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Constraint-based metabolic control analysis for rational strain engineering

Publications associées (27)

Optimality principles for the analysis of biological processes across scales: From enzyme kinetics to microbiome dynamics

Microorganisms are essential for life on Earth, performing key roles in numerous biological processes. Their influence extends across a wide spectrum, from human health and ecological balance to advancements in biotechnology and industrial applications. Th ...

EPFL2024

Reconstruction and analysis of genome-scale metabolic networks in single organisms and microbial communities

Evangelia Vagena

Microorganisms are a key component in the chain of life. They are essential for agriculture, produce a large proportion of oxygen, and play a central role in the cycle of elements. Microorganisms are widely used in the production of food and alcoholic beve ...

EPFL2024

A ride time-oriented scheduling algorithm for dial-a-ride problems

Nikolaos Geroliminis, Claudia Bongiovanni, Mor Kaspi

This paper offers a new algorithm to efficiently optimize scheduling decisions for dial-a-ride problems (DARPs), including problem variants considering electric and autonomous vehicles (e-ADARPs). The scheduling heuristic, based on linear programming theor ...

Pergamon-Elsevier Science Ltd2024

Learning to Remove Cuts in Integer Linear Programming

Volkan Cevher, Grigorios Chrysos, Efstratios Panteleimon Skoulakis

Cutting plane methods are a fundamental approach for solving integer linear programs (ILPs). In each iteration of such methods, additional linear constraints (cuts) are introduced to the constraint set with the aim of excluding the previous fractional opti ...

2024

HaloTag-Based Tools for Live-Cell Imaging and Elucidation of Organellar Redox Biology

Sarah Emmert

Redox homeostasis is a key factor in maintaining cellular function and health. The main determinant of the intracellular redox potential is ubiquitous glutathione (GSH) together with its oxidized dimer (GSSG). Importantly, both redox equilibrium and GSH ho ...

EPFL2024

Modeling, analysis, and design of complex biological networks

Mohammadomid Oftadeh

Automating experimental procedures has resulted in an unprecedented increase in the volume of generated data, which, in turn, has caused an accumulation of unprocessed data. As a result, the need to develop tools to analyze data systematically has been ris ...

EPFL2023

Expanding computational biochemistry towards complex and non-natural compounds

Anastasia Sveshnikova

In the beginning was the metabolism. The biochemical processes that make life possible transformed the soup of chemicals into the life on Earth we know today. Since then, living organisms have evolved, and life on Earth has become more complex. Living orga ...

EPFL2023

A Spatial Branch and Bound Algorithm for Continuous Pricing with Advanced Discrete Choice Demand Modeling

Michel Bierlaire

In this paper, we present a spatial branch and bound algorithm to tackle the continuous pricing problem, where demand is captured by an advanced discrete choice model (DCM). Advanced DCMs, like mixed logit or latent class models, are capable of modeling de ...

2023

Reinforcement Learning for Joint Design and Control of Battery-PV Systems

Christophe Ballif, Nicolas Würsch, Laure-Emmanuelle Perret Aebi, Marine Dominique Cauz

The decentralisation and unpredictability of new renewable energy sources require rethinking our energy system. Data-driven approaches, such as reinforcement learning (RL), have emerged as new control strategies for operating these systems, but they have n ...

2023

Quantitative Methods for Omnichannel Decision-Making

Andrey Vasilyev

Omnichannel retail has emerged as the new standard in today's commerce landscape, with retailers integrating their physical and online channels to enhance the customer shopping experience. However, such integration presents significant challenges for retai ...

EPFL2023

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

Daniel Probst

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, Florence Armand, Romain Hamelin, Mathilde Stéphanie Willemin

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, Victor Luc Etienne Viterbo, Anastasia Sveshnikova

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