Biomedical subjects

Björn H Junker

Publications and source records attributed to Björn H Junker.

7 recordsLinked to original sources

PubMed2006

Meta-All: a system for managing metabolic pathway information.

BACKGROUND: Many attempts are being made to understand biological subjects at a systems level. A major resource for these approaches are biological databases, storing manifold information about DNA, RNA and protein sequences including their functional and structural motifs, molecular markers, mRNA expression levels, metabolite concentrations, protein-protein interactions, phenotypic traits or taxonomic relationships. The use of these databases is often hampered by the fact that they are designed for special application areas and thus lack universality. Databases on metabolic pathways, which provide an increasingly important foundation for many analyses of biochemical processes at a systems level, are no exception from the rule. Data stored in central databases such as KEGG, BRENDA or SABIO-RK is often limited to read-only access. If experimentalists want to store their own data, possibly still under investigation, there are two possibilities. They can either develop their own information system for managing that own data, which is very time-consuming and costly, or they can try to store their data in existing systems, which is often restricted. Hence, an out-of-the-box information system for managing metabolic pathway data is needed. RESULTS: We have designed META-ALL, an information system that allows the management of metabolic pathways, including reaction kinetics, detailed locations, environmental factors and taxonomic information. Data can be stored together with quality tags and in different parallel versions. META-ALL uses Oracle DBMS and Oracle Application Express. We provide the META-ALL information system for download and use. In this paper, we describe the database structure and give information about the tools for submitting and accessing the data. As a first application of META-ALL, we show how the information contained in a detailed kinetic model can be stored and accessed. CONCLUSION: META-ALL is a system for managing information about metabolic pathways. It facilitates the handling of pathway-related data and is designed to help biochemists and molecular biologists in their daily research. It is available on the Web at http://bic-gh.de/meta-all and can be downloaded free of charge and installed locally.

Database Management Systems↗

PubMed2006

Exploration of biological network centralities with CentiBiN.

BACKGROUND: The elucidation of whole-cell regulatory, metabolic, interaction and other biological networks generates the need for a meaningful ranking of network elements. Centrality analysis ranks network elements according to their importance within the network structure and different centrality measures focus on different importance concepts. Central elements of biological networks have been found to be, for example, essential for viability. RESULTS: CentiBiN (Centralities in Biological Networks) is a tool for the computation and exploration of centralities in biological networks such as protein-protein interaction networks. It computes 17 different centralities for directed or undirected networks, ranging from local measures, that is, measures that only consider the direct neighbourhood of a network element, to global measures. CentiBiN supports the exploration of the centrality distribution by visualising central elements within the network and provides several layout mechanisms for the automatic generation of graphical representations of a network. It supports different input formats, especially for biological networks, and the export of the computed centralities to other tools. CONCLUSION: CentiBiN helps systems biology researchers to identify crucial elements of biological networks. CentiBiN including a user guide and example data sets is available free of charge at http://centibin.ipk-gatersleben.de/. CentiBiN is available in two different versions: a Java Web Start application and an installable Windows application.

Computer Graphics↗

PubMed2006

VANTED: a system for advanced data analysis and visualization in the context of biological networks.

BACKGROUND: Recent advances with high-throughput methods in life-science research have increased the need for automatized data analysis and visual exploration techniques. Sophisticated bioinformatics tools are essential to deduct biologically meaningful interpretations from the large amount of experimental data, and help to understand biological processes. RESULTS: We present VANTED, a tool for the visualization and analysis of networks with related experimental data. Data from large-scale biochemical experiments is uploaded into the software via a Microsoft Excel-based form. Then it can be mapped on a network that is either drawn with the tool itself, downloaded from the KEGG Pathway database, or imported using standard network exchange formats. Transcript, enzyme, and metabolite data can be presented in the context of their underlying networks, e. g. metabolic pathways or classification hierarchies. Visualization and navigation methods support the visual exploration of the data-enriched networks. Statistical methods allow analysis and comparison of multiple data sets such as different developmental stages or genetically different lines. Correlation networks can be automatically generated from the data and substances can be clustered according to similar behavior over time. As examples, metabolite profiling and enzyme activity data sets have been visualized in different metabolic maps, correlation networks have been generated and similar time patterns detected. Some relationships between different metabolites were discovered which are in close accordance with the literature. CONCLUSION: VANTED greatly helps researchers in the analysis and interpretation of biochemical data, and thus is a useful tool for modern biological research. VANTED as a Java Web Start Application including a user guide and example data sets is available free of charge at http://vanted.ipk-gatersleben.de.

Algorithms↗

PubMed2004

Application of Petri net theory for modelling and validation of the sucrose breakdown pathway in the potato tuber.

