2025

Lee, S.-H., N.-R. Lee, J. H. Ji, H.-J. Tak, Y. Q. Lee, M. Lee, D. Kim, S. Lim, Lee, D.-Y., C. H. Lee, E. J. Y. and K. H. Kim. 2025. Evolution-aided enhancement of β-glucosidase activity for improved conversion of isoflavone glucosides to aglycones by Lactobacillus gasseri. Food Chem., in press.

Kim, S.-J., M. Lee, D. Kim, S. Yoon, Lee, D.-Y.*. 2025. AutoML-driven soft sensors for real-time monitoring of amino acids in mammalian perfusion cultures. Biotechnol. Bioeng. in press.

Kim, D., S.-Y. Park, Y. Q. Lee, Y. Kwon, Y. H. Choe, M. J. Kim* and Lee, D.-Y.*. 2025. Combining site-specific gastrointestinal microbiome and mycobiome profiling with clinical indicators for effective management of pediatric Crohn's disease. iScience, 28(8): 113160.

Park, S.-Y., Y. Q. Lee, D. Kim, D. K. Sung, K.-S. Kim, J. S. Lee, J.-Y. Cho, W, S. Lee, S. I. Sung* and Lee, D.-Y.*. 2025. Deciphering dynamic antibiotics-microbiome-metabolome interactions in preterm infants using systems biology. iScience, 28(8): 113038.

Lee, Y. Q., Y.-M. Choi, S.-Y. Park, S.-K. Kim, M. Lee, D. Kim, L. Koduru, M. Lakshmanan, S. Jung, M. J. Kim, Y. H. Choe and Lee, D.-Y.*. 2025. Genome-scale metabolic model-guided systematic framework for designing customized live biotherapeutic products. npj Syst. Biol. Appl., 11, 73.

Lee, M†., S.-H. Han†, D. Kim, S. Yun, J. Yeom, M. Kyeong, S.-Y. Park* and Lee, D.-Y.*. 2025. Systematic identification of genomic hotspots for high-yield protein production in CHO cells. New Biotechnol., 88, 61–72.

Demissie, E. A., S.-Y. Park, J. H. Moon and Lee, D.-Y.*. 2025. Comparative analysis of codon optimization tools: advancing toward a multi-criteria framework for synthetic gene design. J. Microbiol. Biotechnol., 35, e2411066.

Han, S.-H.†,*, Park, S.-Y.†, Cha, H.-M., Lee, K.-B., Lim, J.-H., Lee, D.-Y.*. 2025. A robust scale-down model development and process characterization for monoclonal antibody biomanufacturing using multivariate data analysis. J. Biotechnol., 401, 11-20.

Song, J., Park, S.-Y., Lee, D.-Y.*. 2025. Characterization and design of dipeptide media formulation for scalable therapeutic production. Appl. Microbiol. Biotechnol., 109, 7.

2024

Song, H.-S.*, Lee, N.-R., Kessell, A. K., McCullough, H. C., Park, S.-Y., Zhou, K. and Lee, D.-Y.*. 2024. Kinetics-based inference of environment-dependent microbial interactions and their dynamic variation. mSystems, 9(5), e01305-23. 

Park, S.-Y.†, Choi, D.-H.†, Song, J., Lakshmanan, M., Richelle, A., Yoon, S., Kontoravdi, C., Lewis, N. E., Lee, D.-Y.*. 2024. Driving towards digital biomanufacturing by CHO genome-scale models. Trends Biotechnol., 42(9), 1192-1203.

Keita, V. M.†, Lee, Y. Q.†, Lakshmanan, M., Ow, D. S.-W., Staniland, P., Staniland, J., Savill, I., Tee, K. L., Wong, T. S.*, Lee, D.-Y.*. 2024. Evaluating oleaginous yeasts for enhanced microbial lipid production using sweetwater as a sustainable feedstock. Microb. Cell Fact., 23, 63.

Wang, Y., Fu, Q., Park, S. Y., Lee, Y. S., Park, S.-Y., Lee, D.-Y., and Yoon, S., 2024. Decoding cellular mechanism of recombinant adeno-associated virus (rAAV) and engineering host-cell factories toward intensified viral vector manufacturing. Biotechnol. Adv., 71, 108322.

Park, S.-Y., Song, J., Choi, D.-H., Park, U., Cho, H., Hong, B. H., Silberberg, Y. R., Lee, D.-Y.*,. 2024. Exploring metabolic effects of dipeptide feed media on CHO cell cultures by in silico model-guided flux analysis. Appl. Microbiol. Biotechnol., 108, 123.

2023

Park, S.-Y.†, Choi, D.-H., Song, J., Park, U., Cho, H., Hong, B. H., Silberberg, Y. R., Lee, D.-Y.*,. 2023. Debottlenecking and reformulating feed media for improved CHO cell growth and titer by data-driven and model-guided analyses. Biotechnol. J., 18(12), 2300126.

Choi, Y.-M., Choi, D.-H., Lee, Y. Q., Koduru, L., Lewis, N. E., Lakshmanan, M.*, Lee, D.-Y.*, 2023. Mitigating biomass composition uncertainties in flux balance analysis using ensemble representations. Comput. Struct. Biotechnol. J. 21, 3736-3745.

Kim, S.-K.†, Lee, M.†, Lee, Y. Q., Lee, H. J., Rho, M., Kim, Y., Seo, J. Y., Youn, S. H., Hwang, S. J., Kang, N. G., Lee, C.-H., Park, S.-Y.*, Lee, D.-Y.*, 2023. Genome-scale metabolic modeling and in silico analysis of opportunistic skin pathogen Cutibacterium acnes. Front. Cell. Infect. Microbiol. 13, 1099314. 

Park, S.-Y., Kim, S. J., Park, C. H., Kim, J. Y., Lee, D.-Y.*, 2023. Data-driven prediction models for forecasting multi-step ahead profiles of mammalian cell culture performance towards bioprocess digital twin. Biotechnol. Bioeng. 120(9), 2494–2508. 

Kang, D. E., An, Y. B., Kim, Y., Ahn, S., Kim, Y. J., Lim, J. S., ... Ryu, S. H., Choi, H., Yoo, J., You, W. K., Lee, D.-Y., Park, J., Hong, M., Lee, G. M., Baik, J. Y., Hong, J. K., 2023. Enhanced cell growth, production, and mAb quality produced in Chinese hamster ovary-K1 cells by supplementing polyamine in the media. Appl. Microbiol. Biotechnol. 107, 2855-2870.

