Research Fields

Computational & Systems Biology, Machine Learning, Probabilistic Networks, Translational Bioinformatics

 

 

Ph.D.

(Computer Science) KAIST, Republic of Korea, 2007

 

 

Brief Biography

Sungwon Jung is an Associate Professor of the Department of Genome Medicine and Science at Gachon University College of Medicine.

 

Dr. Jung's research targets systematic modeling of complex biological systems. He has made contributions to large-scale probabilistic network models, dynamic network models for biological systems, computational inference of neuronal connectivity, epigenetic effect on gene expressions, and context-specific pathway analysis with genomic data.

 

His current research is developing systematic methods that discover novel and druggable targets of diseases based on genomic data. Main approach is developing mathematical and computational methods that predict drug targets by modeling biological pathways with network models. He is also developing computational models and algorithms for pathway activity profiling and personalized disease subtype identification.

 

 

Professional Experience

Gachon University College of Medicine (Sep 2020 - present)

Associate Professor

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Department of Health Sciences and Technology, Gachon Advanced Institute for Health Sciences & Technology (2015 - present)

Adjunct Professor

 

Gachon University College of Medicine (March 2015 - Aug 2020)

Assistant Professor

 

Samsung Medical Center (Nov 2013 - Feb 2015)

Principal Scientist

 

Translational Genomics Research Institute (May 2008 - Sep 2013)

Post Doctoral Fellow

 

KAIST (Feb 2007 - May 2008)

Post Doctoral Research Associate

 

 

Selected Old Publications (See "Publication" for recent lists)

• Bo Young Oh, Woo Yong Lee, Sungwon Jung, Hye Kyung Hong, Do-Hyun Nam, Yoon Ah Park, Jung Wook Huh, Seong Hyeon Yun, Hee Cheol Kim, Ho-Kyung Chun and Yong Beom Cho. "Correlation between tumor engraftment in patient-derived xenograft models and clinical outcomes in colorectal cancer patients" Oncotarget, 6(18):16059-68, 2015.

• Sungwon Jung, and Seungchan Kim. “EDDY: A novel statistical gene set test method to detect differential genetic dependencies” Nucleic Acids Research 42(7): e60, 2014.

• Bodour Salhia, Jeff Kiefer, Julianna T. D. Ross, Raghu Metapally, Rae Anne Martinez, Kyle N. Johnson, Danielle M. DiPerna, Kimberly M. Paquette, Sungwon Jung, Sara Nasser, Garrick Wallstrom, Waibhav Tembe, Angela Baker, John Carpten, Jim Resau, Timothy Ryken, Zita Sibenaller, Emanual F. Petricoin, Lance A. Liotta, Ramesh K. Ramanathan, Michael E. Berens, and Nhan L. Tran. “Integrated Genomic and Epigenomic Analysis of Breast Cancer Brain Metastasis” PLoS ONE, volume 9, no. 1:e85448 EP-, 2014.

• Sungwon Jung, Michael P. Verdicchio, Jeff Kiefer, Daniel Von Hoff, Michael Berens, Michael Bittner, and Seungchan Kim. “Learning Contextual Gene Set Interaction Networks of Cancer with Condition Specificity” BMC Genomics, volume 14, no. 110, 2013.

• Angela Baker, Esteban Braggio, Suzanna Jacobus, Sungwon Jung, Dirk Larson, Terry Themeau, Angela Dispenzieri, Scott A Van Wier, Gregory Ahmann, Joan Levy, Louis Perkins, Seungchan Kim, Kim Henderson, David Vesole, S Vincent Rajkumar, Dianne F Jelinek, John Carpten, and Rafael Fonseca. “Uncovering the biology of multiple myeloma among African Americans: a comprehensive genomics approach” Blood, volume 121, no. 16:3147-52, 2013.

• Sungwon Jung, Seungchan Kim, Molly Gale, Irene Cherni, Rafael Fonseca, John Carpten, and Bodour Salhia. “DNA Methylation in Multiple Myeloma is Weakly Associated with Gene Transcription” PLoS One, volume 7, no. 12:e52626. doi:10.1371/journal.pone.0052626, 2012.

• Sungwon Jung, Yoonkey Nam, and Doheon Lee. “Inference of Combinatorial Neuronal Synchrony with Bayesian Networks”Journal of Neuroscience Methods, volume 186:130–139, 2010.

• Chao Sima, Jianping Hua, and Sungwon Jung. “Inference of Gene Regulatory Network Using Time-series Data: A Survey”Current Genomics, volume 10, no. 6:416–429, 2009.