Song Research Group - Journal Articles

Journal Articles

2021

  • Sengupta, A., Fansler, S. J., Chu, R. K., Danczak, R. E., Garayburu-Caruso, V. A., Renteria, L., Song, H.-S., Toyoda, J., Wells, J., & Stegen, J. C. (2021). Disturbance triggers non-linear microbe–environment feedbacks, Biogeosciences, 18(16), 4773–4789. https://doi.org/10.5194/bg-18-4773-2021

  • Ahamed, F., Song, H.-S., and Ho Y.K. (2021). Modeling Coordinated Enzymatic Control of Saccharification and Fermentation by Clostridium thermocellum During Consolidated Bioprocessing of Cellulose, Biotechnology and Bioengineering, 118, 1898-1912. https://doi.org/10.1002/bit.27705   
  • Song, H.-S., Stegen, J. C., Graham, E. B., and Scheibe, T. (2021). Historical Contingency in Microbial Resilience to Hydrologic Perturbations. Frontiers in Water, 3, 590378. https://doi.org/10.3389/frwa.2021.590378

2020

  • Ro, S.-H., Fay, J., Cyuzuzo, C. I., Jang, Y., Lee, N., Song, H.-S., and Harris, E. N. (2020). SESTRINs: Emerging Dynamic Stress-Sensors in Metabolic and Environmental Health. Frontiers in Cell and Developmental Biology, 8, 603421. https://doi.org/10.3389/fcell.2020.603421.
  • Song, H.-S., Stegen, J. C., Graham, E. B., Lee, J.-Y., Garayburu-Caruso, V., Nelson, W. C., Chen, X., Moulton, J. D., & Scheibe, T. D. (2020). Representing Organic Matter Thermodynamics in Biogeochemical Reactions via Substrate-Explicit Modeling. Frontiers in Microbiology, 11,  531756. https://doi.org/10.3389/fmicb.2020.531756.

  • Kessell, A. K., McCullough, H. C., Auchtung, J. M., Bernstein, H. C., & Song, H.-S. (2020). Predictive interactome modeling for precision microbiome engineering. Current Opinion in Chemical Engineering, 30, 77-85. https://doi.org/10.1016/j.coche.2020.08.003.
  • Choi, Y.-M., Lee, Y. Q., Song, H.-S., & Lee, D.-Y. (2020). Genome scale metabolic models and analysis for evaluating probiotic potentials. Biochemical Society Transactions, 48(4), 1309-1321. https://doi.org/10.1042/bst20190668.
  • McClure, R. S., Lee, J.-Y., Chowdhury, T. R., Bottos, E. M., White, R. A., Kim, Y.-M., Nicora, C. D., Metz, T. O., Hofmockel, K. S., Jansson, J. K., & Song, H.-S. (2020). Integrated network modeling approach defines key metabolic responses of soil microbiomes to perturbations. Scientific Reports, 10(1), 1-9. https://doi.org/10.1038/s41598-020-67878-7.
  • Lee, J.-Y., Sadler, N. C., Egbert, R. G., Anderton, C. R., Hofmockel, K. S., Jansson, J. K., & Song, H.-S. (2020). Deep Learning Predicts Microbial Interactions from Self-organized Spatiotemporal Patterns. Computational and Structural Biotechnology Journal, 18, 1259-1269.  https://doi.org/10.1016/j.csbj.2020.05.023.
  • Lee, J.-Y., Haruta, S., Kato, S., Bernstein, H. C., Lindemann, S. R., Lee, D.-Y., Fredrickson, J. K., & Song, H.-S. (2020). Prediction of Neighbor-Dependent Microbial Interactions From Limited Population Data. Frontiers in Microbiology, 10, 3049. https://doi.org/10.3389/fmicb.2019.03049.
  • Garayburu-Caruso, V. A., Stegen, J. C., Song, H.-S., Renteria, L., Wells, J., Garcia, W., Resch, C. T., Goldman, A. E., Chu, R. K., & Toyoda, J. (2020). Carbon limitation leads to thermodynamic regulation of aerobic metabolism. Environmental Science & Technology Letters, 7(7): 517-524. https://doi.org/10.1021/acs.estlett.0c00258.
  • Ahamed, F., Singh, M., Song, H.-S., Doshi, P., Ooi, C. W., & Ho, Y. K. (2020). On the use of sectional techniques for the solution of depolymerization population balances: Results on a discrete-continuous mesh. Advanced Powder Technology, 31(7): 2669-2679. https://doi.org/10.1016/j.apt.2020.04.032