Yeo, X. Y., Tan, L. Y., Chae, W. R., Lee, D.-Y., Lee, Y.-A., Wuestefeld, T., Jung, S., 2023. Liver’s influence on the brain through the action of bile acids. Front. Neurosci. 17,1123967. 

2022

Koduru, L., Lakshmanan, M., Lee, Y. Q., Ho, P.-L., Lim, P.-Y., Ler, W. X., Ng, S. K., Kim, D., Park, D.-S., Banu, M., Ow, D. S. W.* and Lee, D.-Y.*, 2022. Systematic evaluation of genome-wide metabolic landscapes in lactic acid bacteria reveals diet- and strain-specific probiotic idiosyncrasies. Cell Rep. 41(10), 111735.

Park, S.-Y., Choi, D.-H., Song, J., Park, U., Cho, H., Hong, B. H., Shozui, F., Silberberg, Y. R., Lee, D.-Y.*, 2022. Characterizing basal and feed media effects on mammalian cell cultures by systems engineering approaches. IFAC-PapersOnLine 55, 31-36.

Hong, J. K.†, Choi, D.-H.†, Park, S.-Y., Silberberg, Y. R., Shozui, F., Nakamurad, E., Kayahara, T., Lee, D.-Y.*, 2022. Data-driven and model-guided systematic framework for media development in CHO cell culture. Metab. Eng. 73, 114-123.

D'Souza, J. S.*, Ghag, S. B.*, Lee, D.-Y.*, 2022. Editorial: Heterologous protein expression and production platforms: the how, now and wow of it, Volume II. Front. Bioeng. Biotechnol. 10, 946381.

Yeo, H. C., Park, S.-Y., Tan, T., Ng, S. K., Lakshmanan, M., Lee, D.-Y.*, 2022. Combined multivariate statistical and flux balance analyses uncover media bottlenecks to the growth and productivity of CHO cell cultures. Biotechnol. Bioeng. 119, 1740-1754.

Koduru, L., Lakshmanan, M., Hoon, S., Lee, D.-Y., Lee, Y. K., Ow, D. S. W., 2022. Systems biology of gut microbiota-human receptor interactions: Toward anti-inflammatory probiotics. Front. Microbiol. 13, 846555.

2021

Song, H.-S., Lindemann, S. R., Lee, D.-Y., 2021. Editorial: Predictive modeling of human microbiota and their role in health and disease. Front. Microbiol. 12, 782871.

Lee, A. P., Kok, Y. J., Lakshmanan, M., Leong, D., Zheng, L., Lim, H. L., Chen, S., Mak, S. Y., Ang, K. S., Templeton, N., Salim, T., Wei, X., Gifford, E., Tan, A. H.-M., Bi, X., Ng, S. K., Lee, D.-Y.*, Ling, W. L.*, Ho, Y. S.*, 2021. Multi-omics profiling of a CHO cell culture system unravels the effect of culture pH on cell growth, antibody titer and product quality. Biotechnol. Bioeng. 118, 4305-4316.

Park, S.-Y., Park, C.-H., Choi, D.-H., Hong, J. K., Lee, D.-Y.*, 2021. Bioprocess digital twins of mammalian cell culture for advanced biomanufacturing. Curr. Opin. Chem. Eng. 33, 100702.

Sng, B. J. R., Mun, B., Mohanty, B., Kim, M., Phua, Z. W., Yang, H., Lee, D.-Y., Jang, I. C., 2021. Combination of red and blue light induces anthocyanin and other secondary metabolite biosynthesis pathways in an age-dependent manner in Batavia lettuce. Plant Sci. 310, 110977.

2020

Kim, S., Kim, J., Kim, N., Lee, D., Lee, H., Lee, D.-Y.*, Kim, KH*, 2020. Metabolomic elucidation of the effect of sucrose on the secondary metabolite profiles in Melissa officinalis by ultraperformance liquid chromatography-mass spectrometry. ACS Omega 5, 33186-33195.

Choi, Y. -M., Lee, Y. Q., Song, H.-S., Lee, D.-Y.*, 2020. Genome scale metabolic models and analysis for evaluating probiotic potentials. Biochem. Soc. Trans. 48, 1309-1321. 

Széliová, D., Ruckerbauer, D.E., Galleguillos, S.N., Petersen, L.B., Natter, K., Hanscho, M., Troyer, C., Causon, T., Schoeny, H., Christensen, H.B., Lee, D.-Y., Lewis, N. E., Koellensperger, G., Hann, S., Nielsen, L. K., Borth, N., Zanghellini, J., 2020. What CHO is made of: variations in the biomass composition of Chinese hamster ovary cell lines. Metab. Eng. 61, 288-300.

Seneviratne, C. J., Balan, P., Suriyanarayanan, T., Lakshmanan, M., Lee, D.-Y., Rho, M., Jakubovics, N., Brandt, B., Crielaard, W., Zaura, E., 2020. Oral microbiome-systemic studies: perspectives on current limitations and future artificial intelligence-based approaches. Crit. Rev. Microbiol. 46, 288-299.

Yeo, H. C., Hong, J., Lakshmanan, M.*, Lee, D.-Y.*, 2020. Enzyme capacity-based genome scale modelling of CHO cells. Metab. Eng. 60, 138-147.

Lee, N.-R., Lee, C. H., Lee, D.-Y.*, Park, J.-B.*, 2020. Genome-scale metabolic network reconstruction and in silico analysis of hexanoic acid producing Megasphaera elsdenii. Microorganisms 8, 539.

Lieven, C., Beber, M.E., Olivier, B.G., Bergmann, F.T., Ataman, M., Babaei, P., Bartell, J.A., Blank, L.M., Chauhan, S., Correia, K., Diener, C., Dräger, A., Ebert, B.E., Edirisinghe, J.N., Faria, J.P., Feist, A.M., Fengos, G., Fleming, R.M.T., García-Jiménez, B., Hatzimanikatis, V., van Helvoirt, W., Henry, C.S., Hermjakob, H., Herrgård, M.J., Kaafarani, A., Kim, H.U., King, Z., Klamt, S., Klipp, E., Koehorst, J.J., König, M., Lakshmanan, M., Lee, D.-Y., Lee, S.Y., Lee, S., Lewis, N.E., Liu, F., Ma, H., Machado, D., Mahadevan, R., Maia, P., Mardinoglu, A., Medlock, G.L., Monk, J.M., Nielsen, J., Nielsen, L.K., Nogales, J., Nookaew, I., Palsson, B.O., Papin, J.A., Patil, K.R., Poolman, M., Price, N.D., Resendis-Antonio, O., Richelle, A., Rocha, I., Sánchez, B.J., Schaap, P.J., Malik Sheriff, R.S., Shoaie, S., Sonnenschein, N., Teusink, B., Vilaça, P., Vik, J.O., Wodke, J.A.H., Xavier, J.C., Yuan, Q., Zakhartsev, M., Zhang, C., 2020. Memote for standardized genome-scale metabolic model testing. Nat. Biotechnol. 38, 272-276.

