Multi-modal Graph Integration for Biologically Interpretable Domain Identification Using Spatial Transcriptomics", BioRXiv, 2026
    2. [J] M. Kang†, E. Jang, T. Mersha†, "Intra- and Inter-multi-omics Interaction Analysis Using Deep Learning", Bioinformatics Advances, 2026
    3. [C] E. Jang, E. Ko, and M. Kang†, "Inference of Disease-Associated Pathway Interaction Networks using Graph Neural Networks", Accepted in The 17th ACM BCB 2026 (full paper, acceptance rate: 19.9%), 2026
    4. [C] J. Suhyeong, L. Dumontet, S.R. Han, T.J. Oh and M. Kang†, "IDF-EC: Interpretable Dynamic Feature–Logit Fusion for Enzyme Commission Number Prediction", Accepted in The 17th ACM BCB 2026 (short paper), 2026
    5. [C] B. Baek, E. Jang, Y. Kim, and M. Kang†, "Knowledge-Guided Learning with Curated Prior Genetic Biomarkers for Robust Model Interpretation", Accepted in The 25th European Conference on Computational Biology (ECCB 2026) (Acceptance rate: 19.64%), 2026
    6. [C] S. Parsa, S. Kosaraju, E. Ko, B. Baek, T. Mersha, and M. Kang†, "PIMO: Pathway-based Interpretable Multi-Omics interactions for multi-omics integration", Accepted in Intelligent Systems for Molecular Biology (ISMB) (Acceptance rate: 13%), 2026
    7. [C] E. Ko, S. Parsa, S. Kosaraju, T. Mersha†, M. Kang†, "Fairness-aware Supervised Hierarchical Contrastive Semantic Learning for Sexual Dimorphism Analysis", Accepted in Intelligent Systems for Molecular Biology (ISMB) (Acceptance rate: 13%), 2026
    8. [J] W. Lee*, L. Dumontet*, K. Jung, H. Lee, T. Oh†, M. Kang†, "Plastic hydrolytic enzyme classification using explainable deep learning", Accepted in Applied and Environmental Microbiology (IF: 3.7), 2026
    9. [J] L. Suh*, E. Ko*, B. Baek, J. Yoo, S.W. Lee, J. Shen, R. Lee†, M. Kang†, "Examining Ethnic and Racial Variations in Opioid-related Hospitalizations Using Western U.S. Electronic Health Records", Journal of Racial and Ethnic Health Disparities, 2026
    10. [J] K. Kim*, A. Yaganapu*, S. Kosaraju, A. Bhatt, Y. Luo, S. Parsa, J. Park, H. Lee, J.H. Lee, T. Oh†, M. Kang†, "Prediction of bacterial Cytochrome P450-compound interactions based on positive-unlabeled deep learning", Bioinformatics, 2026
    11. [J] L. Dumontet*, S. Han*, T. Oh†, M. Kang†, "Trustworthy prediction of enzyme commission numbers using a hierarchical interpretable transformer", Nature Communications (IF: 15.7), 2026
    12. [J] B. Baek, J. Jo, M. Kang†, Y. Kim†, "Stochastic LASSO: enhanced high-dimensional LASSO for high-throughput genomic data", Scientific Reports, 2026
    13. [J] L. Dumontet, S. Han, A. Prouvost, J. Lee, T. Oh†, M. Kang†, "Interpretable Kolmogorov-Arnold Networks for Enzyme Commission Number Prediction", npj Artificial intelligence, 2026
    14. [J] Y. Zhou, J. Tian, M. Kang, and K. Kang†, "Echo-SMADS: A Hierarchical Planning Model for Predicting Ejection Fraction Using Echocardiography", Computer Methods and Programs in Biomedicine, 2026
    2025
    1. [J] S. Kosaraju, D. H. Song, H. J. An, Y. Choi, J. Han, J. W. Yang†, M. Kang†, "ALK-expression screening using H&E-stained histopathological images via evidential deep learning", npj Digital Medicine (IF: 15.1, 2nd ranked in Medical Informatics by Google scholar metrics), 2025
