Harnessing Artificial Intelligence for Predictive Biocatalysis We are advancing the field of predictive biocatalysis through cutting-edge machine learning approaches. Our team (BRS team at MICALIS,
In a recently published article in iScience, researchers from the University of Paris-Saclay and the University of Lyon 1 have developed a software suite to
Constraint-based metabolic models have been used for decades to predict the phenotype of microorganisms in different environments. However, quantitative predictions are limited unless labor-intensive measurements
We believe that the synthetic biology and metabolic engineering communities need to be provided with easily acessible and usable computational tools enabling them to apply
Cell-free lysates are a major platform for in vitro protein production but batch-to-batch variation makes production difficult to predict. A research team from the Micalis
Metabolic engineering aims to produce chemicals of interest from living organisms, to advance toward greener chemistry. Despite efforts, the research and development process is still
While machine learning methods are used in many areas, including human health, interfacing these methods with the living world has been little explored at the
Synthetic biology is the field of engineering biology inspired by engineering in computation, standardization, and construction to develop new devices composed of biological parts. Cell-free
RetroRules is a database of reaction rules for metabolic engineering (https://retrorules.org). Reaction rules are generic descriptions of chemical reactions that can be used in retrosynthesis
Synthetic biology applied to industrial biotechnology is transforming the way we produce chemicals. However, despite advances in the scale and scope of metabolic engineering, the
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