Koduru, L., Kim, H. Y., Lakshmanan, M., Mohanty, B., Lee, Y. Q., Lee, C. H.*, Lee, D.-Y.*, 2020. Genome-scale metabolic reconstruction and in silico analysis of rice leaf blight pathogen, Xanthomonas oryzae. Mol. Plant Pathol. 21, 527-540.

Hong, J. K., Yeo, H. C., Lakshmanan, M., Han, S. H., Cha, H. M., Han, M., Lee, D.-Y.*, 2020. In silico model-based characterization of metabolic response to harsh sparging stress in fed-batch CHO cell cultures. J. Biotechnol. 308, 10-20.

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. Front. Microbiol. 10, 3049.

2019

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. Front. Microbiol. 10, 1264. 

Lakshmanan, M., Kok, Y.J., Lee, A.P., Kyriakopoulos, S., Lim, H.L., Teo, G., Poh, S.L., Tang, W.Q., Hong, J., Tan, A.H.-M., Bi, X., Ho, Y.S., Zhang, P., Ng, S.K., Lee, D.-Y.*, 2019. Multi-omics profiling of CHO parental hosts reveals cell-line specific variations in bioprocessing traits. Biotechnol. Bioeng. 116, 2117–2129. 

Hong, J.K., Choi, H.-Y., Park, H.-R., Kim, D.-I.*, Lee, D.-Y.*, 2019.  Inhibition of autolysosome formation improves rrhGAA production driven by RAmy3D promoter in transgenic rice cell culture. Biotechnol. Bioprocess Eng. 24, 568–578. 

2018

Choi, H.-Y., Park, H., Hong, J.K., Kim, S.-D., Kwon, J.-Y., You, S., Do, J., Lee, D.-Y., Kim, H.H., Kim, D.-I., 2018. N-glycan remodeling using mannosidase inhibitors to increase terminal high-mannose glycans on acid α-glucosidase in transgenic rice cell cultures. Sci. Rep. 8, 16130. 

Koduru, L., Lakshmanan, M., Lee, D.-Y.*, 2018. In silico model-guided identification of transcriptional regulator targets for efficient strain design. Microb. Cell Fact. 17, 167. 

Ang, K.S., Lakshmanan, M., Lee, N.-R., Lee, D.-Y.*, 2018. Metabolic modeling of microbial community interactions for health, environmental and biotechnological applications. Curr. Genomics 19, 712–722. 

Hong, J.K., Lakshmanan, M., Goudar, C., Lee, D.-Y.*, 2018. Towards next generation cell line development and engineering by systems approaches. Curr. Opin. Chem. Eng. 22, 1–10. 

Kim, N.-H., Jayakodi, M., Lee, S.-C., Choi, B.-S., Jang, W., Lee, J., Kim, H.H., Waminal, N.E., Lakshmanan, M., van Nguyen, B., Lee, Y.S., Park, H.-S., Koo, H.J., Park, J.Y., Perumal, S., Joh, H.J., Lee, H., Kim, J., Kim, I.S., Kim, K., Koduru, L., Kang, K.B., Sung, S.H., Yu, Y., Park, D.S., Choi, D., Seo, E., Kim, S., Kim, Y.-C., Hyun, D.Y., Park, Y.-I., Kim, C., Lee, T.-H., Kim, H.U., Soh, M.S., Lee, Y., In, J.G., Kim, H.-S., Kim, Y.-M., Yang, D.-C., Wing, R.A., Lee, D.-Y.*, Paterson, A.H.*, Yang, T.-J.*, 2018. Genome and evolution of the shade-requiring medicinal herb Panax ginseng. Plant Biotechnol. J. 16, 1904–1917. 

Hong, J.K., Nargund, S., Lakshmanan, M., Kyriakopoulos, S., Kim, D.Y., Ang, K.S., Leong, D., Yang, Y., Lee, D.-Y.*, 2018. Comparative phenotypic analysis of CHO clones and culture media for lactate shift. J. Biotechnol. 283, 97–104. 

Yeo, H.C., Chen, S., Ho, Y.S., Lee, D.-Y.*, 2018. An LC–MS-based lipidomics pre-processing framework underpins rapid hypothesis generation towards CHO systems biotechnology. Metabolomics 14, 98. 

Woo, J.-M., Jeon, E.-Y., Seo, E.-J., Seo, J.-H., Lee, D.-Y., Yeon, Y.J., Park, J.-B., 2018. Improving catalytic activity of the Baeyer–Villiger monooxygenase-based Escherichia coli biocatalysts for the overproduction of (Z)-11-(heptanoyloxy)undec-9-enoic acid from ricinoleic acid. Sci. Rep. 8, 10280. 

Son, S.Y., Lee, S., Singh, D., Lee, N.-R., Lee, D.-Y., Lee, C.H., 2018. Comprehensive secondary metabolite profiling toward delineating the solid and submerged-state fermentation of Aspergillus oryzae KCCM 12698. Front. Microbiol. 9, 1076. 

Jayakodi, M., Choi, B.-S., Lee, S.-C., Kim, N.-H., Park, J.Y., Jang, W., Lakshmanan, M., Mohan, S.V.G., Lee, D.-Y., Yang, T.-J., 2018. Ginseng Genome Database: an open-access platform for genomics of Panax ginseng. BMC Plant Biol. 18, 62. 

Widiastuti, H., Lee, N.-R., Karimi, I.A., Lee, D.-Y.*, 2018. Genome-scale model-driven in silico analysis for enhanced production of succinic acid in Zymomonas mobilis. Processes 6, 30. 

Kyriakopoulos, S., Ang, K.S., Lakshmanan, M., Huang, Z., Yoon, S., Gunawan, R., Lee, D.-Y.*, 2018. Kinetic modelling of mammalian cell culture bioprocessing: the quest to advance biomanufacturing. Biotechnol. J. 13, e1700229. 