2019

  • Ahamed, F., Song, H.-S., Ooi, C. W., & Ho, Y. K. (2019). Modelling heterogeneity in cellulose properties predicts the slowdown phenomenon during enzymatic hydrolysis. Chemical Engineering Science, 206, 118-133. https://dx.doi.org/10.1016/j.ces.2019.05.028.
  • Song, H.-S., Lee, J. Y., Haruta, S., Nelson, W. C., Lee, D. Y., Lindemann, S. R., Fredrickson, J. K., & Bernstein, H. C. (2019). Minimal Interspecies Interaction Adjustment (MIIA): Inference of Neighbor-Dependent Interactions in Microbial Communities. Frontiers in Microbiology, 10,  1264. https://doi.org/10.3389/fmicb.2019.01264.
  • Chowdhury, T. R., Lee, J. Y., Bottos, E. M., Brislawn, C. J., White, R. A., Bramer, L. M., Brown, J., Zucker, J. D., Kim, Y. M., Jumpponen, A., Rice, C. W., Fansler, S. J., Metz, T. O., McCue, L. A., Callister, S. J., Song, H.-S., & Jansson, J. K. (2019). Metaphenomic Responses of a Native Prairie Soil Microbiome to Moisture Perturbations. mSystems, 4(4). https://doi.org/10.1128/mSystems.00061-19

2018

  • Song, X. H., Chen, X. Y., Stegen, J., Hammond, G., Song, H.-S., Dai, H., Graham, E., & Zachara, J. M. (2018). Drought Conditions Maximize the Impact of High-Frequency Flow Variations on Thermal Regimes and Biogeochemical Function in the Hyporheic Zone. Water Resources Research, 54(10), 7361-7382. https://dx.doi.org/10.1029/2018wr022586.
  • Khan, N., Maezato, Y., McClure, R. S., Brislawn, C. J., Mobberley, J. M., Isern, N., Chrisler, W. B., Markillie, L. M., Barney, B. M., Song, H.-S., Nelson, W. C., & Bernstein, H. C. (2018). Phenotypic responses to interspecies competition and commensalism in a naturally-derived microbial co-culture. Scientific Reports, 8. https://doi.org/10.1038/s41598-017-18630-1.
  • McClure, R. S., Overall, C. C., Hill, E. A., Song, H.-S., Charania, M., Bernstein, H. C., McDermott, J. E., & Beliaev, A. S. (2018). Species-specific transcriptomic network inference of interspecies interactions. ISME Journal, 12(8), 2011-2023. https://dx.doi.org/10.1038/s41396-018-0145-6.
  • Song, H.-S. (2018). Design Principles of Microbial Communities: From Understanding to Engineering. Current Genomics, 19(8), 699-700. https://dx.doi.org/10.2174/138920291908181005100741.
  • Dautel, S., Khan, N., Brandvold, K. R., Brislawn, C. J., Hutchison, J., Weitz, K. K., Heyman, H. M., Song, H.-S., Ilhan, Z. E., & Hill, E. A. (2018). Lactobacillus acidophilus disrupts collaborative multispecies bile acid metabolism. bioRxiv, 296020. https://doi.org/10.1101/296020

2017

  • Song, H.-S., Thomas, D. G., Stegen, J. C., Li, M. J., Liu, C. X., Song, X. H., Chen, X. Y., Fredrickson, J. K., Zachara, J. M., & Scheibe, T. D. (2017). Regulation-Structured Dynamic Metabolic Model Provides a Potential Mechanism for Delayed Enzyme Response in Denitrification Process. Frontiers in Microbiology, 8,  1866. https://doi.org/10.3389/fmicb.2017.01866.
  • Bernstein, H. C., Brislawn, C., Renslow, R. S., Dana, K., Morton, B., Lindemann, S. R., Song, H.-S., Atci, E., Beyenal, H., Fredrickson, J. K., Jansson, J. K., & Moran, J. J. (2017). Trade-offs between microbiome diversity and productivity in a stratified microbial mat. ISME Journal, 11(2), 405-414. https://dx.doi.org/10.1038/ismej.2016.133.
  • Song, H.-S., 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. https://dx.doi.org/10.1093/bioinformatics/btx171

