Third-generation biorefineries as the means to produce fuels and chemicals from CO2
Concerns regarding petroleum depletion and global climate change caused by greenhouse
gas emissions have spurred interest in renewable alternatives to fossil fuels. Third …
gas emissions have spurred interest in renewable alternatives to fossil fuels. Third …
Yeast systems biology: model organism and cell factory
J Nielsen - Biotechnology journal, 2019 - Wiley Online Library
For thousands of years, the yeast Saccharomyces cerevisiae (S. cerevisiae) has served as a
cell factory for the production of bread, beer, and wine. In more recent years, this yeast has …
cell factory for the production of bread, beer, and wine. In more recent years, this yeast has …
Combining mechanistic and machine learning models for predictive engineering and optimization of tryptophan metabolism
Through advanced mechanistic modeling and the generation of large high-quality datasets,
machine learning is becoming an integral part of understanding and engineering living …
machine learning is becoming an integral part of understanding and engineering living …
Controlling gene expression with deep generative design of regulatory DNA
Abstract Design of de novo synthetic regulatory DNA is a promising avenue to control gene
expression in biotechnology and medicine. Using mutagenesis typically requires screening …
expression in biotechnology and medicine. Using mutagenesis typically requires screening …
A consensus S. cerevisiae metabolic model Yeast8 and its ecosystem for comprehensively probing cellular metabolism
Genome-scale metabolic models (GEMs) represent extensive knowledgebases that provide
a platform for model simulations and integrative analysis of omics data. This study …
a platform for model simulations and integrative analysis of omics data. This study …
Improving the phenotype predictions of a yeast genome‐scale metabolic model by incorporating enzymatic constraints
Genome‐scale metabolic models (GEM s) are widely used to calculate metabolic
phenotypes. They rely on defining a set of constraints, the most common of which is that the …
phenotypes. They rely on defining a set of constraints, the most common of which is that the …
Deep learning suggests that gene expression is encoded in all parts of a co-evolving interacting gene regulatory structure
Understanding the genetic regulatory code governing gene expression is an important
challenge in molecular biology. However, how individual coding and non-coding regions of …
challenge in molecular biology. However, how individual coding and non-coding regions of …
Recent advances in metabolic engineering of Saccharomyces cerevisiae: new tools and their applications
Metabolic engineering aims to develop efficient cell factories by rewiring cellular
metabolism. As one of the most commonly used cell factories, Saccharomyces cerevisiae …
metabolism. As one of the most commonly used cell factories, Saccharomyces cerevisiae …
Turnover number predictions for kinetically uncharacterized enzymes using machine and deep learning
The turnover number k cat, a measure of enzyme efficiency, is central to understanding
cellular physiology and resource allocation. As experimental k cat estimates are unavailable …
cellular physiology and resource allocation. As experimental k cat estimates are unavailable …
Unification of protein abundance datasets yields a quantitative Saccharomyces cerevisiae proteome
Protein activity is the ultimate arbiter of function in most cellular pathways, and protein
concentration is fundamentally connected to protein action. While the proteome of yeast has …
concentration is fundamentally connected to protein action. While the proteome of yeast has …