Mishra, P., Lee, N.-R., Lakshmanan, M., Kim, M., Kim, B.-G., Lee, D.-Y.*, 2018. Genome-scale model-driven strain design for dicarboxylic acid production in Yarrowia lipolytica. BMC Syst. Biol. 12, 12. 

2017

Koduru, L., Kim, Y., Bang, J., Lakshmanan, M., Han, N.S.*, Lee, D.-Y.*, 2017. Genome-scale modeling and transcriptome analysis of Leuconostoc mesenteroides unravel the redox governed metabolic states in obligate heterofermentative lactic acid bacteria. Sci. Rep. 7. 

Krishnamurthy, P., Mohanty, B., Wijaya, E., Lee, D.-Y., Lim, T.-M., Lin, Q., Xu, J., Loh, C.-S., Kumar, P.P., 2017. Transcriptomics analysis of salt stress tolerance in the roots of the mangrove Avicennia officinalis. Sci. Rep. 7, 10031. 

Huang, Z., Lee, D.-Y., Yoon, S., 2017. Quantitative intracellular flux modeling and applications in biotherapeutic development and production using CHO cell cultures. Biotechnol. Bioeng. 114, 2717–2728. [Cover page article].

Jeon, W., Priscilla, L., Park, G., Lee, H., Lee, N., Lee, D.-Y, Kwon, H., Ahn, I., Lee, C., Lee, H., Ahn, J., 2017. Complete genome sequence of the sulfur-oxidizing chemolithoautotrophic Sulfurovum lithotrophicum 42BKT. Stand. Genomic Sci. 12, 54. 

Jung, E.S., Park, H.M., Hyun, S.M., Shon, J.C., Lakshmanan, M., Noh, M., Yeo, H.C., Liu, K.-H., Lee, D.-Y., Hwang, J.S., Lee, C.H., 2017. Integrative metabolomic analysis reveals diet supplementation with green tea alleviates UVB-damaged mouse skin correlated with ascorbate metabolism and urea cycle. Metabolomics 13, 82. 

Yusufi, F.N.K., Lakshmanan, M., Ho, Y.S., Loo, B.L.W., Ariyaratne, P., Yang, Y., Ng, S.K., Tan, T.R.M., Yeo, H.C., Lim, H.L., Ng, S.W., Hiu, A.P., Chow, C.P., Wan, C., Chen, S., Teo, G., Song, G., Chin, J.X., Ruan, X., Sung, K.W.K., Hu, W.-S., Yap, M.G.S., Bardor, M., Nagarajan, N.*, Lee, D.-Y.*, 2017. Mammalian systems biotechnology reveals global cellular adaptions in a recombinant antibody-producing CHO cell line. Cell Syst 4, 530–542.e6. 

Bang, J., Li, L., Seong, H., Kwon, Y.W., Lee, D.-Y., Han, N.S., 2017. Macromolecular and Elemental Composition Analyses of Leuconostoc mesenteroides ATCC 8293 Cultured in a Chemostat. J. Microbiol. Biotechnol. 27, 939–942. 

Pek, H.B., Lim, P.Y., Liu, C., Lee, D.-Y., Bi, X., Wong, F.T., Ow, D.S.-W., 2017. Cytoplasmic expression of a thermostable invertase from Thermotoga maritima in Lactococcus lactis. Biotechnol. Lett. 39, 759–765.

Klement, M., Zheng, J., Liu, C., Tan, H.-L., Wong, V.V.T., Choo, A.B.-H., Lee, D.-Y.*, Ow, D.S.-W., 2017. Antibody engineering of a cytotoxic monoclonal antibody 84 against human embryonic stem cells: investigating the effects of multivalency on cytotoxicity. J. Biotechnol. 243, 29–37. 

Kim, M., Sun, G., Lee, D.-Y., Kim, B.-G., 2017. BeReTa: A systematic method for identifying target transcriptional regulators to enhance microbial production of chemicals. Bioinformatics 33, 87–94. 

Lee, Y.S., Park, H.-S., Lee, D.-K., Jayakodi, M., Kim, N.-H., Lee, S.-C., Kundu, A., Lee, D.-Y., Kim, Y.C., In, J.G., Kwon, S.W., Yang, T.-J., 2017. Comparative analysis of the transcriptomes and primary metabolite profiles of adventitious roots of five Panax ginseng cultivars. J. Ginseng Res. 41, 60–68. 

2016

Lakshmanan, M., Cheung, C.Y.M., Mohanty, B., Lee, D.-Y.*, 2016. Modeling rice metabolism: from elucidating environmental effects on cellular phenotype to guiding crop improvement. Front. Plant Sci. 7, 1795. 

Mohanty, B., Takahashi, H., de Los Reyes, B.G., Wijaya, E., Nakazono, M., Lee, D.-Y.*, 2016. Transcriptional regulatory mechanism of alcohol dehydrogenase 1-deficient mutant of rice for the cell survival under complete submergence. Rice 9, 51. 

Ahn, J., Jang, M.-J., Ang, K.S., Lee, H., Choi, E.-S., Lee, D.-Y.*, 2016. Codon optimization of Saccharomyces cerevisiae mating factor alpha prepro-leader to improve recombinant protein production in Pichia pastoris. Biotechnol. Lett. 38, 2137–2143. 

Yeo, H.C., Ting, S., Brena, R.M., Koh, G., Chen, A., Toh, S.Q., Lim, Y.M., Oh, S.K.W.*, Lee, D.-Y.*, 2016. Genome-wide transcriptome and binding sites analyses identify early FOX expressions for enhancing cardiomyogenesis efficiency of hESC cultures. Sci. Rep. 6, 31068. 

Yu, N., Kang, J.-S., Chang, C.-C., Lee, T.-Y., Lee, D.-Y.*, 2016. Robust economic optimization and environmental policy analysis for microgrid planning: an application to Taichung Industrial Park, Taiwan. Energy 113, 671–682. 

Hefzi, H., Ang, K.S., Hanscho, M., Bordbar, A., Ruckerbauer, D., Lakshmanan, M., Orellana, C.A., Baycin-Hizal, D., Huang, Y., Ley, D., Martinez, V.S., Kyriakopoulos, S., Jiménez, N.E., Zielinski, D.C., Quek, L.-E., Wulff, T., Arnsdorf, J., Li, S., Lee, J.S., Paglia, G., Loira, N., Spahn, P.N., Pedersen, L.E., Gutierrez, J.M., King, Z.A., Lund, A.M., Nagarajan, H., Thomas, A., Abdel-Haleem, A.M., Zanghellini, J., Kildegaard, H.F., Voldborg, B.G., Gerdtzen, Z.P., Betenbaugh, M.J., Palsson, B.O., Andersen, M.R., Nielsen, L.K., Borth, N.*, Lee, D.-Y.*, Lewis, N.E.*, 2016. A consensus genome-scale reconstruction of Chinese hamster ovary cell metabolism. Cell Syst 3, 434–443.e8. 