2016

  • Lindemann, S. R., Bernstein, H. C., Song, H.-S., Fredrickson, J. K., Fields, M. W., Shou, W. Y., Johnson, D. R., & Beliaev, A. S. (2016). Engineering microbial consortia for controllable outputs. ISME Journal, 10(9), 2077-2084. https://dx.doi.org/10.1038/ismej.2016.26.
  • Henry, C. S., Bernstein, H. C., Weisenhorn, P., Taylor, R. C., Lee, J. Y., Zucker, J., & Song, H.-S. (2016). Microbial Community Metabolic Modeling: A Community Data-Driven Network Reconstruction. Journal of Cellular Physiology, 231(11), 2339-2345. https://dx.doi.org/10.1002/jcp.25428.
  • Renslow, R. S., Lindemann, S. R., & Song, H.-S. (2016). A Generalized Spatial Measure for Resilience of Microbial Systems. Frontiers in Microbiology, 7,  443. https://doi.org/10.3389/fmicb.2016.00443.
  • Ramkrishna, D., & Song, H.-S. (2016). Analysis of Bioprocesses. Dynamic Modeling is a Must. MaterialsToday:Proceedings, 3(10), 3587-3599. https://doi.org/10.1016/j.matpr.2016.10.040

2015

  • Song, H.-S., & Liu, C. X. (2015). Dynamic Metabolic Modeling of Denitrifying Bacterial Growth: The Cybernetic Approach. Industrial & Engineering Chemistry Research, 54(42), 10221-10227. https://dx.doi.org/10.1021/acs.iecr.5b01615.
  • Song, H.-S., Renslow, R. S., Fredrickson, J. K., & Lindemann, S. R. (2015). Integrating Ecological and Engineering Concepts of Resilience in Microbial Communities. Frontiers in Microbiology, 6,  1298. https://doi.org/10.3389/fmicb.2015.01298.
  • Song, H.-S., McClure, R. S., Bernstein, H. C., Overall, C. C., Hill, E. A., & Beliaev, A. S. (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. https://doi.org/10.3390/life5021127.