    2. [J] C. Lee*, A. Yaganapu*, A, Singam, S. Fikru, R. Rahmani, J. Zheng, M. Kang†, and S. Park†, "Artificial intelligence in cellular senescence research: a narrative review", Aging Advances, 2025 (* indicates the co-first authors)
    3. [C] S. Lee, K. Kang, J. Kim, and M. Kang†, "Explainable integrative bipartite graph convolutional neural network for predicting ejection fraction in echocardiography", The 28th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2025), 2025
    4. [J] S. Yang, J. Choi, S.H. Kim, Y. Kuk, K. Park, M. Kang, S. Byun†, J.Y. Joo†, "Towards understanding cancer dormancy over strategic hitching up mechanisms to technologies", Molecular Cancer (IF: 27.7), 2025
    5. [J] S. Kim, S. Yang, J. Jung, J. Choi, M. Kang, J.Y. Joo†, "Psychedelic Drugs in Mental Disorders: Current Clinical Scope and Deep Learning-Based Advanced Perspectives", Advanced Science (IF: 15.1), 2025
    6. [J] Y. Kim, J. Shen, J. Reeves, I. Choe, M. Kang, D. Byun, I. Ioanitoaia-Chaudhry, M. Teresa, M. Tabrizi, I. Kwak, and J. Yoo, "Comparative Effectiveness of Telehealth Versus In-Person Primary Care for the Adults Living with Intellectual Disabilities and Obesity: Insights of a Provider Shortage State in the United States". TELEMEDICINE and e-HEALTH, 2025
    7. [J] P. Reed, Y. Kim, J. Shen, S. Kosaraju, M. Kang, J. Carson, I. Chaudhry, S. Kim, C. Jeong, Y. Hwang, J. Yoo, "Race-Specific Impact of Telehealth Advance Care Planning on Cost of Dementia: A Cost Prediction Study". International Journal of Environmental Research and Public Health, 22(9), 1399, 2025
    2024
    1. [J] E. Ko, Y. Kim, F. Shokoohi, T. Mersha†, M. Kang†, "SPIN: Sex-specific and Pathway-based Interpretable Neural Network for Sexual Dimorphism Analysis", Briefings in Bioinformatics (IF: 9.5), 2024
    2. [J] S. Yang, S.H. Kim, M. Kang, J. Joo†, "Molecular insights into regulatory RNAs in the cellular machinery", Experimental & Molecular Medicine (IF: 9.5), 2024
    3. [J] J. Soh, Y. Kim, J. Shen, M. Kang, S. Chaudhry, T. Chung, S. Kim, Y. Hwang, D. Lim, A. Khattak, L. Frimer, J. Joo†, "Trends of emergency department visits for cannabinoid hyperemesis syndrome in Nevada: An interrupted time series analysis", PLOS One, 2024
    2023
    1. [J] A. Yaganapu, M. Kang†, "Multi-layered Self-attention Mechanism for Weakly Supervised Semantic Segmentation", Computer Vision and Image Understanding (IF: 4.5), 2023
    2. [J] S. Han*, M. Park*, S. Kosaraju, J. Lee*, J. H. Lee, T. Oh†, M. Kang†, "Evidential deep learning for trustworthy prediction of enzyme commission number", Briefings in Bioinformatics (IF: 9.5) (* co-advising students at Sun Moon University)
    3. [J] S. Yang, S.H. Kim, M. Kang, J. Joo†, "Harnessing deep learning into hidden mutations of neurological disorders for therapeutic challenges", Archives of Pharmacal Research (IF: 4.946), 2023
    4. [J] J. Yoo, H.T. Kang, I. Choe, L. Kim, D. Han, J. Shen, Y. Kim, P. Reed, I. loantioaia-Chaudhry, M. T. Chong, M. Kang, J. Reeves, M. Tabrizi, "Racial and Ethnic Disparity in 4Ms among Older Adults Among Telehealth Users as Primary Care". Gerontol Geriatr Med. 2023