Swainston, N., Smallbone, K., Hefzi, H., Dobson, P.D., Brewer, J., Hanscho, M., Zielinski, D.C., Ang, K.S., Gardiner, N.J., Gutierrez, J.M., Kyriakopoulos, S., Lakshmanan, M., Li, S., Liu, J.K., Martínez, V.S., Orellana, C.A., Quek, L.-E., Thomas, A., Zanghellini, J., Borth, N., Lee, D.-Y., Nielsen, L.K., Kell, D.B., Lewis, N.E., Mendes, P., 2016. Recon 2.2: from reconstruction to model of human metabolism. Metabolomics 12, 109. 

Mohanty, B., Lakshmanan, M., Lim, S.-H., Kim, J.K., Ha, S.-H., Lee, D.-Y.*, 2016. Light-specific transcriptional regulation of the accumulation of carotenoids and phenolic compounds in rice leaves. Behav. 11, e1184808. 

Sha, S., Agarabi, C., Brorson, K., Lee, D.-Y., Yoon, S., 2016. N-glycosylation design and control of therapeutic monoclonal antibodies. Trends Biotechnol. 34, 835–846. [Cover page article].

Mishra, P., Park, G.-Y., Lakshmanan, M., Lee, H.-S., Lee, H., Chang, M.W., Ching, C.B., Ahn, J.*, Lee, D.-Y.*, 2016. Genome-scale metabolic modeling and in silico analysis of lipid accumulating yeast Candida tropicalis for dicarboxylic acid production. Biotechnol. Bioeng. 113, 1993–2004. 

Ang, K.S., Kyriakopoulos, S., Li, W., Lee, D.-Y.*, 2016. Multi-omics data driven analysis establishes reference codon biases for synthetic gene design in microbial and mammalian cells. Methods 102, 26–35. [Special Issue: Pan-omics analysis of biological data, invited]

Mohanty, B., Kitazumi, A., Cheung, C.Y.M., Lakshmanan, M., de Los Reyes, B.G., Jang, I.-C., Lee, D.-Y.*, 2016. Identification of candidate network hubs involved in metabolic adjustments of rice under drought stress by integrating transcriptome data and genome-scale metabolic network. Plant Sci. 242, 224–239. [Special Issue: From Genomics to Breeding, invited]

Kim, M., Yi, J.S., Lakshmanan, M., Lee, D.-Y.*, Kim, B.-G.*, 2016. Transcriptomics-based strain optimization tool for designing secondary metabolite overproducing strains of Streptomyces coelicolor. Biotechnol. Bioeng. 113, 651–660. 

Yeo, H.C., Chung, B.K.-S., Chong, W., Chin, J.X., Ang, K.S., Lakshmanan, M., Ho, Y.S., Lee, D.-Y.*, 2015. A genetic algorithm-based approach for pre-processing metabolomics and lipidomics LC-MS data. Metabolomics 12, 5. 

2015

Lakshmanan, M., Lim, S.-H., Mohanty, B., Kim, J.K., Ha, S.-H.*, Lee, D.-Y.*, 2015. Unraveling the light-specific metabolic and regulatory signatures of rice through combined in silico modeling and multi-omics analysis. Plant Physiol. 169, 3002–3020. 

Lakshmanan, M., Kim, T.Y., Chung, B.K.S., Lee, S.Y., Lee, D.-Y.*, 2015. Flux-sum analysis identifies metabolite targets for strain improvement. BMC Syst. Biol. 9, 73. 

Liu, C., Chin, J.X., Lee, D.-Y.*, 2015. SynLinker: an integrated system for designing linkers and synthetic fusion proteins. Bioinformatics 31, 3700–3702. 

Lakshmanan, M., Yu, K., Koduru, L., Lee, D.-Y.*, 2015. In silico model-driven cofactor engineering strategies for improving the overall NADP(H) bioavailability in microbial cell factories. J. Ind. Microbiol. Biotechnol. 42, 1401–1414. 

Kwok, J.J.M., Lee, D.-Y.*, 2015. Coopetitive supply chain relationship model: application to the smartphone manufacturing network. PLoS One 10, e0132844. 

Chen, B., Lee, D.-Y., Chang, M.W., 2015. Combinatorial metabolic engineering of Saccharomyces cerevisiae for terminal 2 alkene production. Metab. Eng. 31, 53–61. 

Yu, N., Dieu, L.T.J., Harvey, S., Lee, D.-Y.*, 2015. Optimization of process configuration and strain selection for microalgae-based biodiesel production. Bioresour. Technol. 193, 25–34. 

Pek, H.B., Klement, M., Ang, K.S., Chung, B.K.-S., Ow, D.S.-W., Lee, D.-Y.*, 2015. Exploring codon context bias for synthetic gene design of a thermostable invertase in Escherichia coli. Enzyme Microb. Technol. 75-76, 57–63. 

Klement, M., Liu, C., Loo, B.L.W., Choo, A.B.-H., Ow, D.S.-W., Lee, D.-Y.*, 2015. Effect of linker flexibility and length on the functionality of a cytotoxic engineered antibody fragment. J. Biotechnol. 199, 90–97. 

de Los Reyes, B.G., Mohanty, B., Yun, S.J., Park, M.-R., Lee, D.-Y.*, 2015. Upstream regulatory architecture of rice genes: Summarizing the baseline towards genus-wide comparative analysis of regulatory networks and allele mining. Rice 8, 14. [Highly accessed]

Vishwanathan, N., Yongky, A., Johnson, K.C., Fu, H.-Y., Jacob, N.M., Le, H., Yusufi, F.N.K., Lee, D.-Y., Hu, W.-S., 2015. Global insights into the Chinese hamster and CHO cell transcriptomes. Biotechnol. Bioeng. 112, 965–976. [Spotlighted article]

Yu, K., Liu, C., Kim, B.-G., Lee, D.-Y.*, 2015. Synthetic fusion protein design and applications. Biotechnol. Adv. 33, 155–164. 

2014

Lakshmanan, M., Mohanty, B., Lim, S.-H., Ha, S.-H., Lee, D.-Y.*, 2014. Metabolic and transcriptional regulatory mechanisms underlying the anoxic adaptation of rice coleoptile. AoB Plants 6. 

