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BMC Bioinformatics|August 16, 2022
PredictiveNetwork: predictive gene network estimation with application to gastric cancer drug response-predictive network analysisHeewon Park, Seiya Imoto, Satoru MiyanoBriefings in Bioinformatics|December 5, 2025
Powerful gene network enrichment analysis and its application to severe COVID-19 gene networkHeewon Park, Seiya Imoto, Satoru MiyanoPlos One|November 7, 2015
Recursive Random Lasso (RRLasso) for Identifying Anti-Cancer Drug TargetsHeewon Park, Seiya Imoto, Satoru MiyanoPlos One|August 23, 2023
Comprehensive information-based differential gene regulatory networks analysis (CIdrgn): Application to gastric cancer and chemotherapy-responsive gene network identificationHeewon Park, Seiya Imoto, Satoru MiyanoStatistical Methods in Medical Research|January 16, 2026
CiFGNA: Comprehensive information-based functional gene network analysisHeewon Park, Seiya Imoto, Satoru MiyanoBioinformatics (Oxford, England)|May 18, 2026
MetaCCI: Meta Cell Cell Interaction inference and its application to CCIs characteristics of MDSHeewon Park, Seiya Imoto, Satoru MiyanoScientific Reports|August 5, 2024
Meta graphical lasso: uncovering hidden interactions among latent mechanismsKoji Maruhashi, Hisashi Kashima, Satoru Miyano, et al.Journal of Computational Biology : a Journal of Computational Molecular Cell Biology|October 21, 2017
Adaptive NetworkProfiler for Identifying Cancer Characteristic-Specific Gene Regulatory NetworksHeewon Park, Teppei Shimamura, Seiya Imoto, et al.IEEE/ACM Transactions on Computational Biology and Bioinformatics|May 11, 2016
A Novel Adaptive Penalized Logistic Regression for Uncovering Biomarker Associated with Anti-Cancer Drug SensitivityHeewon Park, Yuichi Shiraishi, Seiya Imoto, et al.Frontiers in Artificial Intelligence|June 1, 2026
Explaining hidden mechanisms: a generative model for causal graphs with nonlinear latent factorsKoji Maruhashi, Heewon Park, Rui Yamaguchi, et al.Pageof 55