    5. [J] J. Yoo, P. S. Reed, J. Shen, J. Carson, M. Kang, J. Reeves, Y. Kim, I. Choe, P. Kim, L. Kim, H. Kang, and M. Tabrizi "Impact of Advance Care Planning on the Hospitalization-Associated Utilization and Cost of Patients with Alzheimer’s Disease-Related Disorders Receiving Primary Care via Telehealth in a Provider Shortage Area: A Quantitative Pre-Study". Int. J. Environ. Res. Public Health. 2023
    2022
    1. [J] S. Kosaraju, J. Park, H. Lee, J. W. Yang† and M. Kang†, "Deep learning-based framework for slide-based histopathological image analysis", Scientific Reports (IF: 4.996), 2022
    2. [J] K. Lim, S. Yang, S. Kim, E. Ko, M. Kang, J. Joo†, "Cryptic mutations of PLC family members in brain disorders: recent discoveries and a deep learning-based approach", Brain (IF: 15.255), 2022
    3. [J] S. Lee, B. Werner, D. Nguyen, C. Wang, M. Kang, N. Ayutyanont, S. Lee. "Opioid Utility and Hospital Outcomes among Inpatients admitted with Osteoarthritis and Spine Disorders". American Journal of Physical Medicine & Rehabilitation. 2022
    4. [J] H. Lee, M. Kang, D. Kim, D. Seo and Y. Li†, "Epidemic Vulnerability Index for Effective Vaccine Distribution against Pandemic", IEEE/ACM Transactions on Computational Biology and Bioinformatics (IEEE TCBB), 2022
    5. [J] J. Jo, S. Jung, J. Park, Y. Kim, and M. Kang†, "Hi-LASSO: High-performance python and apache spark packages for feature selection with high-dimensional data", PLOS ONE (IF: 3.752), 2022
    6. [E] M. Kang and J. Oh†, "Deep Learning and Machine Learning in Bioinformatics", International Journal of Molecular Sciences (IJMS), 2022
    7. [C] M. Jeong, M. Kang and Y. Jung, "Impact of Bridge Construction on County Population in Georgia", The 9th International Conference on Construction Engineering and Project Management (ICCEPM), Las Vegas, 2022
    2021
    1. [J] M. Kang†, E. Ko, T. Mersha†, "A Roadmap for Multi-Omics Data Integration using Deep Learning", Briefings in Bioinformatics (IF: 11.62), 2021
    2. [C] Y. Jung, M. Kang, M. Jeong, J. Ahn "Network and Cluster Analysis on Bridge Inspection Reports Using Text Mining Algorithms", ASCE CRC, 2022
    3. [C] H. Lee, M. Kang, Y. Li, D. Seo, D. Kim, "Epidemic Vulnerability Index for Effective Vaccine Distribution against Pandemic", ISBRA, 2022
    4. [J] S.K. Kim, X. Liu, J. Park, D. Um, G. Kilaru, C.-M. Chiang, M. Kang, K. Huber, K. Kang†, T.K. Kim†, "Functional coordination of BET family proteins underlies altered transcription associated with memory impairment in fragile X syndrome", Science Advances (IF: 13.116), 2021
    5. [C] J. H. Oh, W. Choi, E. Ko, M. Kang†, A. Tannenbaum, and J. O. Deasy†, "PathCNN: Interpretable convolutional neural networks for survival prediction and pathway analysis applied to glioblastoma", International Society for Computational Biology (ISMB), Published in Bioinformatics, 2021
    6. [J] S. Kim, S. Yang, K. Lim, E. Ko, H. Jang, M. Kang, P. Suh, and J. Joo†, "Prediction of Alzheimer’s disease-specific phospholipase c gamma-1 SNV by deep learning-based approach for high-throughput screening", Proceedings of the National Academy of Sciences of the United States of America (PNAS) (IF: 9.412), 2021
    7. [J] S. Zhang, Z. Zhu†, and M. Kang, "PGNets: planet mass prediction using convolutional neural networks for radio continuum observations of protoplanetary discs", Monthly Notices of the Royal Astronomical Society (MNRAS) (IF: 5.356), 510(3), 2021