2014

Before 2014

  • Song, H.-S., DeVilbiss, F., & Ramkrishna, D. (2013). Modeling metabolic systems: the need for dynamics. Current Opinion in Chemical Engineering, 2(4), 373-382. https://dx.doi.org/10.1016/j.coche.2013.08.004.
  • Song, H.-S., Ramkrishna, D., Pinchuk, G. E., Beliaev, A. S., Konopka, A. E., & Fredrickson, J. K. (2013). Dynamic modeling of aerobic growth of Shewanella oneidensis. Predicting triauxic growth, flux distributions, and energy requirement for growth. Metabolic Engineering, 15, 25-33. https://dx.doi.org/10.1016/j.ymben.2012.08.004.
  • Song, H.-S., & Ramkrishna, D. (2013). Complex nonlinear behavior in metabolic processes: Global bifurcation analysis of Escherichia coli growth on multiple substrates. Processes, 1(3), 263-278. https://doi.org/10.3390/pr1030263.
  • Kim, J. I., Song, H.-S., Sunkara, S. R., Lali, A., & Ramkrishna, D. (2012). Exacting predictions by cybernetic model confirmed experimentally: Steady state multiplicity in the chemostat. Biotechnology Progress, 28(5), 1160-1166. https://dx.doi.org/10.1002/btpr.1583.
  • Adler, P., Song, H.-S., Kastner, K., Ramkrishna, D., & Kunz, B. (2012). Prediction of dynamic metabolic behavior of Pediococcus pentosaceus producing lactic acid from lignocellulosic sugars. Biotechnology Progress, 28(3), 623-635. https://dx.doi.org/10.1002/btpr.1521.
  • Song, H.-S., & Ramkrishna, D. (2012). Prediction of dynamic behavior of mutant strains from limited wild-type data. Metabolic Engineering, 14(2), 69-80. https://dx.doi.org/10.1016/j.ymben.2012.02.003.
  • Song, H.-S., Kim, S. J., & Ramkrishna, D. (2012). Synergistic Optimal Integration of Continuous and Fed-Batch Reactors for Enhanced Productivity of Lignocellulosic Bioethanol. Industrial & Engineering Chemistry Research, 51(4), 1690-1696. https://dx.doi.org/10.1021/ie200879s.
  • Ramkrishna, D., & Song, H.-S. (2012). Dynamic models of metabolism: Review of the cybernetic approach. AIChE Journal, 58(4), 986-997. https://dx.doi.org/10.1002/aic.13734.
  • Song, H.-S., Morgan, J. A., & Ramkrishna, D. (2012). Towards Increasing the Productivity of Lignocellulosic Bioethanol: Rational Strategies Fueled by Modeling. Bioethanol, 173-190. DOI: 10.5772/24278.
  • Geng, J., Song, H.-S., Yuan, J., & Ramkrishna, D. (2012). On enhancing productivity of bioethanol with multiple species. Biotechnology and bioengineering, 109(6), 1508-1517. https://doi.org/10.1002/bit.24419.
  • Song, H.-S., & Ramkrishna, D. (2011). Cybernetic Models Based on Lumped Elementary Modes Accurately Predict Strain-Specific Metabolic Function. Biotechnology and bioengineering, 108(1), 127-140. https://dx.doi.org/10.1002/bit.22922.
  • Franz, A., Song, H.-S., Ramkrishna, D., & Kienle, A. (2011). Experimental and theoretical analysis of poly (β-hydroxybutyrate) formation and consumption in Ralstonia eutropha. Biochemical Engineering Journal, 55(1), 49-58. https://doi.org/10.1016/j.bej.2011.03.006.
  • Song, H.-S., & Ramkrishna, D. (2010). Issues with increasing bioethanol productivity: A model directed study. Korean Journal of Chemical Engineering, 27(2), 576-586. https://dx.doi.org/10.1007/s11814-010-0101-2.
  • Song, H.-S., & Ramkrishna, D. (2010). Prediction of Metabolic Function From Limited Data: Lumped Hybrid Cybernetic Modeling (L-HCM). Biotechnology and bioengineering, 106(2), 271-284. https://dx.doi.org/10.1002/bit.22692.
  • Wong, W. C., Song, H.-S., Lee, J. H., & Ramkrishna, D. (2010). Hybrid cybernetic model-based simulation of continuous production of lignocellulosic ethanol: Rejecting abruptly changing feed conditions. Control Engineering Practice, 18(2), 177-189. https://dx.doi.org/10.1016/j.conengprac.2009.09.002.
  • Song, H.-S., & Ramkrishna, D. (2009). Reduction of a Set of Elementary Modes Using Yield Analysis. Biotechnology and bioengineering, 102(2), 554-568. https://dx.doi.org/10.1002/bit.22062
  • Song, H.-S., Morgan, J. A., & Ramkrishna, D. (2009). Systematic Development of Hybrid Cybernetic Models: Application to Recombinant Yeast Co-Consuming Glucose and Xylose. Biotechnology and bioengineering, 103(5), 984-1002. https://doi.org/10.1002/bit.22332.
