Pathway Preserving Representation of Metabolic Networks (original) (raw)

Metabolic network visualization eliminating node redundance and preserving metabolic pathways

BMC Systems Biology, 2007

The tools that are available to draw and to manipulate the representations of metabolism are usually restricted to metabolic pathways. This limitation becomes problematic when studying processes that span several pathways. The various attempts that have been made to draw genome-scale metabolic networks are confronted with two shortcomings: 1-they do not use contextual information which leads to dense, hard to interpret drawings, 2-they impose to fit to very constrained standards, which implies, in particular, duplicating nodes making topological analysis considerably more difficult.

Semi-automatic drawing of metabolic networks

Information Visualization

In the living cell, biochemical reactions catalyzed by enzymes are the drivers for metabolic processes like growth, energy production, and replication. Metabolic networks are the representation of these processes describing the complex interactions of biochemical compounds. The large amount of manifold data concerning metabolic networks continually arising from current research activities in biotechnology leads to the great challenge of information visualization. Visualizing information in networks first of all requires appropriate network diagrams. In the context of metabolic networks, historical conventions regarding the network layout have been established. These layouts are not realizable by prevailing algorithms for automatic graph drawing. Hence, manual graph drawing is the predominating way to set up metabolic network diagrams. This is very time-consuming without software support, especially considering large networks with more than 500 nodes. We present a semi-automatic appr...

Guiding the interactive exploration of metabolic pathway interconnections

Information Visualization, 2011

Approaches to investigate biological processes have been of strong interest in the last years and are in the focus of several research areas, especially Systems Biology. Biochemical networks are crucial for such a comprehensive understanding of living beings. Drawings of these networks are often visually overloaded and do not scale. A common solution to deal with this complexity is to divide the complete network, e.g., the metabolism, into a large set of single pathways that are hierarchically structured. If those pathways are visualized, this strategy generates additional navigation and exploration problems as the user looses the context within the complete network. In this paper, we present a general solution of this problem of visualizing interconnected pathways and discuss it in context of biochemical networks. Our new visualization approach supports the analyst to get an overview to related pathways if he/she is working within a particular pathway of interest. By using glyphs, brushing, and topological information of the related pathways, our interactive visualization tool is able to intuitively guide the exploration and navigation process, and thus the analysis processes too. To deal with real data and current networks, our tool has been implemented as plugin for the VANTED system.

J2dpathway: A Global Metabolic Pathway Viewer with Node-Abstracting Features

2008

The static approach of representing metabolic pathway diagrams offers no flexibility. Thus, many systems adopt automatic graph layout techniques to visualize the topological architecture of pathways. There are weaknesses, however, because automatically drawn figures are generally difficult to understand. The problem becomes even more serious when we attempt to visualize all of the information in a single, big picture, which usually results in a confusing diagram. To provide a partial solution to this thorny issue, we propose J2dpathway, a metabolic pathway atlas viewer that has node-abstracting features.

Pathway Tools Visualization of Organism-Scale Metabolic Networks

Metabolites, 2021

Metabolomics, synthetic biology, and microbiome research demand information about organism-scale metabolic networks. The convergence of genome sequencing and computational inference of metabolic networks has enabled great progress toward satisfying that demand by generating metabolic reconstructions from the genomes of thousands of sequenced organisms. Visualization of whole metabolic networks is critical for aiding researchers in understanding, analyzing, and exploiting those reconstructions. We have developed bioinformatics software tools that automatically generate a full metabolic-network diagram for an organism, and that enable searching and analyses of the network. The software generates metabolic-network diagrams for unicellular organisms, for multi-cellular organisms, and for pan-genomes and organism communities. Search tools enable users to find genes, metabolites, enzymes, reactions, and pathways within a diagram. The diagrams are zoomable to enable researchers to study lo...

Domain specific vs Generic Network Visualization: an evaluation with metabolic networks

2011

Metabolic networks have been drawn manually for many years, and over time have developed representational conventions that make them familiar to biologists. With increasing current biological discoveries, these networks need to be frequently updated and modified, and automatic visualization algorithms are thus becoming a necessity. Many existing automatic graph layout algorithms exist, and it is not known whether such generic algorithms are sufficiently useful for biologists, or whether algorithms that specifically consider the existing representational conventions are necessary. No prior task efficiency evaluation studies have been performed on biological network visualizations. This paper reports on an experiment comparing the task efficiency of biologically relevant motif-search tasks using three layouts, two of which were produced using existing generic graph layout algorithms (Force Directed, Hierarchical), and one which was specifically designed to take existing metabolic representation conventions into account (MetaViz). Despite the search task favouring the easy identification of node connectivity in the Force Directed layout, the results showed no efficiency difference between Force Directed and MetaViz. We conclude that embodying the representational conventions in an automatic algorithm is not an impediment to task efficiency, and that some minor improvements to MetaViz would enhance its usefulness for biologists even further. .

A Novel Grid-Based Visualization Approach for Metabolic Networks with Advanced Focus&Context View

Lecture Notes in Computer Science, 2010

The universe of biochemical reactions in metabolic pathways can be modeled as a complex network structure augmented with domain specific annotations. Based on the functional properties of the involved reactions, metabolic networks are often clustered into so-called pathways inferred from expert knowledge. To support the domain expert in the exploration and analysis process, we follow the well-known metaphor with the possibility to select multiple foci. In this paper, we introduce a novel approach to generate an interactive layout of such a metabolic network taking its hierarchical structure into account and present methods for navigation and exploration that preserve the mental map. The layout places the network nodes on a fixed rectilinear grid and routes the edges orthogonally between the node positions. Our approach supports bundled edge routes heuristically minimizing a given cost function based on the number of bends, the number of edge crossings and the density of edges within a bundle.

Visual Network Analysis of Dynamic Metabolic Pathways

We extend our previous work on the exploration of static metabolic networks to evolving, and therefore dynamic, pathways. We apply our visualization software to data from a simulation of early metabolism. Thereby, we show that our technique allows us to test and argue for or against different scenarios for the evolution of metabolic pathways. This supports a profound and efficient analysis of the structure and properties of the generated metabolic networks and its underlying components, while giving the user a vivid impression of the dynamics of the system. The analysis process is inspired by Ben Shneiderman’s mantra of information visualization. For the overview, user-defined diagrams give insight into topological changes of the graph as well as changes in the attribute set associated with the participating enzymes, substances and reactions. This way, “interesting features” in time as well as in space can be recognized. A linked view implementation enables the navigation into more detailed layers of perspective for in-depth analysis of individual network configurations.

A NEW CONSTRAINT-BASED COMPOUND GRAPH LAYOUT ALGORITHM FOR VISUALIZING BIOCHEMICAL NETWORKS

2007

Due to the huge amount of information available in biochemical databases, biologists need sophisticated tools to accurately extract the information from such databases and to interpret it correctly. Those tools must be able to dynamically generate any kind of biochemical sub-graphs (i.e., metabolic pathways, genetic regulation, signal transduction, etc.) in a single graph. The visualization tools must be able to cope with such graphs and to take into account the particular semantics of all kinds of biochemical sub-graphs. Therefore, such tools need generic graph layout algorithms that adapt their behavior to the data semantics. In this paper we present the Constrained Compound Graph Layout (C2GL) algorithm designed for the generic representation of biochemical graphs and in which users can represent knowledge about how to draw graphs in accordance with the biochemical semantics