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Dive into the research topics where Marvin Schulz is active.

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Featured researches published by Marvin Schulz.


Bioinformatics | 2010

Annotation and merging of SBML models with semanticSBML

Falko Krause; Jannis Uhlendorf; Timo Lubitz; Marvin Schulz; Edda Klipp; Wolfram Liebermeister

SUMMARY Systems Biology Markup Language (SBML) is the leading exchange format for mathematical models in Systems Biology. Semantic annotations link model elements with external knowledge via unique database identifiers and ontology terms, enabling software to check and process models by their biochemical meaning. Such information is essential for model merging, one of the key steps towards the construction of large kinetic models. SemanticSBML is a tool that helps users to check and edit MIRIAM annotations and SBO terms in SBML models. Using a large collection of biochemical names and database identifiers, it supports modellers in finding the right annotations and in merging existing models. Initially, an element matching is derived from the MIRIAM annotations and conflicting element attributes are categorized and highlighted. Conflicts can then be resolved automatically or manually, allowing the user to control the merging process in detail. AVAILABILITY SemanticSBML comes as a free software written in Python and released under the GPL 3. A Debian package, a source package for other Linux distributions, a Windows installer and an online version of semanticSBML with limited functionality are available at http://www.semanticsbml.org. A preinstalled version can be found on the Linux live DVD SB.OS, available at http://www.sbos.eu. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.


Molecular Systems Biology | 2014

Retrieval, alignment, and clustering of computational models based on semantic annotations

Marvin Schulz; Falko Krause; Nicolas Le Novère; Edda Klipp; Wolfram Liebermeister

The exploding number of computational models produced by Systems Biologists over the last years is an invitation to structure and exploit this new wealth of information. Researchers would like to trace models relevant to specific scientific questions, to explore their biological content, to align and combine them, and to match them with experimental data. To automate these processes, it is essential to consider semantic annotations, which describe their biological meaning. As a prerequisite for a wide range of computational methods, we propose general and flexible similarity measures for Systems Biology models computed from semantic annotations. By using these measures and a large extensible ontology, we implement a platform that can retrieve, cluster, and align Systems Biology models and experimental data sets. At present, its major application is the search for relevant models in the BioModels Database, starting from initial models, data sets, or lists of biological concepts. Beyond similarity searches, the representation of models by semantic feature vectors may pave the way for visualisation, exploration, and statistical analysis of large collections of models and corresponding data.


BMC Bioinformatics | 2009

TIde: a software for the systematic scanning of drug targets in kinetic network models.

Marvin Schulz; Barbara M. Bakker; Edda Klipp

BackgroundDuring the stages of the development of a potent drug candidate compounds can fail for several reasons. One of them, the efficacy of a candidate, can be estimated in silico if an appropriate ordinary differential equation model of the affected pathway is available. With such a model at hand it is also possible to detect reactions having a large effect on a certain variable such as a substance concentration.ResultsWe show an algorithm that systematically tests the influence of activators and inhibitors of different type and strength acting at different positions in the network. The effect on a quantity to be selected (e.g. a steady state flux or concentration) is calculated. Moreover, combinations of two inhibitors or one inhibitor and one activator targeting different network positions are analysed. Furthermore, we present TIde (Target Identification), an open source, platform independent tool to investigate ordinary differential equation models in the common systems biology markup language format. It automatically assigns the respectively altered kinetics to the inhibited or activated reactions, performs the necessary calculations, and provides a graphical output of the analysis results. For illustration, TIde is used to detect optimal inhibitor positions in simple branched networks, a signalling pathway, and a well studied model of glycolysis in Trypanosoma brucei.ConclusionUsing TIde, we show in the branched models under which conditions inhibitions in a certain pathway can affect a molecule concentrations in a different. In the signalling pathway we illuminate which inhibitions have an effect on the signalling characteristics of the last active kinase. Finally, we compare our set of best targets in the glycolysis model with a similar analysis showing the applicability of our tool.


