Biomedical subjects

Katja Wegner

Publications and source records attributed to Katja Wegner.

4 recordsLinked to original sources

PubMed2006

A model diagram layout extension for SBML.

MOTIVATION: Since the knowledge about processes in living cells is increasing, modelling and simulation techniques are used to get new insights into these complex processes. During the last few years, the SBML file format has gained in popularity and support as a means of exchanging model data between the different modelling and simulation tools. In addition to specifying the model as a set of equations, many modern modelling tools allow the user to create and to interact with the model in the form of a reaction graph. Unfortunately, the SBML file format does not provide for the storage of this graph data along with the mathematical description of the model. RESULTS: Therefore, we developed an extension to the SBML file format that makes it possible to store such layout information which describes position and size of objects in the graphical representation. AVAILABILITY: The complete specification can be found on (http://projects.villa-bosch.de/bcb/sbml/ (SBML Layout Extension documentation, 2005). Additionally, a complete implementation exists as part of libSBML (2006, http://www.sbml.org/software/libsbml/).

Cell Physiological Phenomena↗

PubMed2006

Quantification of cross correlations in complex spatiotemporal systems.

We propose a design of the equal time correlation matrix suitable for the analysis of multivariate time series with ill-defined phases. We present the cross-correlation analysis of model data sets taken from coupled stochastic oscillators and compare the concept with the results obtained from a conventional correlation matrix analysis. We show that the concept provides a higher sensitivity combined with a better statistical significance when quantifying weak cross correlations.

Journal Article↗

PubMed2005

A new dynamical layout algorithm for complex biochemical reaction networks.

BACKGROUND: To study complex biochemical reaction networks in living cells researchers more and more rely on databases and computational methods. In order to facilitate computational approaches, visualisation techniques are highly important. Biochemical reaction networks, e.g. metabolic pathways are often depicted as graphs and these graphs should be drawn dynamically to provide flexibility in the context of different data. Conventional layout algorithms are not sufficient for every kind of pathway in biochemical research. This is mainly due to certain conventions to which biochemists/biologists are used to and which are not in accordance to conventional layout algorithms. A number of approaches has been developed to improve this situation. Some of these are used in the context of biochemical databases and make more or less use of the information in these databases to aid the layout process. However, visualisation becomes also more and more important in modelling and simulation tools which mostly do not offer additional connections to databases. Therefore, layout algorithms used in these tools have to work independently of any databases. In addition, all of the existing algorithms face some limitations with respect to the number of edge crossings when it comes to larger biochemical systems due to the interconnectivity of these. Last but not least, in some cases, biochemical conventions are not met properly. RESULTS: Out of these reasons we have developed a new algorithm which tackles these problems by reducing the number of edge crossings in complex systems, taking further biological conventions into account to identify and visualise cycles. Furthermore the algorithm is independent from database information in order to be easily adopted in any application. It can also be tested as part of the SimWiz package (free to download for academic users at 1). CONCLUSION: The new algorithm reduces the complexity of pathways, as well as edge crossings and edge length in the resulting graphical representation. It also considers existing and further biological conventions to create a drawing most biochemists are familiar with. A lot of examples can be found on 2.

Algorithms↗

PubMed2004

CombAlign: a protein sequence comparison algorithm considering recombinations.

The basic linear treatment of sequence comparisons limits the ability of contemporary sequence alignment algorithms to detect non-order-conserving recombinations. Here, we introduce the algorithm combAlign which addresses the assessment of pairwise sequence similarity on non-order-conserving recombinations on a large scale. Emphasizing a two-level approach, combAlign first detects locally well conserved subsequences in a target and a source sequence. Subsequently, the relative placement of alignments is mapped to a graph. Concatenating local alignments to reassemble the target sequence to the fullest extent, the maximum scoring path through the graph denotes the best attainable combAlignment. Parameters influencing this process can be set to meet the user's specific demands. combAlign is applied to examples demonstrating the possibility to reflect evolutionary kinship of proteins even if their domains and motifs are strongly rearranged.

Algorithms↗