Daniel Robert Weilandt

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Many computational models for analyzing and predicting cell physiology rely on in vitro data collected in dilute and controlled buffer solutions. However, this can mislead models because up to 40% of the intracellular volume-depending on the organism, the ...

Whether one aims to design treatments for diseases such as cancer or diabetes, engineer cells to produce valuable biochemicals sustainably, or to grasp the behavior of living organisms, it is essential to understand how cells react to genetic, environmenta ...

Chromatin recruitment of effector proteins involved in gene regulation depends on multivalent interaction with histone post-translational modifications (PTMs) and structural features of the chromatin fiber. Due to the complex interactions involved, it is c ...

Motivation: Large-scale kinetic models are an invaluable tool to understand the dynamic and adaptive responses of biological systems. The development and application of these models have been limited by the availability of computational tools to build and ...

Kinetic models of metabolism relate metabolic fluxes, metabolite concentrations and enzyme levels through mechanistic relations, rendering them essential for understanding, predicting and optimizing the behaviour of living organisms. However, due to the la ...

Devising genetic interventions for desired cellular phenotypes remains challenging regarding time and resources. Kinetic models can accelerate this task by simulating metabolic responses to genetic perturbations. However, exhaustive design evaluations with ...

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 ...

Daniel Robert Weilandt

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Particle-Based Simulation Reveals Macromolecular Crowding Effects on the Michaelis-Menten Mechanism

Modeling biochemical reaction networks in complex intracellular environments

Single-molecule kinetic analysis of HP1-chromatin binding reveals a dynamic network of histone modification and DNA interactions

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

Rational strain design with minimal phenotype perturbation

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