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Staff information

Hyun-Seob Song

Computational Biology
Pacific Northwest National Laboratory
PO Box 999
MSIN: J4-18
Richland, WA 99352


Hyun Song’s research is directed toward developing modeling and computational tools for the simulation of cellular metabolism and microbial community dynamics. His research interest in metabolic modeling includes 1) omics data-guided estimation of flux distribution in a genome-scale metabolic network, 2) integrative analysis of metabolic and regulatory networks, and 3) dynamic prediction of cellular response to genetic and environmental perturbations. These methods are being integrated with population dynamics models toward the development of a general platform of microbial community modeling. His current research is focused on predicting microbial interactions in complex communities by combining data-driven network inference and genome-informed analysis including community metabolic modeling.

Research Interests

  • Pathway analysis of genome-scale metabolic networks
  • Dynamic modeling of metabolic systems
  • Multiscale modeling of microbial community dynamics
  • Computational identification of biomarkers and drug targets
  • Development of efficient numerical algorithms for fast simulation

Education and Credentials

  • Post-doctoral associate, Chemical Engineering, Purdue University, 2000-01, 2007-11
  • Ph.D., Chemical Engineering, Korea University, 1995-99
  • M.S., Chemical Engineering, Korea University, 1993-95
  • B.S., Chemical Engineering, Korea University, 1989-93

Affiliations and Professional Service

  • Member, International Society for Microbial Ecology
  • Member, American Institute of Chemical Engineers
  • Member, Korean Society of Rheology

PNNL Publications


  • Khan N.E., Y. Maezato, R.S. McClure, C.J. Brislawn, J.M. Mobberley, N.G. Isern, and W.B. Chrisler, et al. 2018. "Phenotypic responses to interspecies competition and commensalism in a naturally-derived microbial co-culture." Scientific Reports 8. PNNL-SA-129337. doi:10.1038/s41598-017-18630-1
  • Song H., W.C. Nelson, J. Lee, R.C. Taylor, C.S. Henry, A.S. Beliaev, and D. Ramkrishna, et al. 2018. "Metabolic Network Modeling for Computer-Aided Design of Microbial Interactions." In Emerging Areas in Bioengineering, edited by HN Chang, et al. 793-801. Weinheim:Wiley-VCH Verlag GmbH & Co. PNNL-SA-115176. doi:10.1002/9783527803293


  • Bernstein H.C., C.J. Brislawn, R.S. Renslow, K.L. Dana, B.R. Morton, S.R. Lindemann, and H. Song, et al. 2017. "Trade-offs between microbiome diversity and productivity in a stratified microbial mat." The ISME Journal 11, no. 2:405-414. PNNL-SA-120993. doi:10.1038/ismej.2016.133
  • Song H., D.G. Thomas, J.C. Stegen, M. Li, C. Liu, X. Song, and X. Chen, et al. 2017. "Regulation-structured dynamic metabolic model provides a potential mechanism for delayed enzyme response in denitrification process." Frontiers in Microbiology 8. PNNL-SA-129317. doi:10.3389/fmicb.2017.01866
  • Song H., N. Goldberg, A. Mahajan, and D. Ramkrishna. 2017. "Sequential Computation of Elementary Modes and Minimal Cut Sets in Genome-scale Metabolic Networks Using Alternate Integer Linear Programming." Bioinformatics 33, no. 15:2345-2353. PNNL-SA-101927. doi:10.1093/bioinformatics/btx171


  • Henry C.S., H.C. Bernstein, P. Weisenhorn, R.C. Taylor, J. Lee, J.D. Zucker, and H. Song. 2016. "Microbial Community Metabolic Modeling: A Community Data-Driven Network Reconstruction." Journal of Cellular Physiology 231, no. 11:2339-2345. PNNL-SA-118336. doi:10.1002/jcp.25428
  • Lindemann S.R., H.C. Bernstein, H. Song, J.K. Fredrickson, M.W. Fields, W. Shou, and D. Johnson, et al. 2016. "ENGINEERING MICROBIAL CONSORTIA FOR CONTROLLABLE OUTPUTS." The ISME Journal 10, no. 2016:2077-2084. PNNL-SA-110327. doi:10.1038/ismej.2016.26
  • Ramkrishna D., and H. Song. 2016. "Analysis of Bioprocesses. Dynamic Modeling is a Must." In International Conference on Advances in Bioprocess Engineering and Technology (ICABET 2016), March 11-13, 2016, Hyderabad, India. Materials Today: Proceedings, edited by D Ramkrishna and S Sengupta, 3, 3587-3599. PNNL-SA-115407. doi:10.1016/j.matpr.2016.10.040
  • Renslow R.S., S.R. Lindemann, and H. Song. 2016. "A generalized spatial measure for resilience of microbial systems." Frontiers in Microbiology 7. PNNL-SA-113459. doi:10.3389/fmicb.2016.00443
  • Song H., and D. Ramkrishna. 2016. "Comment on “Mathematical modeling of unicellular microalgae and cyanobacteria metabolism for biofuel production” by Baroukh et al [Curr. Opin. Biotechnol. 2015, 33:198-205]." Current Opinion in Biotechnology 38. PNNL-SA-117715. doi:10.1016/j.copbio.2016.02.026


  • Song H., and C. Liu. 2015. "Dynamic Metabolic Modeling of Denitrifying Bacterial Growth: The Cybernetic Approach." Industrial and Engineering Chemistry Research 54, no. 42:10221-10227. PNNL-SA-110127. doi:10.1021/acs.iecr.5b01615
  • Song H., R.S. McClure, H.C. Bernstein, C.C. Overall, E.A. Hill, and A.S. Beliaev. 2015. "Integrated in silico analyses of regulatory and metabolic networks of Synechococcus sp. PCC 7002 reveal relationships between gene centrality and essentiality." Life 5, no. 2:1127-1140. PNNL-SA-109173. doi:10.3390/life5021127
  • Song H., R.S. Renslow, J.K. Fredrickson, and S.R. Lindemann. 2015. "Integrating ecological and engineering concepts of resilience in microbial communities." Frontiers in Microbiology 6. PNNL-SA-112189. doi:10.3389/fmicb.2015.01298


  • Song H., W.R. Cannon, A.S. Beliaev, and A. Konopka. 2014. "Mathematical Modeling of Microbial Community Dynamics: A Methodological Review." Processes 2, no. 4:711-752. PNNL-SA-104609. doi:10.3390/pr2040711

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