Shangzhong Li, Ph.D.

2012-2019 Bioengineering University of California, San Diego, La Jolla, CA 
"Shangzhong Li"
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Fouladiha H, Marashi SA, Li S, et al. (2020) Systematically gap-filling the genome-scale metabolic model of CHO cells. Biotechnology Letters
Joshi CJ, Schinn SM, Richelle A, et al. (2020) StanDep: Capturing transcriptomic variability improves context-specific metabolic models. Plos Computational Biology. 16: e1007764
Courchesne E, Gazestani VH, Lewis NE. (2020) Prenatal Origins of ASD: The When, What, and How of ASD Development. Trends in Neurosciences. 43: 326-342
Gutierrez JM, Feizi A, Li S, et al. (2020) Genome-scale reconstructions of the mammalian secretory pathway predict metabolic costs and limitations of protein secretion. Nature Communications. 11: 68
Gazestani VH, Lewis NE. (2019) From Genotype to Phenotype: Augmenting Deep Learning with Networks and Systems Biology. Current Opinion in Systems Biology. 15: 68-73
Julie la Cour Karottki K, Hefzi H, Xiong K, et al. (2019) Awakening dormant glycosyltransferases in CHO cells with CRISPRa. Biotechnology and Bioengineering
Richelle A, Joshi C, Lewis NE. (2019) Assessing key decisions for transcriptomic data integration in biochemical networks. Plos Computational Biology. 15: e1007185
Chiang AWT, Li S, Kellman BP, et al. (2019) Combating viral contaminants in CHO cells by engineering innate immunity. Scientific Reports. 9: 8827
Li S, Cha SW, Hefner K, et al. (2019) Proteogenomic annotation of the Chinese hamster reveals extensive novel translation events and endogenous retroviral elements. Journal of Proteome Research
Richelle A, Chiang AWT, Kuo CC, et al. (2019) Increasing consensus of context-specific metabolic models by integrating data-inferred cell functions. Plos Computational Biology. 15: e1006867
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