Vassily Hatzimanikatis

Associate Professor

Switzerland

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Vassily Hatzimanikatis is an Associate Professor at Ecole Polytechnique Federale de Lausanne in Switzerland. His research focuses on computational systems biotechnology, including high-throughput kinetic modeling, metabolic network reconstruction, and strain design. Recent publications explore topics such as metabolic interaction models, generative machine learning for kinetic modeling, and the implications of antibiotic tolerance in pathogens.

Articles (17)

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2025

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2025

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2025

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2024

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2024

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2022

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2022

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2021

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2021

Collaborators (6)

Alan Pacheco

University of Lausanne

SWITZERLAND

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Tamara Rossy

Massachusetts Institute of Technology

UNITED STATES

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Ljubisa Miskovic

EPFL (École Polytechnique Fédérale de Lausanne)

SWITZERLAND

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Evangelia Vayena

Laboratoire d'analyse et d'architecture des systèmes

SWITZERLAND

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Julia A. Vorholt

Full Professor

Swiss Federal Institute of Technology in Zurich

SWITZERLAND

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Wolf-Dietrich Hardt

Professor of Microbiology

Eidgenössische Technische Hochschule Zürich

SWITZERLAND

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Vassily Hatzimanikatis

Research Interests

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About

Articles (17)

Metabolic network reconstruction as a resource for analyzing Salmonella Typhimurium SL1344 growth in the mouse intestine

The Dawn of High-Throughput and Genome-Scale Kinetic Modeling: Recent Advances and Future Directions

Designing pathways for bioproducing complex chemicals by combining tools for pathway extraction and ranking

Generative machine learning produces kinetic models that accurately characterize intracellular metabolic states

Genome-scale models of metabolism and expression predict the metabolic burden of recombinant protein expression

Rational strain design with minimal phenotype perturbation

Pseudomonas aeruginosa faces a fitness trade-off between mucosal colonization and antibiotic tolerance during airway infection

Metabolic interaction models recapitulate leaf microbiota ecology

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

Symbolic kinetic models in python (SKiMpy): intuitive modeling of large-scale biological kinetic models

Reconstructing Kinetic Models for Dynamical Studies of Metabolism using Generative Adversarial Networks

A workflow for annotating the knowledge gaps in metabolic reconstructions using known and hypothetical reactions

ARBRE: Computational resource to predict pathways towards industrially important aromatic compounds

Expanding biochemical knowledge and illuminating metabolic dark matter with ATLASx

A genome-scale metabolic model of Saccharomyces cerevisiae that integrates expression constraints and reaction thermodynamics

The effects of model complexity and size on metabolic flux distribution and control: case study in Escherichia coli

NICEpath: Finding metabolic pathways in large networks through atom-conserving substrate–product pairs

Collaborators (6)

Alan Pacheco

Tamara Rossy

Ljubisa Miskovic

Evangelia Vayena

Julia A. Vorholt

Wolf-Dietrich Hardt

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