Loh, W.P., Loo, B., Zhou, L., Zhang, P., Lee, D.-Y., Yang, Y., Lam, K.P., 2014. Overexpression of microRNAs enhances recombinant protein production in Chinese hamster ovary cells. Biotechnol. J. 9, 1140–1151. 

Lee, N.-R., Lakshmanan, M., Aggarwal, S., Song, J.-W., Karimi, I.A., Lee, D.-Y.*, Park, J.-B., 2014. Genome-scale metabolic network reconstruction and in silico flux analysis of the thermophilic bacterium Thermus thermophilus B27. Microb. Cell Fact. 13, 61. 

Chin, J.X., Chung, B.K.-S., Lee, D.-Y.*, 2014. Codon Optimization On-Line (COOL): a web-based multi-objective optimization platform for synthetic gene design. Bioinformatics 30, 2210–2212. 

Park, S.-J., Yeo, H.C., Kang, N.-Y., Kim, H., Lin, J., Ha, H.-H., Vendrell, M., Lee, J.-S., Chandran, Y., Lee, D.-Y.*, Yun, S.-W., Chang, Y.-T., 2014. Mechanistic elements and critical factors of cellular reprogramming revealed by stepwise global gene expression analyses. Stem Cell Res. 12, 730–741. 

Courtes, F.C., Gu, C., Wong, N.S.C., Dedon, P.C., Yap, M.G.S., Lee, D.-Y.*, 2014. 28S rRNA is inducibly pseudouridylated by the mTOR pathway in CHO cell cultures. J. Biotechnol. 174, 16–21. 

Courtes, F.C., Vardy, L., Wong, N.S.C., Bardor, M., Yap, M.G.S., Lee, D.-Y.*, 2014. Understanding translational control mechanisms of the mTOR pathway in CHO cells by polysome profiling. N. Biotechnol. 31, 514–523. 

Lakshmanan, M., Koh, G., Chung, B.K.S., Lee, D.-Y.*, 2014. Software applications for flux balance analysis. Brief. Bioinform. 15, 108–122. 

2013

Lakshmanan, M., Chung, B.K.-S., Liu, C., Kim, S.-W., Lee, D.-Y.*, 2013. Cofactor modification analysis: a computational framework to identify cofactor specificity engineering targets for strain improvement. J. Bioinform. Comput. Biol. 11, 1343006. 

Lakshmanan, M., Mohanty, B., Lee, D.-Y.*, 2013. Identifying essential genes/reactions of the rice photorespiration by in silico model-based analysis. Rice 6, 20. 

Chung, B.K.-S., Yusufi, F.N.K., Mariati, Yang, Y., Lee, D.-Y.*, 2013. Enhanced expression of codon optimized interferon gamma in CHO cells. J. Biotechnol. 167, 326–333. 

Courtes, F.C., Lin, J., Lim, H.L., Ng, S.W., Wong, N.S.C., Koh, G., Vardy, L., Yap, M.G.S., Loo, B., Lee, D.-Y.*, 2013. Translatome analysis of CHO cells to identify key growth genes. J. Biotechnol. 167, 215–224. 

Lakshmanan, M., Zhang, Z., Mohanty, B., Kwon, J.-Y., Choi, H.-Y., Nam, H.-J., Kim, D.-I., Lee, D.-Y.*, 2013. Elucidating the rice cells metabolism under flooding and drought stresses using flux-based modelling and analysis. Plant Physiol. 162, 2140–2150. 

Chung, B.K.-S., Dick, T., Lee, D.-Y.*, 2013. In silico analyses for the discovery of tuberculosis drug targets. J. Antimicrob. Chemother. 68, 2701–2709. 

Lee, T.S., Ho, Y.S., Yeo, H.C., Lin, J.P.Y., Lee, D.-Y.*, 2013. Precursor mass prediction by clustering ionization products in LC-MS-based metabolomics. Metabolomics 9, 1301–1310. 

Chung, B.K.-S., Lakshmanan, M., Klement, M., Ching, C.B., Lee, D.-Y.*, 2013. Metabolic reconstruction and flux analysis in Pichia yeasts. Appl. Microbiol. Biotechnol. 97, 1865–1873. [Invited Min-Review]

Chung, B.K.-S., Lakshmanan, M., Klement, M., Mohanty, B., Lee, D.-Y.*, 2013. Genome-scale in silico modeling and analysis for designing synthetic terpenoid-producing microbial cell factories. Chem. Eng. Sci. 103, 100–108. [Special Issue: Synthetic Biology, invited]

Ming Kwok, J.J., Yu, N., Karimi, I.A., Lee, D.-Y.*, 2013. Microgrid scheduling for reliable, cost effective and environmentally friendly management. Ind. Eng. Chem. Res. 52, 142–151. 

2012

Chung, B.K.-S., Lee, D.-Y.*, 2012. Computational codon optimization of synthetic gene for protein expression. BMC Syst. Biol. 6, 134.

Mohanty, B., Herath, V., Wijaya, E., Yeo, H.C., de Los Reyes, B.G., Lee, D.-Y.*, 2012. Patterns of cis-element enrichment reveal potential regulatory modules involved in the transcriptional regulation of anoxia response of japonica rice. Gene 511, 235–242.

Kim, Y.J., Eom, H.-J., Seo, E.-Y., Lee, D.-Y., Kim, J.H., Han, N.S., 2012. Development of a chemically defined minimal medium for the exponential growth of Leuconostoc mesenteroides ATCC8293. J. Microbiol. Biotechnol. 22, 1518–1522. 

Aggarwal, S., Karimi, I.A., Kilbane, J.J., Ii, Lee, D.-Y., 2012. Roles of sulfite oxidoreductase and fulfite reductase in improving desulfurization by Rhodococcus erythropolis. Mol. Biosyst. 8, 2724–2732. 

Chong, W.P.K., Thng, S.H., Hiu, A.P., Lee, D.-Y., Chan, E.C.Y., Ho, Y.S., 2012. LC-MS-based metabolic characterization of high monoclonal antibody-producing Chinese hamster ovary cells. Biotechnol. Bioeng. 109, 3103–3111. 