    2020
    1. [J] W. Stone, D. Kim, V. Youdom Kemmoe, M. Kang, and J. Son†, "Rethinking the Weakness of Stream Ciphers and Its Application to Encrypted Malware Detection", IEEE Access, vol. 8, pp. 191602-191616, 2020
    2. [E] Young-Rae Cho and M. Kang†, "Interpretable machine learning in bioinformatics", Methods, 2020
    3. [J] S. Kosaraju, J. Hao, H. Koh†, and M. Kang†, "Deep-Hipo: Multi-scale Receptive Field Deep Learning for Histopathological Image Analysis", Methods, 2020 - IF: 3.782
    4. [C] J. Hao*, S. Kosaraju*, N. Tsaku, D. H. Song, and M. Kang†, "PAGE-Net: Interpretable and Integrative Deep Learning for Survival Analysis Using Histopathological Images and Genomic Data", Pacific Symposium on Biocomputing (PSB), 2020 (* indicates the co-first authors)
    5. [B] M. Kang and J. Gao (2020) Integration of Multi-omics Data for Expression Quantitative Trait Loci (eQTL) Analysis and eQTL Epistasis. In: Shi X. (eds) eQTL Analysis. Methods in Molecular Biology, vol 2082. Humana, New York, NY
    2019
    1. [J] J. Hao, Y. Kim, T. Mallavarapu, J.H. Oh, and M. Kang†, "Interpretable deep neural network for cancer survival analysis by integrating genomic and clinical data", BMC Medical Genomics 12, 189 (2019) - IF: 3.062 (5-years)
    2. [C] M. Kang, A. Biswas, D. Kim, and J. Gao, "Semi-supervised Discriminative Transfer Learning in Cross-language Text Classification," International Conference on Machine Learning and Applications (IEEE ICMLA 2019), 2019
    3. [C] N. Tsaku, S. Kosaraju, T. Aqila, M. Masum, D.H. Song, A. Monda, and M. Kang†, "Texture-based Deep Learning for Effective Histopathological Cancer Image Classification", IEEE International Conference on Bioinformatics & Biomedicine (IEEE BIBM 2019), Accepted as a short paper (Acceptance rate: 36.4%)
    4. [J] T. Mallavarapu, J. Hao, Y. Kim, J.H. Oh, M. Kang†, "Pathway-based Deep Clustering for Molecular Subtyping of Cancer", Methods, 2019
    5. [C] S. Kosaraju, M. Masum, N. Tsaku, P. Patel, T. Bayramoglu, G. Modgil, and M. Kang†, "DoT-Net: Document Layout Classification Using Texture-based CNN", The 15th International Conference on Document Analysis and Recognition (ICDAR), 2019
    6. [J] Y. Kim, J. Hao, T. Mallavarapu, J. Park, and M. Kang†, "Hi-LASSO: High-dimensional LASSO", IEEE Access (IF: 3.557), vol. 7, pp. 44562-44573, 2019. doi: 10.1109/ACCESS.2019.2909071
    7. [C] 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%)
    8. [C] 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
    9. [C] 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), Honolulu, HI, USA, 2019, pp. 159-163. doi: 10.1109/ICCNC.2019.8685644
    10. [C] W. Feng, Z. Yu, M. Kang, H. Gong, and T. Ahn, "Practical Evaluation of Different Omics Data Integration Methods", International Workshop on Health Intelligence (W3PHAI'19) In conjunction with the 33rd AAAI Conference on Artificial Intelligence (AAAI-19), Accepted
    2018
    1. [C] 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), pp. 381-386, Madrid, Spain, 3-6 Dec. 2018 - Regular paper (Acceptance rate: 19.6%, 105 out of 534)
    2. [C] 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), pp. 470-475, Madrid, Spain, 3-6 Dec. 2018 - Regular paper (Acceptance rate: 19.6%, 105 out of 534)
