Person
Michaël Roger Germain Moret
Related publications (7)
Supplementary datasets for the manuscript "Generative machine learning produces kinetic models that accurately characterize intracellular metabolic states" -Part 2
Vassily Hatzimanikatis, Ljubisa Miskovic, Michaël Roger Germain Moret
Supplementary files containing datasets needed to reproduce the results of the manuscript "Generative machine learning produces kinetic models that accurately characterize intracellular metabolic states" by S. Choudhury et al. The code to use with these da ...
EPFL Infoscience2023Generative machine learning produces kinetic models that accurately characterize intracellular metabolic states
Vassily Hatzimanikatis, Ljubisa Miskovic, Michaël Roger Germain Moret
Large omics datasets are nowadays routinely generated to provide insights into cellular processes. Nevertheless, making sense of omics data and determining intracellular metabolic states remains challenging. Kinetic models of metabolism are crucial for int ...
2023Supplementary datasets for the manuscript "Generative machine learning produces kinetic models that accurately characterize intracellular metabolic states" - Part 3
Vassily Hatzimanikatis, Ljubisa Miskovic, Michaël Roger Germain Moret
Supplementary files containing datasets needed to reproduce the results of the manuscript "Generative machine learning produces kinetic models that accurately characterize intracellular metabolic states" by S. Choudhury et al (https://doi.org/10.1101/2023. ...
EPFL Infoscience2023Uncertainty reduction in biochemical kinetic models: Enforcing desired model properties
Vassily Hatzimanikatis, Ljubisa Miskovic, Michaël Roger Germain Moret
A persistent obstacle for constructing kinetic models of metabolism is uncertainty in the kinetic properties of enzymes. Currently, available methods for building kinetic models can cope indirectly with uncertainties by integrating data from different biol ...
2019Machine Learning for Uncertainty Reduction in Biochemical Kinetic Models
Vassily Hatzimanikatis, Ljubisa Miskovic, Michaël Roger Germain Moret
The primary goal of kinetic models is to capture the systemic properties of the metabolic networks, and we need large-scale kinetic models for reliable in silico analyses of the complex dynamic behavior of metabolism. However, parameter uncertainty hinders ...
2018Deciphering ambiguous control over fluxes through characterization and reduction of uncertainty
Vassily Hatzimanikatis, Ljubisa Miskovic, Michaël Roger Germain Moret
The development of kinetic models is still facing the challenges such as large uncertainties in available data. Uncertainty originating from various sources including metabolite concentration levels, flux values, thermodynamic and kinetic data propagates t ...
2017Identifying patterns in kinetic parameters that determine the impact of rate-limiting enzymes
Vassily Hatzimanikatis, Ljubisa Miskovic, Michaël Roger Germain Moret
Kinetic models are essential for studying complex behavior and properties of metabolism. However, a persistent hurdle for constructing these models is uncertainty in the kinetic properties of enzymes. Currently available methods for building kinetic models ...
2016