Selvarasu, S., Ho, Y.S., Chong, W.P.K., Wong, N.S.C., Yusufi, F.N.K., Lee, Y.Y., Yap, M.G.S., Lee, D.-Y.*, 2012. Combined in silico modeling and metabolomics analysis to characterize fed-batch CHO cell culture. Biotechnol. Bioeng. 109, 1415–1429.  [Special Issue: CHO Cell Genomics, invited] [Highlighted as Top 25 most accessed article from Jan-Dec 2012]

Wu, S.M., Tan, K.S., Chen, H., Beh, T.T., Yeo, H.C., Ng, S.K.-L., Wei, S., Lee, D.-Y., Choo, A.B.-H., Chan, K.K.-K., 2012. Enhanced production of neuroprogenitors, dopaminergic neurons and identification of target genes by overexpression of Sonic hedgehog in human embryonic stem cells. Stem Cells Dev. 21, 729–741. 

Kang, J.-S., Lee, T.-Y., Lee, D.-Y., 2012. Robust optimization for engineering design. Eng. Optim. 44, 175–194. 

2011

Yeo, H.C., Beh, T.T., Quek, J.J.L., Koh, G., Chan, K.K.K., Lee, D.-Y.*, 2011. Integrated transcriptome and binding sites analysis implicates E2F in the regulation of self-renewal in human pluripotent stem cells. PLoS One 6, e27231. 

Koh, G., Low, A., Poh, D., Yao, Y., Ng, S.K., Wong, V.V.T., Vagenende, V., Lam, K.-P., Lee, D.-Y.*, 2011. Integrative analysis workflow for the structural and functional classification of C-type lectins. BMC Bioinformatics 12 Suppl 14, S5. 

Aggarwal, S., Karimi, I.A.*, Lee, D.-Y.*, 2011. Reconstruction of a genome-scale metabolic network of Rhodococcus erythropolis for desulfurization studies. Mol. Biosyst. 7, 3122–3131. 

Ahn, J., Chung, B.K.S., Lee, D.-Y.*, Park, M., Karimi, I.A., Jung, J.-K., Lee, H., 2011.  NADPH-dependent pgi-gene knockout Escherichia coli metabolism producing shikimate on different carbon sources. FEMS Microbiol. Lett. 324, 10–16. 

Naraharisetti, P.K., Karimi, I.A., Anand, A., Lee, D.-Y., 2011. A linear diversity constraint – application to scheduling in microgrids. Energy 36, 4235–4243. 

Koh, G., Lee, D.-Y.*, 2011. Mathematical modeling and sensitivity analysis of the integrated TNFa-mediated apoptotic pathway for identifying key regulators. Comput. Biol. Med. 41, 512–528. 

Ding, V.M.Y., Boersema, P.J., Foong, L.Y., Preisinger, C., Koh, G., Natarajan, S., Lee, D.-Y., Boekhorst, J., Snel, B., Lemeer, S., Heck, A.J.R., Choo, A., 2011. Tyrosine phosphorylation profiling in FGF-2 stimulated human embryonic stem cells. PLoS One 6, e17538. 

Chong, W.P.K., Yusufi, F.N.K., Lee, D.-Y., Reddy, S.G., Wong, N.S.C., Heng, C.K., Yap, M.G.S., Ho, Y.S., 2011. Metabolomics-based identification of apoptosis-inducing metabolites in fed-batch CHO culture media. J. Biotechnol. 151, 218–224. 

Aggarwal, S., Karimi, I.A., Lee, D.Y., 2011. Flux-based analysis of sulfur metabolism in desulfurizing strains of Rhodococcus erythropolis. FEMS Microbiol. Lett. 315, 115–121. 

Widiastuti, H., Kim, J.Y., Selvarasu, S., Karimi, I.A., Kim, H., Seo, J.-S., Lee, D.-Y.*, 2011. Genome-scale modeling and in silico analysis of ethanologenic bacteria Zymomonas mobilis. Biotechnol. Bioeng. 108, 655–665. 

Lee, D.-Y.*, Chung, B.K.S., Yusufi, F.N.K., Selvarasu, S., 2011.  In silico genome-scale modeling and analysis for identifying anti-tubercular drug targets. Drug Dev. Res. 72, 121–129.  [Special Issue: In Silico Tools in Drug Design, invited]

2010

Selvarasu, S., Kim, D.Y., Karimi, I.A., Lee, D.-Y.*, 2010. Combined data preprocessing and multivariate statistical analysis characterizes fed-batch culture of mouse hybridoma cells for rational medium design. J. Biotechnol. 150, 94–100. 

Chung, B.K., Selvarasu, S., Andrea, C., Ryu, J., Lee, H., Ahn, J., Lee, H., Lee, D.-Y.*, 2010. Genome-scale metabolic reconstruction and in silico analysis of methylotrophic yeast Pichia pastoris for strain improvement. Microb. Cell Fact. 9, 50. [Highly accessed].

Chong, W.P.K., Reddy, S.G., Yusufi, F.N.K., Lee, D.-Y., Wong, N.S.C., Heng, C.K., Yap, M.G.S., Ho, Y.S., 2010. Metabolomics-driven approach for the improvement of Chinese hamster ovary cell growth: overexpression of malate dehydrogenase II. J. Biotechnol. 147, 116–121. 

Lee, F.C., Pandu Rangaiah, G., Lee, D.-Y., 2010. Modeling and optimization of a multi-product biosynthesis factory for multiple objectives. Metab. Eng. 12, 251–267. 

Chin, J., Koh, G., Lee, D.-Y.*, 2010. How necessary is a fast testkit for mitigation of pandemic flu? J. R. Soc. Interface 7, 1033–1047. 

Selvarasu, S., Karimi, I.A., Ghim, G.-H., Lee, D.-Y.*, 2010. Genome-scale modeling and in silico analysis of mouse metabolic network. Mol. Biosyst. 6, 152–161. [Cover page article] [Highly accessed].

2009

Chung, B.K.S., Lee, D.-Y.*, 2009. Flux-sum analysis: a metabolite-centric approach for understanding the metabolic network. BMC Syst. Biol. 3, 117. [Highly accessed].

Chong, W.P.K., Goh, L.T., Reddy, S.G., Yusufi, F.N.K., Lee, D.Y., Wong, N.S.C., Heng, C.K., Yap, M.G.S., Ho, Y.S., 2009. Metabolomics profiling of extracellular metabolites in recombinant Chinese hamster ovary fed-batch culture. Rapid Commun. Mass Spectrom. 23, 3763–3771. 

Kharkwal, S., Karimi, I.A., Chang, M.W., Lee, D.-Y.*, 2009. Strain improvement and process development for biobutanol production. Recent Pat. Biotechnol. 3, 202–210. [Invited review].

