van Lent P, Schmitz J, Abeel T. Simulated Design-Build-Test-Learn Cycles for Consistent Comparison of Machine Learning Methods in Metabolic Engineering. ACS synthetic biology. 2023. doi:10.1021/acssynbio.3c00186
Zhou HL, Zhang R, Anand P, et al. Metabolic reprogramming by the S-nitroso-CoA reductase system protects against kidney injury. Nature. 2019;565(7737):96-100. doi:10.1038/s41586-018-0749-z
Johns NI, Gomes ALC, Yim SS, et al. Metagenomic mining of regulatory elements enables programmable species-selective gene expression. Nat Methods. 2018;15(5):323-329. doi:10.1038/nmeth.4633
Woolston BM, Roth T, Kohale I, Liu DR, Stephanopoulos G. Development of a formaldehyde biosensor with application to synthetic methylotrophy. Biotechnol Bioeng. 2018;115(1):206-215. doi:10.1002/bit.26455
Young EM, Zhao Z, Gielesen BEM, et al. Iterative algorithm-guided design of massive strain libraries, applied to itaconic acid production in yeast. Metab Eng. 2018;48:33-43. doi:10.1016/j.ymben.2018.05.002
Krueger AS, Munck C, Dantas G, et al. Simulating Serial-Target Antibacterial Drug Synergies Using Flux Balance Analysis. PLoS One. 2016;11(1):e0147651. doi:10.1371/journal.pone.0147651