Journal of Physical Chemistry B | 2010

Parameter Balancing in Kinetic Models of Cell Metabolism

Timo Lubitz; Marvin Schulz; Edda Klipp; Wolfram Liebermeister

Kinetic modeling of metabolic pathways has become a major field of systems biology. It combines structural information about metabolic pathways with quantitative enzymatic rate laws. Some of the kinetic constants needed for a model could be collected from ever-growing literature and public web resources, but they are often incomplete, incompatible, or simply not available. We address this lack of information by parameter balancing, a method to complete given sets of kinetic constants. Based on Bayesian parameter estimation, it exploits the thermodynamic dependencies among different biochemical quantities to guess realistic model parameters from available kinetic data. Our algorithm accounts for varying measurement conditions in the input data (pH value and temperature). It can process kinetic constants and state-dependent quantities such as metabolite concentrations or chemical potentials, and uses prior distributions and data augmentation to keep the estimated quantities within plausible ranges. An online service and free software for parameter balancing with models provided in SBML format (Systems Biology Markup Language) is accessible at www.semanticsbml.org. We demonstrate its practical use with a small model of the phosphofructokinase reaction and discuss its possible applications and limitations. In the future, parameter balancing could become an important routine step in the kinetic modeling of large metabolic networks.


Methods in Enzymology | 2011

Sustainable Model Building: The Role of Standards and Biological Semantics

Falko Krause; Marvin Schulz; Neil Swainston; Wolfram Liebermeister

Systems biology models can be reused within new simulation scenarios, as parts of more complex models or as sources of biochemical knowledge. Reusability does not come by itself but has to be ensured while creating a model. Most important, models should be designed to remain valid in different contexts-for example, for different experimental conditions-and be published in a standardized and well-documented form. Creating reusable models is worthwhile, but it requires some efforts when a model is developed, implemented, documented, and published. Minimum requirements for published systems biology models have been formulated by the MIRIAM initiative. Main criteria are completeness of information and documentation, availability of machine-readable models in standard formats, and semantic annotations connecting the model elements with entries in biological Web resources. In this chapter, we discuss the assumptions behind bottom-up modeling; present important standards like MIRIAM, the Systems Biology Markup Language (SBML), and the Systems Biology Graphical Notation (SBGN); and describe software tools and services for handling semantic annotations. Finally, we show how standards can facilitate the construction of large metabolic network models.


Bioinformatics | 2013

Biographer: web-based editing and rendering of SBGN compliant biochemical networks.

Falko Krause; Marvin Schulz; Ben Ripkens; Max Flöttmann; Marcus Krantz; Edda Klipp; Thomas Handorf

Motivation: The rapid accumulation of knowledge in the field of Systems Biology during the past years requires advanced, but simple-to-use, methods for the visualization of information in a structured and easily comprehensible manner. Results: We have developed biographer, a web-based renderer and editor for reaction networks, which can be integrated as a library into tools dealing with network-related information. Our software enables visualizations based on the emerging standard Systems Biology Graphical Notation. It is able to import networks encoded in various formats such as SBML, SBGN-ML and jSBGN, a custom lightweight exchange format. The core package is implemented in HTML5, CSS and JavaScript and can be used within any kind of web-based project. It features interactive graph-editing tools and automatic graph layout algorithms. In addition, we provide a standalone graph editor and a web server, which contains enhanced features like web services for the import and export of models and visualizations in different formats. Availability: The biographer tool can be used at and downloaded from the web page http://biographer.biologie.hu-berlin.de/. The different software packages, including a server-indepenent version as well as a web server for Windows and Linux based systems, are available at http://code.google.com/p/biographer/ under the open-source license LGPL. Contact: [email protected] or [email protected]


Genome Informatics | 2006

SBMLmerge, a System for Combining Biochemical Network Models

Marvin Schulz; Jannis Uhlendorf; Edda Klipp; Wolfram Liebermeister


BMC Bioinformatics | 2012

Propagating semantic information in biochemical network models

Marvin Schulz; Edda Klipp; Wolfram Liebermeister


Nature Precedings | 2011

SBML Level 3 Package Proposal: Annotation

Dagmar Waltemath; Neil Swainston; Allyson L. Lister; Frank Bergmann; Ron Henkel; Stefan Hoops; Michael Hucka; Nick Juty; Sarah M. Keating; Christian Knuepfer; Falko Krause; Camille Laibe; Wolfram Liebermeister; Catherine Lloyd; Goksel Misirli; Marvin Schulz; Morgan Taschuk; Nicolas Le Novère


Nature Precedings | 2010

SemanticSBML – state of affairs

Wolfram Liebermeister; Falko Krause; Marvin Schulz; Timo Lubitz

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Edda Klipp

Humboldt University of Berlin

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Falko Krause

Humboldt University of Berlin

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Timo Lubitz

Humboldt University of Berlin

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Neil Swainston

University of Manchester

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Jannis Uhlendorf

Humboldt University of Berlin

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Ben Ripkens

Humboldt University of Berlin

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Marcus Krantz

Humboldt University of Berlin

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