    3. [J] 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
    4. [C] M. Masum, S. Kosaraju, T. Bayramoglu, G. Modgil, and M. Kang, "Automatic Knowledge Extraction from OCR documents Using Hierarchical Document Analysis," ACM Research in Adaptive and Convergent Systems (ACM RACS 2018), Accepted
    5. [J] J. Park, J. A. Bhuiyan, M. Kang, J. Son and K. Kang, "Nearest-Neighbor Search with Locally Weighted Linear Regression for Heartbeat Classification," Soft Computing (Springer), 2017, doi:10.1007/s00500-016-2410-9
    6. [J] Y. Kim, J. Hao, Y. Gautam, T. Mersha, M. Kang†, "DiffGRN: Differential gene regulatory network analysis", International Journal of Data Mining and Bioinformatics (IJDMB), 2018
    7. [J] Y. Kim, M. Kang, S. R. Jeong, "Text Mining and Sentiment Analysis for Predicting Box Office Success", KSII Transactions on Internet and Information Systems, 12:8, 2018, doi:10.3837/tiis.2018.08.030
    8. [J] A. Biswas, M. Kang, D. Kim, and J. Gao, "Robust Inductive Matrix Completion Strategy to Explore Associations between LincRNAs andHuman Disease Phenotypes," IEEE/ACM Transactions on Computational Biology and Bioinformatics (IEEE TCBB), 2018, DOI: 10.1109/TCBB.2018.2844816
    2017
    1. [J] A. Biswas, D. Kim, M. Kang, and J. Gao, "Stable solution to l2,1-based robust inductive matrix completion and its application in linking long noncoding RNAs to human diseases," BMC Medical Genomics, 10(Suppl 5):77, 2017
    2. [J] 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
    3. [J] M. Kang, D. Kim, C. Liu, and J. Gao, "Identifying cis/trans-acting expression Quantitative Trait Loci (eQTL)," International Journal of Data Mining and Bioinformatics (IJDMB), Vol.19, No.1, pp.1 - 18, 2017
    4. [J] M. Kang, L. Tang, and J. Gao, "Nonlinear-RANSAC parameter optimization for dynamic molecular systems and signaling pathways," International Journal of Data Mining and Bioinformatics (IJDMB), 18:02, No. 2, 2017,
    5. [J] D. Kim, M. Kang, A. Biswas, C. Yang, X. Wang, and J. Gao, "Effects of Low Dose Ionizing Radiation on DNA Damage-Caused Pathways by Reverse Phase Protein Array and Bayesian Networks," Journal of Bioinformatics and Computational Biology (JBCB), 15:02, 1750006, 2017, doi: 10.1142/S0219720017500068
    6. [J] J. Park, M. Kang, J. Gao, Y. Kim, and K. Kang, "Cascade Classification with Adaptive Feature Extraction for Arrhythmia Detection," Journal of Medical Systems (IF: 2.213), 41:11, 2017, doi: 10.1007/s10916-016-0660-9
    7. [C] 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. [C] M. Nguyen, C. Hung and M. Kang, "A Comparison on Sparse Coding and Moran’s I Method for Image Denoising," ACM Research in Adaptive and Convergent Systems (RACS 2017), 2017
    9. [C] 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
    10. [B] D. Gharana, S. Suh, and M. Kang, "Gender classification using deep learning", Big Data and Visual Analytics, Springer, pp 55-69, 2017
    2016
    1. [J] D. Kim, M. Kang, A. Biswas, C. Liu and J. Gao, "Integrative approach for inference of gene regulatory networks using lasso-based random featuring and application to psychiatric disorders," BMC Medical Genomics (IF: 2.726), p(Suppl 2):50, 2016, DOI: 10.1186/s12920-016-0202-9
