Author
Andreas Kremling
Other affiliations: Max Planck Society
Bio: Andreas Kremling is an academic researcher from Technische Universität München. The author has contributed to research in topics: Pseudomonas putida & Medicine. The author has an hindex of 23, co-authored 77 publications receiving 5062 citations. Previous affiliations of Andreas Kremling include Max Planck Society.
Papers published on a yearly basis
Papers
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California Institute of Technology1, University of Hertfordshire2, University of California, Berkeley3, Jet Propulsion Laboratory4, University of Cambridge5, Centre national de la recherche scientifique6, University of Auckland7, GlaxoSmithKline8, Max Planck Society9, Stellenbosch University10, University of Connecticut Health Center11, Virginia Bioinformatics Institute12, University of California, Irvine13, Keio University14, Princeton University15
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.
Abstract: Motivation: Molecular biotechnology now makes it possible to build elaborate systems models, but the systems biology community needs information standards if models are to be shared, evaluated and developed cooperatively. Results: We summarize the Systems Biology Markup Language (SBML) Level 1, a free, open, XML-based format for representing biochemical reaction networks. SBML is a software-independent language for describing models common to research in many areas of computational biology, including cell signaling pathways, metabolic pathways, gene regulation, and others. ∗ To whom correspondence should be addressed. Availability: The specification of SBML Level 1 is freely available from http://www.sbml.org/.
3,205 citations
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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.
186 citations
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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.
164 citations
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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.
Abstract: In Escherichia coli K-12, components of the phosphoenolpyruvate-dependent phosphotransferase systems (PTSs) represent a signal transduction system involved in the global control of carbon catabolism through inducer exclusion mediated by phosphoenolpyruvate-dependent protein kinase enzyme IIA(Crr) (EIIA(Crr)) (= EIIA(Glc)) and catabolite repression mediated by the global regulator cyclic AMP (cAMP)-cAMP receptor protein (CRP). We measured in a systematic way the relation between cellular growth rates and the key parameters of catabolite repression, i.e., the phosphorylated EIIA(Crr) (EIIA(Crr) approximately P) level and the cAMP level, using in vitro and in vivo assays. Different growth rates were obtained by using either various carbon sources or by growing the cells with limited concentrations of glucose, sucrose, and mannitol in continuous bioreactor experiments. The ratio of EIIA(Crr) to EIIA(Crr) approximately P and the intracellular cAMP concentrations, deduced from the activity of a cAMP-CRP-dependent promoter, correlated well with specific growth rates between 0.3 h(-1) and 0.7 h(-1), corresponding to generation times of about 138 and 60 min, respectively. Below and above this range, these parameters 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.
153 citations
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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.
Abstract: A benchmark problem is described for the reconstruction and analysis of biochemical networks given sampled experimental data. The growth of the organisms is described in a bioreactor in which one substrate is fed into the reactor with a given feed rate and feed concentration. Measurements for some intracellular components are provided representing a small biochemical network. Problems of reverse engineering, parameter estimation, and identifiability are addressed. The contribution mainly focuses on the problem of model discrimination. If two or more model variants describe the available experimental data, a new experiment must be designed to discriminate between the hypothetical models. For the problem presented, the feed rate and feed concentration of a bioreactor system are available as control inputs. To verify calculated input profiles an interactive Web site (http://www.sysbio.de/projects/benchmark/) is provided. Several solutions based on linear and nonlinear models are discussed.
139 citations
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01 Aug 2000
TL;DR: Assessment of medical technology in the context of commercialization with Bioentrepreneur course, which addresses many issues unique to biomedical products.
Abstract: BIOE 402. Medical Technology Assessment. 2 or 3 hours. Bioentrepreneur course. Assessment of medical technology in the context of commercialization. Objectives, competition, market share, funding, pricing, manufacturing, growth, and intellectual property; many issues unique to biomedical products. Course Information: 2 undergraduate hours. 3 graduate hours. Prerequisite(s): Junior standing or above and consent of the instructor.
4,833 citations
01 Jan 2000
3,536 citations
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TL;DR: An update on the online database resource Search Tool for the Retrieval of Interacting Genes (STRING), which provides uniquely comprehensive coverage and ease of access to both experimental as well as predicted interaction information.
Abstract: An essential prerequisite for any systems-level understanding of cellular functions is to correctly uncover and annotate all functional interactions among proteins in the cell. Toward this goal, remarkable progress has been made in recent years, both in terms of experimental measurements and computational prediction techniques. However, public efforts to collect and present protein interaction information have struggled to keep up with the pace of interaction discovery, partly because protein-protein interaction information can be error-prone and require considerable effort to annotate. Here, we present an update on the online database resource Search Tool for the Retrieval of Interacting Genes (STRING); it provides uniquely comprehensive coverage and ease of access to both experimental as well as predicted interaction information. Interactions in STRING are provided with a confidence score, and accessory information such as protein domains and 3D structures is made available, all within a stable and consistent identifier space. New features in STRING include an interactive network viewer that can cluster networks on demand, updated on-screen previews of structural information including homology models, extensive data updates and strongly improved connectivity and integration with third-party resources. Version 9.0 of STRING covers more than 1100 completely sequenced organisms; the resource can be reached at http://string-db.org.
3,239 citations
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TL;DR: This primer covers the theoretical basis of the approach, several practical examples and a software toolbox for performing the calculations.
Abstract: Flux balance analysis is a mathematical approach for analyzing the flow of metabolites through a metabolic network. This primer covers the theoretical basis of the approach, several practical examples and a software toolbox for performing the calculations.
3,229 citations
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TL;DR: COPASI is presented, a platform-independent and user-friendly biochemical simulator that offers several unique features, and numerical issues with these features are discussed; in particular, the criteria to switch between stochastic and deterministic simulation methods, hybrid deterministic-stochastic methods, and the importance of random number generator numerical resolution in Stochastic simulation.
Abstract: Motivation: Simulation and modeling is becoming a standard approach to understand complex biochemical processes. Therefore, there is a big need for software tools that allow access to diverse simulation and modeling methods as well as support for the usage of these methods.
Results: Here, we present COPASI, a platform-independent and user-friendly biochemical simulator that offers several unique features. We discuss numerical issues with these features; in particular, the criteria to switch between stochastic and deterministic simulation methods, hybrid deterministic--stochastic methods, and the importance of random number generator numerical resolution in stochastic simulation.
Availability: The complete software is available in binary (executable) for MS Windows, OS X, Linux (Intel) and Sun Solaris (SPARC), as well as the full source code under an open source license from http://www.copasi.org.
Contact: mendes@vbi.vt.edu
2,351 citations