VANESA - A Software Application for the Visualization and Analysis of Networks in System Biology Applications

Brinkrolf C, Janowski SJ, Kormeier B, et al. VANESA - A Software Application for the Visualization and Analysis of Networks in System Biology Applications. Journal of Integrative Bioinformatics. 2014;11(2):239.VANESA is a modeling software for the automatic reconstruction and analysis of biological networks based on life-science database information. Using VANESA, scientists are able to model any kind of biological processes and systems as biological networks. It is now possible for scientists to automatically reconstruct important molecular systems with information from the databases KEGG, MINT, IntAct, HPRD, and BRENDA. Additionally, experimental results can be expanded with database information to better analyze the investigated elements and processes in an overall context. Users also have the possibility to use graph theoretical approaches in VANESA to identify regulatory structures and significant actors within the modeled systems. These structures can then be further investigated in the Petri net environment of VANESA. It is platform-independent, free-of-charge, and available at http://vanesa.sf.net

VANESA - A Software Application for the Visualization and Analysis of Networks in System Biology Applications

Brinkrolf C, Janowski SJ, Kormeier B, et al. VANESA - A Software Application for the Visualization and Analysis of Networks in System Biology Applications. Journal of Integrative Bioinformatics. 2014;11(2):239.VANESA is a modeling software for the automatic reconstruction and analysis of biological networks based on life-science database information. Using VANESA, scientists are able to model any kind of biological processes and systems as biological networks. It is now possible for scientists to automatically reconstruct important molecular systems with information from the databases KEGG, MINT, IntAct, HPRD, and BRENDA. Additionally, experimental results can be expanded with database information to better analyze the investigated elements and processes in an overall context. Users also have the possibility to use graph theoretical approaches in VANESA to identify regulatory structures and significant actors within the modeled systems. These structures can then be further investigated in the Petri net environment of VANESA. It is platform-independent, free-of-charge, and available at http://vanesa.sf.net

VANESA - A Software Application for the Visualization and Analysis of Networks in Systems Biology Applications

VANESA is a modeling software for the automatic reconstruction and analysis of biological networks based on life-science database information. Using VANESA, scientists are able to model any kind of biological processes and systems as biological networks. It is now possible for scientists to automatically reconstruct important molecular systems with information from the databases KEGG, MINT, IntAct, HPRD, and BRENDA. Additionally, experimental results can be expanded with database information to better analyze the investigated elements and processes in an overall context. Users also have the possibility to use graph theoretical approaches in VANESA to identify regulatory structures and significant actors within the modeled systems. These structures can then be further investigated in the Petri net environment of VANESA. It is platform-independent, free-of-charge, and available at http://vanesa.sf.net

The LAILAPS Information Retrieval Portal as Scalable and Integrative Database Query Endpoint

Lange M, Chen J, Borck D, et al. The LAILAPS Information Retrieval Portal as Scalable and Integrative Database Query Endpoint. In: Proceedings of the 6th International Symposium on Health Informatics and Bioinformatics. 2011: 37

Building Information Retrieval Portals using the lailaps search engine

Lange M, Chen J, Borck D, et al. Building Information Retrieval Portals using the lailaps search engine. In: Proceedings of the 6th International Symposium on Health Informatics and Bioinformatics. 2011: 90

Modeling of cell-cell communication processes with Petri nets using the example of quorum sensing

Janowski SJ, Kormeier B, Töpel T, et al. Modeling of cell-cell communication processes with Petri nets using the example of quorum sensing. In Silico Biology. 2010;10(Special Issue: Petri Net Applications in Molecular Biology):27-48.The understanding of the molecular mechanism of cell-to-cell communication is fundamental for system biology. Up to now, the main objectives of bioinformatics have been reconstruction, modeling and analysis of metabolic, regulatory and signaling processes, based on data generated from high-throughput technologies. Cell-to-cell communication or quorum sensing (QS), the use of small molecule signals to coordinate complex patterns of behavior in bacteria, has been the focus of many reports over the past decade. Based on the quorum sensing process of the organism Aliivibrio salmonicida, we aim at developing a functional Petri net, which will allow modeling and simulating cell-to-cell communication processes. Using a new editor-controlled information system called VANESA (http://vanesa.sf.net), we present how to combine different fields of studies such as life-science, database consulting, modeling, visualization and simulation for a semi-automatic reconstruction of the complex signaling quorum sensing network. We show how cell-to-cell communication processes and information-flow within a cell and across cell colonies can be modeled using VANESA and how those models can be simulated with Petri net network structures in a sophisticated way

Modeling of Cell-to-Cell Communication Processes with Petri Nets Using the Example of Quorum Sensing

Janowski SJ, Kormeier B, Töpel T, et al. Modeling of Cell-to-Cell Communication Processes with Petri Nets Using the Example of Quorum Sensing. In: Wingender E, ed. Biological Petri Nets. Studies in health technology and informatics. Vol 162. Amsterdam: IOS Press; 2011: 182-203.The understanding of the molecular mechanism of cell-to-cell communication is fundamental for system biology. Up to now, the main objectives of bioinformatics have been reconstruction, modeling and analysis of metabolic, regulatory and signaling processes, based on data generated from high-throughput technologies. Cell-to-cell communication or quorum sensing (QS), the use of small molecule signals to coordinate complex patterns of behavior in bacteria, has been the focus of many reports over the past decade. Based on the quorum sensing process of the organism Aliivibrio salmonicida, we aim at developing a functional Petri net, which will allow modeling and simulating cell-to-cell communication processes. Using a new editor-controlled information system called VANESA (http://vanesa.sf.net), we present how to combine different fields of studies such as life-science, database consulting, modeling, visualization and simulation for a semi-automatic reconstruction of the complex signaling quorum sensing network. We show how cell-to-cell communication processes and information-flow within a cell and across cell colonies can be modeled using VANESA and how those models can be simulated with Petri net network structures in a sophisticated way

Histology of cholesteatoma.

<p>Histologically, a mixture of keratinous material and stratified squamous epithelium is required to diagnose cholesteatoma. The epithelium displays stratified squamous epithelium with keratinization (matrix). The subepithelial region is occupied by connective tissue. Abbreviations: C: stratum corneum; G: stratum granulosum; S: stratum spinosum; B: stratum basale; D: dermis. Magnification, 600x.</p

Heatmap of log expression values.

<p>For the heatmap generation, significantly regulated genes with a fold change of five were used. 116 up-regulated and 29 down-regulated genes are shown. The clustering reveals that the mRNA profiles of control samples (EAS1-EAS7) show differences to cholesteatoma samples (Chole1-Chole7) relating to the expression of inflammation related genes such as metalloproteinases (e.g. MMP9). The strong co-expression of MMP9 and its known substrate SPP1 (osteopontin 9) might be important. Furthermore, there was a group of patients with low expression of both MMP9 and SPP1, but high expression of genes such as S100A and GJB2.</p