  • Song, H.-S., & Ramkrishna, D. (2009). When is the quasi-steady-state approximation admissible in metabolic modeling? When admissible, what models are desirable? Industrial & Engineering Chemistry Research, 48(17), 7976-7985. https://doi.org/10.1021/ie900075f.
  • Ramkrishna, D., & Song, H.-S. (2008). A Rationale for Monod's Biochemical Growth Kinetics. Industrial & Engineering Chemistry Research, 47(23), 9090-9098. https://dx.doi.org/10.1021/ie800905d.
  • Lee, J. S., Shin, D. M., Song, H.-S., Jung, H. W., & Hyun, J. C. (2006). Existence of optimal cooling conditions in the film blowing process. Journal of Non-Newtonian Fluid Mechanics, 137(1-3), 24-30. https://dx.doi.org/10.1016/j.jnnfm.2005.12.011.
  • Song, H.-S., & Han, S. P. (2005). A general correlation for pressure drop in a Kenics static mixer. Chemical Engineering Science, 60(21), 5696-5704. https://dx.doi.org/10.1016/j.ces.2005.04.084.
  • Song, H.-S., Ramkrishna, D., Trinh, S., & Wright, H. (2004). Operating strategies for Fischer-Tropsch reactors: A model-directed study. Korean Journal of Chemical Engineering, 21(2), 308-317. https://doi.org/10.1007/BF02705414.
  • Hyun, J. C., Kim, H., Lee, J. S., Song, H.-S., & Jung, H. W. (2004). Transient solutions of the dynamics in film blowing processes. Journal of Non-Newtonian Fluid Mechanics, 121(2-3), 157-162. https://dx.doi.org/10.1016/j.jnnfm.2004.06.004.
  • Choe, J., Kwon, Y., Kim, Y., Song, H.-S., & Song, K. H. (2003). Micromixer as a continuous flow reactor for the synthesis of a pharmaceutical intermediate. Korean Journal of Chemical Engineering, 20(2), 268-272. https://doi.org/10.1007/BF02697239.
  • Song, H.-S., Ramkrishna, D., Trinh, S., Espinoza, R. L., & Wright, H. (2003). Multiplicity and sensitivity analysis of Fischer-Tropsch bubble column slurry reactors: plug-flow gas and well-mixed slurry model. Chemical Engineering Science, 58(12), 2759-2766. https://dx.doi.org/10.1016/S0009-2509(03)00125-8.
  • Song, H.-S., Ramkrishna, D., Trinh, S., & Wright, H. (2003). Diagnostic nonlinear analysis of Fischer-Tropsch synthesis in stirred-tank slurry reactors. AIChE Journal, 49(7), 1803-1820.  https://doi.org/10.1002/aic.690490717.
  • Song, H.-S., Lee, J. S., & Hyun, J. C. (2002). A kinetic model for polystyrene (PS) pyrolysis reaction. Korean Journal of Chemical Engineering, 19(6), 949-953. https://doi.org/10.1007/BF02707216.
  • Lee, J. S., Jung, H. W., Song, H.-S., Lee, K. Y., & Hyun, J. C. (2001). Kinematic waves and draw resonance in film casting process. Journal of Non-Newtonian Fluid Mechanics, 101(1-3), 43-54. https://doi.org/10.1016/S0377-0257(01)00155-0.
  • Song, H.-S., & Hyun, J. C. (2001). Practical optimization methods for finding best recycling pathways of plastic materials. Clean Technology, 7(2), 99-107. https://www.cheric.org/research/tech/periodicals/view.php?seq=12826.
  • Jung, H. W., Song, H.-S., & Hyun, J. C. (2000). Draw resonance and kinematic waves in viscoelastic isothermal spinning. AIChE Journal, 46(10), 2106-2111. https://grtrkr.korea.ac.kr/jchyun/papers/AIChE46-10-2106.pdf.
  • Jung, H. W., Song, H.-S., & Hyun, J. C. (1999). Analysis of the stabilizing effect of spinline cooling in melt spinning. Journal of Non-Newtonian Fluid Mechanics, 87(2-3), 165-174. https://doi.org/10.1016/S0377-0257(99)00061-0.
  • Song, H.-S., & Hyun, J. C. (1999). An optimization study on the pyrolysis of polystyrene in a batch reactor. Korean Journal of Chemical Engineering, 16(3), 316-324. https://doi.org/10.1007/BF02707119.
  • Song, H.-S., Moon, K. S., & Hyun, J. C. (1999). A life-cycle assessment (LCA) study on the various recycle routes of PET bottles. Korean Journal of Chemical Engineering, 16(2), 202-207. https://doi.org/10.1007/BF02706837.
  • Song, H.-S., & Hyun, J. C. (1999). A study on the comparison of the various waste management scenarios for PET bottles using the life-cycle assessment (LCA) methodology. Resources Conservation and Recycling, 27(3), 267-284. https://doi.org/10.1016/S0921-3449(99)00022-1.
  • Song, H.-S., Park, Y. D., & Hyun, J. C. (1996). Optimization for the minimum reaction time of PET esterification. Korean Journal of Chemical Engineering, 13(4), 369-378. https://doi.org/10.1007/BF02705964.