Kim, P.-J., Lee, D.-Y.*, Jeong, H.*, 2009. Centralized modularity in mammalian N-glycosylation pathways. PLoS One 4, e7317. 

Jung, T.-S., Yeo, H.C., Reddy, S.G., Cho, W.-S., Lee, D.-Y.*, 2009. WEbcoli: an interactive and asynchronous web-based system for in silico design and analysis of genome-scale E. coli model.  Bioinformatics 25, 2850–2852. 

Oh, Y.-G., Lee, D.-Y., Lee, S.Y., Park, S., 2009. Multiobjective flux balancing using the NISE method for metabolic network analysis. Biotechnol. Prog. 25, 999–1008. 

Selvarasu, S., Wong, V.V.T., Karimi, I.A., Lee, D.-Y.*, 2009. Elucidation of metabolism in hybridoma cells grown in fed-batch culture by genome-scale modeling. Biotechnol. Bioeng. 102, 1494–1504. 

Selvarasu, S., Ow, D.S.-W., Lee, S.Y., Lee, M.M., Oh, S.K.-W., Karimi, I.A., Lee, D.-Y.*, 2009. Characterizing Escherichia coli DH5α growth and metabolism in complex media using genome-scale flux analysis. Biotechnol. Bioeng. 102, 923–934. 

Ow, D.S.-W., Lee, D.-Y.*, Yap, M.G.-S., Oh, S.K.-W., 2009. Identification of cellular objective for elucidating the physiological state of plasmid-bearing Escherichia coli using genome-scale in silico analysis. Biotechnol. Prog. 25, 61–67. 

Yusufi, F.N.K., Park, W., Lee, M.M., Lee, D.-Y.*, 2009. An alpha-numeric code for representing N-linked glycan structures in secreted glycoproteins. Bioprocess Biosyst. Eng. 32, 97–107. 

Lee, D.-Y.*, Saha, R., Yusufi, F.N.K., Park, W., Karimi, I.A., 2009. Web-based applications for building, managing and analyzing kinetic models of biological systems. Brief. Bioinform. 10, 65–74. 

2001~2008

2008

Ahn, J.O., Lee, H.W., Saha, R., Park, M.S., Jung, J.-K., Lee, D.-Y.*, 2008. Exploring the effects of carbon sources on the metabolic capacity for shikimic acid production in Escherichia coli using in silico metabolic predictions. J. Microbiol. Biotechnol. 18, 1773–1784. 

2007

Kim, P.-J#., Lee, D.-Y.#, Kim, T.Y., Lee, K.H., Jeong, H., Lee, S.Y., Park, S., 2007. Metabolite-essentiality elucidates robustness of Escherichia coli metabolism. Proc. Natl. Acad. Sci. U. S. A. 104, 13638–13642.

Choi, H.S., Kim, T.Y., Lee, D.-Y., Lee, S.Y., 2007. Incorporating metabolic flux ratios into constraint-based flux analysis by using artificial metabolites and converging ratio determinants. J. Biotechnol. 129, 696–705. 

2006

Lee, D.-Y., Yun, C., Cho, A., Hou, B.K., Park, S., Lee, S.Y., 2006. WebCell: a web-based environment for kinetic modeling and dynamic simulation of cellular networks. Bioinformatics 22, 1150–1151. 

Lee, D.-Y., Zimmer, R., Lee, S.Y., Park, S., 2006. Colored Petri net modeling and simulation of signal transduction pathways. Metab. Eng. 8, 112–122. 

2005

Fan, L.-T., Shafie, S., Bertók, B., Friedler, F., Lee, D.-Y., Seo, H., Park, S. W., Lee, S. Y., 2005. Graph-theoretic approach for identifying catalytic or metabolic pathways. J. Chin. Inst. Eng., 28, 1021-1037.

Lee, S.J.#, Lee, D.-Y.#, Kim, T.Y., Kim, B.H., Lee, J., Lee, S.Y., 2005. Metabolic engineering of Escherichia coli for the enhanced production of succinic acid based on genome comparison and in silico gene knock-out simulation. Appl. Environ. Microbiol. 71, 7880–7887. (#Equally contributed authors)

Lee, S.Y., Woo, H.M., Lee, D.-Y., Choi, H.S., Kim, T.Y., Yun, H., 2005. Systems-level analysis of genome-scale in silico metabolic models using MetaFluxNet. Biotechnol. Bioprocess Eng. 10, 425. 

Yun, H., Lee, D.-Y., Jeong, J., Lee, S., Lee, S.Y., 2005. MFAML: a standard data structure for representing and exchanging metabolic flux models. Bioinformatics 21, 3329–3330. 

Lee, S.Y., Lee, D.-Y., Kim, T.Y., 2005. Systems biotechnology for strain improvement. Trends Biotechnol. 23, 349–358. 

Lee, D.-Y., Fan, L.T., Park, S., Lee, S.Y., Shafie, S., Bertók, B., Friedler, F., 2005. Complementary identification of multiple flux distributions and multiple metabolic pathways. Metab. Eng. 7, 182–200. 

2004

Hou, B.K., Kim, J.S., Jun, J.H., Lee, D.-Y., Kim, Y.W., Chae, S., Roh, M., In, Y.-H., Lee, S.Y., 2004. BioSilico: an integrated metabolic database system. Bioinformatics 20, 3270–3272. 

Lee, D.-Y., Sung, S.W., Lee, S.Y., Park, S., 2004. Combined deterministic-stochastic approach for pharmacokinetic modeling. Ind. Eng. Chem. Res. 43, 1133–1143. 

2003

Lee, D.-Y.*, Yun, H., Park, S., Lee, S.Y., 2003. MetaFluxNet: the management of metabolic reaction information and quantitative metabolic flux analysis. Bioinformatics 19, 2144–2146. 

Lee, D.-Y., Lee, M., Lee, Y., Park, S., 2003. MP criterion-based multiloop PID controllers tuning for desired closed loop responses. Korean J. Chem. Eng. 20, 8–13. 

2002

Song, J., Park, H., Lee, D.-Y., Park, S., 2002. Scheduling of actual size refinery processes considering environmental impacts with multiobjective optimization. Ind. Eng. Chem. Res. 41, 4794–4806. 

2001

Seo, H., Lee, D.-Y., Park, S., Fan, L.T., Shafie, S., Bertók, B., Friedler, F., 2001. Graph-theoretical identification of pathways for biochemical reactions. Biotechnol. Lett. 23, 1551–1557.