    2. [J] M. Kang, J. Park, D. Kim, A. Biswas, C. Liu and J. Gao, "Multi-Block Bipartite Graph for Integrative Genomic Analysis," IEEE/ACM Transactions on Computational Biology and Bioinformatics (IEEE TCBB), 2016, DOI: 10.1109/TCBB.2016.2591521
    3. [J] M. Kang, L. Tang, and J. Gao, "Computational modeling of animal foreign body responses to implanted biomaterials," BMC Bioinformatics (IF: 2.576), 17(1):1-13, 2016, doi: 10.1186/s12859-016-0947-3- [Supplement]
    4. [J] S. Hill, L. Heiser, ..., The HPN-DREAM consortium (..., M. Kang, ...), and S. Mukherjee, "Inferring causal molecular networks: empirical assessment through a community-based effort, " Nature Methods (IF: 32.072), 13, 310-318, 2016
    5. [C] 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
    6. [C] A. Kumer Biswas, D. Kim, M. Kang, and J. Gao, "Robust Inductive Matrix Completion Strategy to Explore Associations between LincRNAs and Human Disease Phenotypes," Proceedings of IEEE International Conference on Bioinformatics & Biomedicine (IEEE BIBM 2016), pp. 334-339, 2016 - Regular paper, acceptance rate 19%
    7. [C] J. Park, M. Kang, J. Hur, and K. Kang, "Recommendations for antiarrhythmic drugs based on latent semantic analysis with fc-means clustering," 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (IEEE EMBC 2016), 2016
    2015
    1. [J] A. Biswas, M. Kang, D. Kim, C. Ding, B. Zhang, X. Wu, and J. Gao, "Inferring Disease Associations of the Long non-coding RNAs through Non-negative Matrix Factorization", Network Modeling Analysis in Health Informatics and Bioinformatics, 4(1), doi: 10.1007/s13721-015-0081-6, Springer
    2. [J] M. Kang, D. Kim, C. Liu, and J. Gao, "Multiblock Discriminant Analysis: A Novel Approach for Integrative Genomic Study", BioMed Research International (IF: 2.706), 2015, doi:10.1155/2015/783592
    3. [J] M. Kang, C. Zhang, H. Chun, C. Ding, C. Liu, and J. Gao, "eQTL epistasis: detecting epistatic effects and inferring hierarchical relationships of genes in biological pathways", Bioinformatics (IF: 6.968), 31(5):656-664, 2015, doi: 10.1093/bioinformatics/btu727 - [Supplement]
    4. [C] M. Kang, J. Park, D. Kim, A. Biswas, C. Liu, and J. Gao, "An Integrative Genomic Study for Multimodal Genomic Data Using Multi-Block Bipartite Graph", Proceedings of IEEE International Conference on Bioinformatics & Biomedicine (IEEE BIBM 2015), pp. 563-568, Washington D.C., USA, Nov. 9-12, 2015 - Regular paper (acceptance rate 19%, 68/346)
    5. [C] D. Kim, M. Kang, A. Biswas, C. Liu, and J. Gao, "Integrative approach for inference of gene regulatory networks using lasso-based random featuring and application to Psychiatric disorders", Proceedings of IEEE International Conference on Bioinformatics & Biomedicine (IEEE BIBM 2015), pp. 145-150, Washington D.C., USA, Nov. 9-12, 2015 - Regular paper (acceptance rate 19%, 68/346)
    6. [C] J. Park, M. Kang, Y. Kim, and K. Kang, "Heartbeat classification for detecting arrhythmia using normalized beat morphology features", Proceedings of IEEE International Conference on Bioinformatics & Biomedicine (IEEE BIBM 2015), Washington D.C., USA, Nov. 9-12, 2015
    2014
