DyMMM-LEAPS: An ML-based framework for modulating evenness and stability in synthetic microbial communities.

ABSTRACT: There have been a growing number of computational strategies to aid in the design of synthetic microbial consortia. A framework to identify regions in parametric space to maximize two essential properties, evenness and stability, is critical. In this study, we introduce DyMMM-LEAPS (dynamic multispecies metabolic modeling-locating evenness and stability in large parametric space), an extension of the DyMMM framework. Our method explores the large parametric space of genetic circuits in synthetic microbial communities to identify regions of evenness and stability. Due to the high computational costs of exhaustive sampling, we utilize adaptive sampling and surrogate modeling to reduce the number of simulations required to map the vast space. Our framework predicts engineering targets and com

SUBMITTER: Choudhary R 

PROVIDER: S-EPMC11427784 | biostudies-literature | 2024 Sep

REPOSITORIES: biostudies-literature