Visualization of Metabolic Networks

A special issue of Metabolites (ISSN 2218-1989). This special issue belongs to the section "Bioinformatics and Data Analysis".

Deadline for manuscript submissions: closed (31 December 2021) | Viewed by 9435

Special Issue Editor

SRI International, Menlo Park, CA 94025, USA
Interests: pathway bioinformatics; metabolic modeling; genome informatics
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Metabolic networks are important in many areas of the life sciences, from understanding human disease to synthetic biology to bioremediation and industrial microbiology.  Genome sequencing has given rise to genome-scale understanding of metabolic networks, and metagenomic sequencing has yielded understanding of the metabolic networks of organism communities.  Genome-scale metabolic modeling has produced quantitative models of whole metabolic networks.  The complexity of whole-organism metabolic networks calls for visualization methods that enable scientists to more quickly grasp and interrogate these networks.  Yet traditional graph layout techniques have not produced satisfying results for metabolic networks, so researchers have developed metabolism-specific layout algorithms.  This special issue of Metabolites is dedicated to studies of the visualization of metabolic networks above the pathway level, be they organism- or near-organism-scale metabolic networks, or community-scale metabolic networks.

Dr. Peter D. Karp
Guest Editor

Manuscript Submission Information

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Keywords

  • Metabolic networks
  • Visualization
  • Pathways

Published Papers (2 papers)

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Research

10 pages, 949 KiB  
Article
IDARE2—Simultaneous Visualisation of Multiomics Data in Cytoscape
by Thomas Pfau, Mafalda Galhardo, Jake Lin and Thomas Sauter
Metabolites 2021, 11(5), 300; https://0-doi-org.brum.beds.ac.uk/10.3390/metabo11050300 - 06 May 2021
Cited by 2 | Viewed by 2550
Abstract
Visual integration of experimental data in metabolic networks is an important step to understanding their meaning. As genome-scale metabolic networks reach several thousand reactions, the task becomes more difficult and less revealing. While databases like KEGG and BioCyc provide curated pathways that allow [...] Read more.
Visual integration of experimental data in metabolic networks is an important step to understanding their meaning. As genome-scale metabolic networks reach several thousand reactions, the task becomes more difficult and less revealing. While databases like KEGG and BioCyc provide curated pathways that allow a navigation of the metabolic landscape of an organism, it is rather laborious to map data directly onto those pathways. There are programs available using these kind of databases as a source for visualization; however, these programs are then restricted to the pathways available in the database. Here, we present IDARE2 a cytoscape plugin that allows the visualization of multiomics data in cytoscape in a user-friendly way. It further provides tools to disentangle highly connected network structures based on common properties of nodes and retains structural links between the generated subnetworks, offering a straightforward way to traverse the splitted network. The tool is extensible, allowing the implementation of specialised representations and data format parsers. We present the automated reproduction of the original IDARE nodes using our tool and show examples of other data being mapped on a network of E. coli. The extensibility is demonstrated with two plugins that are available on github. IDARE2 provides an intuitive way to visualise data from multiple sources and allows one to disentangle the often complex network structure in large networks using predefined properties of the network nodes. Full article
(This article belongs to the Special Issue Visualization of Metabolic Networks)
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14 pages, 5492 KiB  
Article
Pathway Tools Visualization of Organism-Scale Metabolic Networks
by Suzanne Paley, Richard Billington, James Herson, Markus Krummenacker and Peter D. Karp
Metabolites 2021, 11(2), 64; https://0-doi-org.brum.beds.ac.uk/10.3390/metabo11020064 - 22 Jan 2021
Cited by 8 | Viewed by 6272
Abstract
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. [...] Read more.
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 local neighborhoods in detail and to see the big picture. The diagrams also serve as tools for comparison of metabolic networks and for interpreting high-throughput datasets, including transcriptomics, metabolomics, and reaction fluxes computed by metabolic models. These data can be overlaid on the metabolic charts to produce animated zoomable displays of metabolic flux and metabolite abundance. The BioCyc.org website contains whole-network diagrams for more than 18,000 sequenced organisms. The ready availability of organism-specific metabolic network diagrams and associated tools for almost any sequenced organism are useful for researchers working to better understand the metabolism of their organism and to interpret high-throughput datasets in a metabolic context. Full article
(This article belongs to the Special Issue Visualization of Metabolic Networks)
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