The metabolic engineering community relies on computational methods for pathway design
to produce important small molecules in microbial hosts. Metabolic network databases are …

Microbial catalysts must partition incoming substrate between the synthesis of biomass and
the synthesis of a desired product. Although biomass synthesis generates more catalyst and …

Plant natural products (PNPs) and their derivatives are important but underexplored sources
of pharmaceutical molecules. To access this untapped potential, the reconstitution of …

Stoichiometric genome-scale metabolic network models (GEMs) have been widely used to
predict metabolic phenotypes. In addition to stoichiometric ratios, other constraints such as …

Retro-biosynthetic approaches have made significant advances in predicting synthesis
routes of target biofuel, bio-renewable or bio-active molecules. The use of only cataloged …

Metabolic “dark matter” describes currently unknown metabolic processes, which form a
blind spot in our general understanding of metabolism and slow down the development of …

基于约束的基因组尺度代谢网络模型(genome-scale metabolic models, GEMs)
分析已被广泛应用于代谢表型的预测. 而实际细胞中代谢速率除计量学约束外 …

Group contribution (GC) methods are conventionally used in thermodynamics analysis of
metabolic pathways to estimate the standard Gibbs energy change (Δ r G′ o) of enzymatic …

The heterogeneity of the aromatic products originating from lignin catalytic depolymerization
remains one of the major challenges associated with lignin valorization. Microbes have …

Metabolic pathway prediction and reconstruction play crucial roles in solving fundamental
and applied biomedical problems. In the case of fundamental research, annotation of …