MOTIVATION: Because of the complexity of metabolic networks and their regulation, formal modelling is a useful method to improve the understanding of these systems. An essential step in network modelling is to validate the network model. Petri net theory provides algorithms and methods, which can be applied directly to metabolic network modelling and analysis in order to validate the model. The metabolism between sucrose and starch in the potato tuber is of great research interest. Even if the metabolism is one of the best studied in sink organs, it is not yet fully understood. RESULTS: We provide an approach for model validation of metabolic networks using Petri net theory, which we demonstrate for the sucrose breakdown pathway in the potato tuber. We start with hierarchical modelling of the metabolic network as a Petri net and continue with the analysis of qualitative properties of the network. The results characterize the net structure and give insights into the complex net behaviour.

Algorithms↗

PubMed2004

Hypothesis-driven approach to predict transcriptional units from gene expression data.

MOTIVATION: A major issue in computational biology is the reconstruction of functional relationships among genes, for example the definition of regulatory or biochemical pathways. One step towards this aim is the elucidation of transcriptional units, which are characterized by co-responding changes in mRNA expression levels. These units of genes will allow the generation of hypotheses about respective functional interrelationships. Thus, the focus of analysis currently moves from well-established functional assignment through comparison of protein and DNA sequences towards analysis of transcriptional co-response. Tools that allow deducing common control of gene expression have the potential to complement and extend routine BLAST comparisons, because gene function may be inferred from common transcriptional control. RESULTS: We present a co-clustering strategy of genome sequence information and gene expression data, which was applied to identify transcriptional units within diverse compendia of expression profiles. The phenomenon of prokaryotic operons was selected as an ideal test case to generate well-founded hypotheses about transcriptional units. The existence of overlapping and ambiguous operon definitions allowed the investigation of constitutive and conditional expression of transcriptional units in independent gene expression experiments of Escherichia coli. Our approach allowed identification of operons with high accuracy. Furthermore, both constitutive mRNA co-response as well as conditional differences became apparent. Thus, we were able to generate insight into the possible biological relevance of gene co-response. We conclude that the suggested strategy will be amenable in general to the identification of transcriptional units beyond the chosen example of E.coli operons. AVAILABILITY: The analyses of E.coli transcript data presented here are available upon request or at http://csbdb.mpimp-golm.mpg.de/

Algorithms↗

PubMed2004

Temporally regulated expression of a yeast invertase in potato tubers allows dissection of the complex metabolic phenotype obtained following its constitutive expression.

The constitutive cytosolic expression of a yeast ( Saccharomyces cerevisiae ) invertase within potato ( Solanum tuberosum ) tubers has previously been documented to produce a dramatic metabolic phenotype in which glycolysis, respiration and amino acid synthesis are markedly enhanced at the cost of starch synthesis. These transgenic lines were further characterised by a massive cycle of sucrose degradation and resynthesis via sucrose-phosphate synthase. We have recently developed a B33 patatin driven alc gene construct allowing tight chemical control of gene expression following supply of acetaldehyde with minimal pleiotropic effects of the inducing agent on metabolism. This construct was used for chemical induction of the yeast invertase gene after 10-weeks growth to dissect the complex metabolic phenotype obtained after constitute expression. Inducible expression led to increased invertase activity within 24 h in well-defined areas within growing tubers. Although the sucrose levels were reduced, there was no effect on the levels of starch whilst levels of many amino acids decreased. Labelling experiments revealed that these lines exhibited increased rates of sucrose cycling, whereas rates of glycolysis and of starch synthesis were not substantially changed. From these results we conclude that sucrose cycling is stimulated in response to a short-term increase in the rate of sucrose mobilisation, providing evidence for a role of sucrose cycling as a buffering capacity that regulates the net rate of sucrose usage. In contrast, the dramatic increase in hexose-phosphate levels and the switch from starch synthesis to respiration seen on the constitutive expression of the invertase was not observed in the inducible lines, suggesting that this is the result of cumulative pleiotropic effects that occurred when the transgene was expressed throughout development.

Carbon Radioisotopes↗

PubMed2003

In plants the alc gene expression system responds more rapidly following induction with acetaldehyde than with ethanol.

It has recently been proposed that acetaldehyde is the physiological inducer of the alc gene system and hence indirectly the activator of the AlcA promoter in Aspergillus nidulans. Here we show that this chemical induces expression of a GUS (beta-D-glucuronidase) reporter under the control of the alc gene system in transgenic potato tubers more rapidly than ethanol allowing tighter control of transgene expression. Furthermore by analysis of metabolite levels we demonstrate that the application of inducer has few effects on metabolism. We propose that this system is therefore ideal for the temporal regulation of important metabolic enzyme activities.

Acetaldehyde↗