Vassily Hatzimanikatis

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Mono-ethylene glycol (MEG) is an important petrochemical with widespread use in numerous consumer products. The current industrial MEG-production process relies on non-renewable fossil fuel-based feedstocks, such as petroleum, natural gas, and naphtha; hen ...

Microbial production of desired compounds provides an efficient framework for the development of renewable energy resources. To be competitive to traditional chemistry, one requirement is to utilize the full capacity of the microorganism to produce target ...

Supplementary datasets accompanying the manuscript "ARBRE: Computational resource to predict pathways towards industrially important aromatic compounds" published in the Metabolic Engineering Journal (https://doi.org/10.1016/j.ymben.2022.03.013). In line w ...

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. ...

The overarching ambition of kinetic metabolic modeling is to capture the dynamic behavior of metabolism to such an extent that systems and synthetic biology strategies can reliably be tested in silico. The lack of kinetic data hampers the development of ki ...

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 ...

Vassily Hatzimanikatis

Chattez avec Graph Search

Exploring biochemical pathways for mono-ethylene glycol (MEG) synthesis from synthesis gas

Integrating computational methods to retrofit enzymes to synthetic pathways

Supplementary datasets for "ARBRE: Computational resource to predict pathways towards industrially important aromatic compounds"

Supplementary datasets for the manuscript "Generative machine learning produces kinetic models that accurately characterize intracellular metabolic states" - Part 3

SYSTEMS BIOLOGY APPROACHES ALLOW INVESTIGATING THE SIGNALING AND METABOLIC REPROGRAMMING OF T CELLS

Do genome-scale models need exact solvers or clearer standards?

Rites of passage: requirements and standards for building kinetic models of metabolic phenotypes

Analysis of genome-scale metabolic model of mycobacterium tuberculosis for new combat strategies

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

The interplay between tRNA competition and decoding on mRNA translation elongation rate modulation

MEMOTE for standardized genome-scale metabolic model testing

Editorial Overview: Mathematical modeling: It's a matter of scale

A NON-CD25-BINDING IL-2 VARIANT FOR THE EXPANSION OR ENGINEERING OF T CELLS THAT CONFER SUPERIOR TUMOR CONTROL

Metabolic modeling in biotechnology and medical research

Systems biology