Hyun-Seob Song

The Song research group focuses on 1) developing model-data integration methods for understanding fundamental mechanisms of interspecies interactions in microbial communities and 2) applying ecological principles for microbiome engineering. The primary goal of human microbiome research in his group is to develop predictive community models for unraveling the relationships among perturbations, composition and functional activities in microbial communities (in particular, in the gut microbiota), and health and disease. For this purpose, they use a suite of complementary in silico tools for synergistic integration, including data-driven computational analysis (such as network inference and machine learning) and physics-based microbial modeling (such as metabolic network reconstruction, agent-based modeling, and cybernetic modeling). This integrative approach uniquely enables predicting context-dependent microbial interactions and community functions and their linkages to human health and disease.

 

Featured publications

  • Song HS, Lee JY, Haruta S, Nelson WC, Lee DY, Lindemann SR, Fredrickson JK, Bernstein HC (2019), Minimal Interspecies Interaction Adjustment (MIIA): inference of member-dependent interactions in microbial communities, Frontiers in Microbiology, 10: Article number 1264
  • McClure RS, Overall CC, Hill EA, Song HS, Charania M, Bernstein HC, McDermott JE, Beliaev AS (2018) Species-specific transcriptomic network inference of interspecies interactions, ISME J. 12: 2011–2023
  • Song HS, Goldberg N, Mahajan A, Ramkrishna D (2017) Sequential computation of elementary modes and minimal cut sets in genome-scale metabolic networks using alternate integer linear programming. Bioinformatics 33(15): 2345–2353
  • Henry CS, Bernstein HC, Weisenhorn P, Taylor RC, Lee JY, Zucker J, Song HS (2016). Microbial Community Metabolic Modeling: A Community Data‐Driven Network Reconstruction. Journal of Cellular Physiology 231: 2339–2345
  • Song HS, McClure RS, Bernstein HC, Overall CC, Hill EA, Beliaev AS (2015) Integrated In silico analyses of regulatory and metabolic networks of Synechococcus sp. PCC 7002 reveal relationships between gene centrality and essentiality. Life 5(2): 1127-1140