miRNA target identification and prediction as a function of time in gene expression data.

The understanding of miRNA target interactions is still limited due to conflicting data and the fact that high-quality validation of targets is a time-consuming process. Faster methods like high-throughput screens and bioinformatics predictions are employed but suffer from several problems. One of these, namely the potential occurrence of downstream (i.e. secondary) effects in high-throughput screens has been only little discussed so far. However, such effects limit usage for both the identification of interactions and for the training of bioinformatics tools. In order to analyse this problem more closely, we performed time-dependent microarray screening experiments overexpressing human miR-517a-3p, and, together with published time-dependent datasets of human miR-17-5p, miR-135b and miR-124 overexpression, we analysed the dynamics of deregulated genes. We show that the number of deregulated targets increases over time, whereas seed sequence content and performance of several miRNA target prediction algorithms actually decrease over time. Bioinformatics recognition success of validated miR-17 targets was comparable to that of data gained only 12 h post-transfection. We therefore argue that the timing of microarray experiments is of critical importance for detecting direct targets with high confidence and for the usability of these data for the training of bioinformatics prediction tools.

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/).

The Systems Biology Markup Language (SBML) Level 3 Package: Layout, Version 1 Core.

Many software tools provide facilities for depicting reaction network diagrams in a visual form. Two aspects of such a visual diagram can be distinguished: the layout (i.e.: the positioning and connections) of the elements in the diagram, and the graphical form of the elements (for example, the glyphs used for symbols, the properties of the lines connecting them, and so on). For software tools that also read and write models in SBML (Systems Biology Markup Language) format, a common need is to store the network diagram together with the SBML representation of the model. This in turn raises the question of how to encode the layout and the rendering of these diagrams. The SBML Level 3 Version 1 Core specification does not provide a mechanism for explicitly encoding diagrams, but it does provide a mechanism for SBML packages to extend the Core specification and add additional syntactical constructs. The Layout package for SBML Level 3 adds the necessary features to SBML so that diagram layouts can be encoded in SBML files, and a companion package called SBML Rendering specifies how the graphical rendering of elements can be encoded. The SBML Layout package is based on the principle that reaction network diagrams should be described as representations of entities such as species and reactions (with direct links to the underlying SBML elements), and not as arbitrary drawings or graphs; for this reason, existing languages for the description of vector drawings (such as SVG) or general graphs (such as GraphML) cannot be used.

TreeWiz: interactive exploration of huge trees.

MOTIVATION: The rapidly increasing amount and disparity of biological data requires interpretation at many levels of description. Human judgement and intuition are important because not all data can be automatically and comprehensively analyzed. Visualization of trees and substructures corresponding to certain features are often used to analyze phylogenies or taxonomies. Unfortunately, most existing tools do not cope with the size of current datasets, the required functionality, or both. RESULTS: We introduce a program for visualization of huge trees and also for the interactive exploration of their content. We have developed a range of new schemes which are tailored for biological problems. Users can get an overview, zoom in, filter out data and retrieve details from standard databases such as SWISS-PROT. Furthermore, it is possible to analyze the relationship between chosen leaf sets that are specified by common features on a second level of representation. On a PC (with approximately equal to 512 MB RAM), trees of up to several tens of thousands of leaves can be loaded and both rapidly and interactively explored. We demonstrate the use of this program for the analysis of the SYSTERS data set (which contains hierarchically clustered protein sequences) to which PFAM domains were added as features.