    1. [C] M. Kang, D. Kim, C. Liu, and J. Gao, "Multi-Block and Multi-Task Learning for Integrative Genomic Study", Proceedings of IEEE 14th International Conference on BioInformatics and BioEngineering (IEEE BIBE 2014), Boca Raton, USA, Nov. 10-12, 2014 - Regular paper for oral presentation
    2. [C] D. Kim, M. Kang, C. Liu, and J. Gao, "Integration of DNA Methylation, Copy Number Variation, and Gene Expression for Gene Regulatory Network Inference and Application to Psychiatric Disorders", Proceedings of IEEE 14th International Conference on BioInformatics and BioEngineering (IEEE BIBE 2014), Boca Raton, USA, Nov. 10-12, 2014
    2013
    1. [C] M. Kang, S. Li, C. Liu, and J. Gao, "eQTL Epistasis: Detecting Complex Interaction Effects between Multiple Loci from eQTL Data", Proceedings of IEEE International Conference on Bioinformatics & Biomedicine (IEEE BIBM 2013), pp. 23-28, Shanghai, China, Dec. 18-21, 2013 - Regular paper (acceptance rate 19.6%)
    2. [C] M. Kang, S. Li, D. Kim, C. Liu, and J. Gao, "eQTL Mapping Study via Regularized Sparse Canonical Correlation Analysis", The 12th International Conference on Machine Learning and Applications (IEEE ICMLA 2013), pp. 129-134, Miami, FL, Dec. 4-7, 2013 - Regular paper (acceptance rate 27%)
    3. [C] M. Kang, C. Liu, and J. Gao, "Sparse Generalized Canonical Correlation Analysis for Biological Model Integration: A Genetics Study of Psychiatric Disorders", The 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (IEEE EMBC 2013), pp. 1490-1493, Osaka, Japan, July 3-7, 2013
    4. [C] M. Kang, D. Kim, and J. Gao, "SF-RPQ: A novel statistical framework for reliable protein quantification in label-free quantitative proteomics", The 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (IEEE EMBC 2013), pp. 3527-3530, Osaka, Japan, July 3-7, 2013
    5. [C] S. Li, M. Kang, J. Nyagilo, B. Zhang, X. Wu, D. Dave and J. Gao, "Continuous Wavelet Transform based Continuum Regression for Quantitative Analysis of Surface-enhanced Raman Spectra", The 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (IEEE EMBC 2013), pp. 4486-4489, Osaka, Japan, July 3-7, 2013
    2012
    1. [C] M. Kang, D. Kim, and J. Gao, "A Novel Multivariate Quantification Strategy for Complex Mass Spectrometry Data", International Conference on Bioinformatics and Computational Biology (BICoB 2012), pp. 257-262, Las Vegas, NV, March 12-14, 2012 - Regular paper
    2011
    1. [C] M. Kang, J. Gao, and L. Tang, "Nonlinear RANSAC Optimization for Parameter Estimation with Applications to Phagocyte Transmigration", The 10th International Conference on Machine Learning and Applications (IEEE ICMLA 2011), pp. 501-504, Honolulu, HI, Dec. 18-21, 2011
    2. [C] J. Choi, M. Kang, D. Engels, R. Elmasri, "Investigation of Impact Factors for Various Performances of Passive UHF RFID System", Proceedings of IEEE International Conference on RFID-Technology and Applications (IEEE RFID-TA), Barcelona, Spain, Sep. 15-16, 2011
    2010
    1. [C] M. Kang, J. Gao, and L. Tang, "Computational Modeling of Phagocyte Transmigration during Biomaterial-Mediated Foreign Body Responses", Proceedings of IEEE International Conference on Bioinformatics & Biomedicine (IEEE BIBM 2010), pp. 609-612, Hong Kong, Dec. 18-21, 2010 (acceptance rate 37.5%)