Lukas Endler

BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models

BackgroundQuantitative models of biochemical and cellular systems are used to answer a variety of questions in the biological sciences. The number of published quantitative models is growing steadily thanks to increasing interest in the use of models as well as the development of improved software systems and the availability of better, cheaper computer hardware. To maximise the benefits of this growing body of models, the field needs centralised model repositories that will encourage, facilitate and promote model dissemination and reuse. Ideally, the models stored in these repositories should be extensively tested and encoded in community-supported and standardised formats. In addition, the models and their components should be cross-referenced with other resources in order to allow their unambiguous identification.DescriptionBioModels Database http://www.ebi.ac.uk/biomodels/ is aimed at addressing exactly these needs. It is a freely-accessible online resource for storing, viewing, retrieving, and analysing published, peer-reviewed quantitative models of biochemical and cellular systems. The structure and behaviour of each simulation model distributed by BioModels Database are thoroughly checked; in addition, model elements are annotated with terms from controlled vocabularies as well as linked to relevant data resources. Models can be examined online or downloaded in various formats. Reaction network diagrams generated from the models are also available in several formats. BioModels Database also provides features such as online simulation and the extraction of components from large scale models into smaller submodels. Finally, the system provides a range of web services that external software systems can use to access up-to-date data from the database.ConclusionsBioModels Database has become a recognised reference resource for systems biology. It is being used by the community in a variety of ways; for example, it is used to benchmark different simulation systems, and to study the clustering of models based upon their annotations. Model deposition to the database today is advised by several publishers of scientific journals. The models in BioModels Database are freely distributed and reusable; the underlying software infrastructure is also available from SourceForge https://sourceforge.net/projects/biomodels/ under the GNU General Public License.

Designing and encoding models for synthetic biology

A key component of any synthetic biology effort is the use of quantitative models. These models and their corresponding simulations allow optimization of a system design, as well as guiding their subsequent analysis. Once a domain mostly reserved for experts, dynamical modelling of gene regulatory and reaction networks has been an area of growth over the last decade. There has been a concomitant increase in the number of software tools and standards, thereby facilitating model exchange and reuse. We give here an overview of the model creation and analysis processes as well as some software tools in common use. Using markup language to encode the model and associated annotation, we describe the mining of components, their integration in relational models, formularization and parametrization. Evaluation of simulation results and validation of the model close the systems biology ‘loop’.

SBML2LaTEX: Conversion of SBML files into human-readable reports

Summary: The XML-based Systems Biology Markup Language (SBML) has emerged as a standard for storage, communication and interchange of models in systems biology. As a machine-readable format XML is difficult for humans to read and understand. Many tools are available that visualize the reaction pathways stored in SBML files, but many components, e.g. unit declarations, complex kinetic equations or links to MIRIAM resources, are often not made visible in these diagrams. For a broader understanding of the models, support in scientific writing and error detection, a human-readable report of the complete model is needed. We present SBML2LaTEX, a Java-based stand-alone program to fill this gap. A convenient web service allows users to directly convert SBML to various formats, including DVI, LaTEX and PDF, and provides many settings for customization. Availability: Source code, documentation and a web service are freely available at http://www.ra.cs.uni-tuebingen.de/software/SBML2LaTeX. Contact:andreas.draeger@uni-tuebingen.de Supplementary information:Supplementary data are available at Bioinformatics online.

Data Integration and Semantic Enrichment of Systems Biology Models and Simulations

The rise of Systems Biology approaches, in conjunction with the availability of numerous powerful and user-friendly modeling environments, brought computational models out of the dusty closets of theoreticians to the forefront of research in biology. Those models are becoming larger, more complex and more realistic. As any other type of data in life sciences, models have to be stored, exchanged and re-used. This was made possible by the development of a series of standards, that, when used in conjunction, can cover the whole life-cycle of a model, including the specification of its structure and syntax, the simulations to be run, and the description of its behaviour and resulting numerical output. We will review those standards, well-accepted or still under development, including the Minimal requirements (MIRIAM, MIASE), the description formats (SBML, SED-ML, SBRML) and the associated ontologies (SBO, KiSAO, TEDDY). We will show how their use by the community, through a rich toolkit of complementary software, can permit to leverage on everyones efforts, to integrate models and simulations with other types of biological knowledge, and eventually lead to the fulfillment of one of Systems Biologys tenets of collaboration between biology, mathematics and computing science.

Using Chemical Kinetics to Model Biochemical Pathways

Chemical kinetics is the study of the rate of reactions transforming some chemical entities into other chemical entities. Over the twentieth century it has become one of the cornerstones of biochemistry. When in the second half of the century basic knowledge of cellular processes became sufficient to understand quantitatively metabolic networks, chemical kinetics associated with systems theory led to the development of what would become an important branch of systems biology. In this chapter we introduce basic concepts of chemical and enzyme kinetics, and show how the temporal evolution of a reaction system can be described by ordinary differential equations. Finally we present a method to apply this type of approach to model any regulatory network.

Using chemical kinetics to model neuronal signalling pathways

Understanding the physical principles and mechanisms underlying biochemical reactions allows to create mechanistic mathematical models of complex biological processes, such as those occurring during neuronal signal transduction. In this chapter we introduce basic concepts of chemical and enzyme kinetics, and reaction thermodynamics. Furthermore we show, how the temporal evolution of a reaction system can be described by ordinary differential equations, that can numerically solved on a computer. Finally we give a short overview of different approaches to modelling cooperative binding to, and allosteric control of, receptors and ion channels.