Publication

Constraint-based metabolic control analysis for rational strain engineering

Publications associées (27)

An explainability framework for deep learning on chemical reactions exemplified by enzyme-catalysed reaction classification

Assigning or proposing a catalysing enzyme given a chemical or biochemical reaction is of great interest to life sciences and chemistry alike. The exploration and design of metabolic pathways and the challenge of finding more sustainable enzyme-catalysed a ...

2023

Development of multiplexed single-molecule imaging techniques to study chromatin invasion dynamics of chromatin effector proteins

Kristina Makasheva

DNA-binding proteins physically interact with the DNA and directly affect genomic functions. The eukaryotic genome is compacted into chromatin, limiting the DNA access to nuclear factors. In this Ph.D. thesis, I explored the dynamic mechanisms, that allow ...

EPFL2023

Proteome adaptations of the organohalide-respiring Desulfitobacterium hafniense strain DCB-2 to various energy metabolisms

Christof Holliger, Julien Maillard, Romain Hamelin, Mathilde Stéphanie Willemin, Florence Armand

IntroductionDesulfitobacterium hafniense was isolated for its ability to use organohalogens as terminal electron acceptors via organohalide respiration (OHR). In contrast to obligate OHR bacteria, Desulfitobacterium spp. show a highly versatile energy meta ...

Frontiers Media SA2023

Data-Driven Control and Optimization under Noisy and Uncertain Conditions

Baiwei Guo

Control systems operating in real-world environments often face disturbances arising from measurement noise and model mismatch. These factors can significantly impact the perfor- mance and safety of the system. In this thesis, we aim to leverage data to de ...

EPFL2023

Molecular reconstruction and simulation of the Neuron-Glia-Vasculature system

Polina Shichkova

The outstanding information processing capacity of the brain relies on numerous molecular mechanisms. It is an extremely energy-expensive function, which involves specialization and collaboration of different cell types. A common framework to study the com ...

EPFL2023

Optimal enzyme utilization suggests that concentrations and thermodynamics determine binding mechanisms and enzyme saturations

Vassily Hatzimanikatis, Daniel Robert Weilandt, Asli Sahin

One of the main challenges hampering the development of kinetic models is the lack of kinetic parameters for many enzymatic reactions. Here, the authors introduce a framework to explore the catalytically optimal operating conditions of any complex enzyme m ...

Nature Portfolio2023

Augmented Lagrangian Methods for Provable and Scalable Machine Learning

Mehmet Fatih Sahin

Non-convex constrained optimization problems have become a powerful framework for modeling a wide range of machine learning problems, with applications in k-means clustering, large- scale semidefinite programs (SDPs), and various other tasks. As the perfor ...

EPFL2023

Computational tools and resources for designing new pathways to small molecules

Vassily Hatzimanikatis, Anastasia Sveshnikova

The metabolic engineering community relies on computational methods for pathway design to produce important small molecules in microbial hosts. Metabolic network databases are continuously curated and updated with known and novel reactions that expand the ...

CURRENT BIOLOGY LTD2022

An optimized high throughput platform, from genetic transformation to fermentation, to screen for secreted laccases in Aspergillus niger

Laure Marie Colette Leynaud-Kieffer Curran

Many challenges are faced in the conversion of biomass into advanced biofuels, one of which is finding the correct organism for the job. The filamentous fungus Aspergillus niger has been chosen as a biocatalyst for cellulose, hemicellulose, and lignin degr ...

EPFL2021

Expanding biochemical knowledge and illuminating metabolic dark matter with ATLASx

Vassily Hatzimanikatis, Jasmin Maria Hafner, Anastasia Sveshnikova, Victor Luc Etienne Viterbo

Metabolic "dark matter" describes currently unknown metabolic processes, which form a blind spot in our general understanding of metabolism and slow down the development of biosynthetic cell factories and naturally derived pharmaceuticals. Mapping the dark ...

Nature Portfolio2022