AI RESEARCH
An Integrative Genome-Scale Metabolic Modeling and Machine Learning Framework for Predicting and Optimizing Biofuel-Relevant Biomass Production in Saccharomyces cerevisiae
arXiv CS.LG
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ArXi:2603.25561v1 Announce Type: new Saccharomyces cerevisiae is a cornerstone organism in industrial biotechnology, valued for its genetic tractability and robust fermentative capacity. Accurately predicting biomass flux across diverse environmental and genetic perturbations remains a significant challenge for rational strain design. We present a computational framework combining the Yeast9 genome-scale metabolic model with machine learning and optimization to predict, interpret, and enhance biomass flux.