Flux visualization using VANTED/FluxMap.

The calculation of metabolic fluxes has been shown to be a valuable asset in systems biology. Several procedures are commonly used to achieve this. Flux balance analyses or metabolic flux analyses usually result in a list of reaction rates (fluxes) provided in a spreadsheet format. This makes it difficult to quickly assess general characteristics of the solution. A fast and easy mapping of these results to a graphical map template facilitates an easy visual data inspection. Here, we describe a protocol that helps in setting up user-specific network templates, mapping flux results to it, and creating multiple exportable flux maps at one time.

Visual analysis of transcriptome data in the context of anatomical structures and biological networks.

The complexity and temporal as well as spatial resolution of transcriptome datasets is constantly increasing due to extensive technological developments. Here we present methods for advanced visualization and intuitive exploration of transcriptomics data as necessary prerequisites in order to facilitate the gain of biological knowledge. Color-coding of structural images based on the expression level enables a fast visual data analysis in the background of the examined biological system. The network-based exploration of these visualizations allows for comparative analysis of genes with specific transcript patterns and supports the extraction of functional relationships even from large datasets. In order to illustrate the presented methods, the tool HIVE was applied for visualization and exploration of database-retrieved expression data for master regulators of Arabidopsis thaliana flower and seed development in the context of corresponding tissue-specific regulatory networks.

VANTED v2: a framework for systems biology applications.

BACKGROUND: Experimental datasets are becoming larger and increasingly complex, spanning different data domains, thereby expanding the requirements for respective tool support for their analysis. Networks provide a basis for the integration, analysis and visualization of multi-omics experimental datasets. RESULTS: Here we present VANTED (version 2), a framework for systems biology applications, which comprises a comprehensive set of seven main tasks. These range from network reconstruction, data visualization, integration of various data types, network simulation to data exploration combined with a manifold support of systems biology standards for visualization and data exchange. The offered set of functionalities is instantiated by combining several tasks in order to enable users to view and explore a comprehensive dataset from different perspectives. We describe the system as well as an exemplary workflow. CONCLUSIONS: VANTED is a stand-alone framework which supports scientists during the data analysis and interpretation phase. It is available as a Java open source tool from http://www.vanted.org.

FluxMap: a VANTED add-on for the visual exploration of flux distributions in biological networks.

BACKGROUND: The quantification of metabolic fluxes is gaining increasing importance in the analysis of the metabolic behavior of biological systems such as organisms, tissues or cells. Various methodologies (wetlab or drylab) result in sets of fluxes which require an appropriate visualization for interpretation by scientists. The visualization of flux distributions is a necessary prerequisite for intuitive flux data exploration in the context of metabolic networks. RESULTS: We present FluxMap, a tool for the advanced visualization and exploration of flux data in the context of metabolic networks. The template-based flux data import assigns flux values and optional quality parameters (e. g. the confidence interval) to biochemical reactions. It supports the discrimination between mass and substance fluxes, such as C- or N-fluxes. After import, flux data mapping and network-based visualization allow the interactive exploration of the dataset. Various visualization options enable the user to adapt layout and network representation according to individual purposes. CONCLUSIONS: The Vanted add-on FluxMap comprises a comprehensive set of functionalities for visualization and advanced visual exploration of flux distributions in biological networks. It is available as a Java open source tool from http://www.vanted.org/fluxmap.

Creating interactive, web-based and data-enriched maps with the Systems Biology Graphical Notation.

The Systems Biology Graphical Notation (SBGN) is an emerging standard for the uniform representation of biological processes and networks. By using examples from gene regulation and metabolism, this protocol shows the construction of SBGN maps by either manual drawing or automatic translation using the tool SBGN-ED. In addition, it discusses the enrichment of SBGN maps with different kinds of -omics data to bring numerical data into the context of these networks in order to facilitate the interpretation of experimental data. Finally, the export of such maps to public websites, including clickable images, supports the communication of results within the scientific community. With regard to the described functionalities, other tools partially overlap with SBGN-ED. However, currently, SBGN-ED is the only tool that combines all of these functions, including the representation in SBGN, data mapping and website export. This protocol aims to assist scientists with the step-by-step procedure, which altogether takes ∼90 min.

Creating views on integrated multidomain data.

MOTIVATION: Modern data acquisition methods in biology allow the procurement of different types of data in increasing quantity, facilitating a comprehensive view of biological systems. As data are usually gathered and interpreted by separate domain scientists, it is hard to grasp multidomain properties and structures. Consequently, there is a need for the integration of biological data from different sources and of different types in one application, providing various visualization approaches. RESULTS: In this article, methods for the integration and visualization of multimodal biological data are presented. This is achieved based on two graphs representing the meta-relations between biological data and the measurement combinations, respectively. Both graphs are linked and serve as different views of the integrated data with navigation and exploration possibilities. Data can be combined and visualized multifariously, resulting in views of the integrated biological data. AVAILABILITY: http://vanted.ipk-gatersleben.de/hive/. CONTACT: rohn@ipk-gatersleben.de.