scispace - formally typeset
A

Andreas Kremling

Researcher at Technische Universität München

Publications -  88
Citations -  5435

Andreas Kremling is an academic researcher from Technische Universität München. The author has contributed to research in topics: Biology & Pseudomonas putida. The author has an hindex of 23, co-authored 77 publications receiving 5062 citations. Previous affiliations of Andreas Kremling include Max Planck Society.

Papers
More filters
Journal ArticleDOI

The systems biology markup language (SBML): a medium for representation and exchange of biochemical network models.

TL;DR: This work summarizes the Systems Biology Markup Language (SBML) Level 1, a free, open, XML-based format for representing biochemical reaction networks, a software-independent language for describing models common to research in many areas of computational biology.
Journal ArticleDOI

Exploiting the bootstrap method for quantifying parameter confidence intervals in dynamical systems.

TL;DR: By applying the bootstrap method a better approximation of (possibly) asymmetric confidence intervals for parameters could be obtained and a dynamical model describing a bio-chemical network is used to evaluate the method.
Journal ArticleDOI

A quantitative approach to catabolite repression in Escherichia coli.

TL;DR: The different phenomena affecting the phosphorylation level of EIIACrr, the key regulation molecule for inducer exclusion and catabolite repression in enteric bacteria, can now be explained quantitatively.
Journal ArticleDOI

Correlation between Growth Rates, EIIACrr Phosphorylation, and Intracellular Cyclic AMP Levels in Escherichia coli K-12

TL;DR: The relation between cellular growth rates and the key parameters of catabolite repression were increasingly uncoupled from the growth rate, which perhaps indicates an increasing role executed by other global control systems, in particular the stringent-relaxed response system.
Journal ArticleDOI

A Benchmark for Methods in Reverse Engineering and Model Discrimination: Problem Formulation and Solutions

TL;DR: A benchmark problem is described for the reconstruction and analysis of biochemical networks given sampled experimental data and several solutions based on linear and nonlinear models are discussed.