TY - JOUR
T1 - Visual exploration of large metabolic models
AU - Aichem, Michael
AU - Czauderna, Tobias
AU - Zhu, Yan
AU - Zhao, Jinxin
AU - Klapperstück, Matthias
AU - Klein, Karsten
AU - Li, Jian
AU - Schreiber, Falk
N1 - Publisher Copyright:
© 2021 The Author(s) 2021. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: [email protected].
PY - 2021/5/10
Y1 - 2021/5/10
N2 - Motivation: Large metabolic models, including genome-scale metabolic models, are nowadays common in systems biology, biotechnology and pharmacology. They typically contain thousands of metabolites and reactions and therefore methods for their automatic visualization and interactive exploration can facilitate a better understanding of these models. Results: We developed a novel method for the visual exploration of large metabolic models and implemented it in LMME (Large Metabolic Model Explorer), an add-on for the biological network analysis tool VANTED. The underlying idea of our method is to analyze a large model as follows. Starting from a decomposition into several subsystems, relationships between these subsystems are identified and an overview is computed and visualized. From this overview, detailed subviews may be constructed and visualized in order to explore subsystems and relationships in greater detail. Decompositions may either be predefined or computed, using built-in or self-implemented methods. Realized as add-on for VANTED, LMME is embedded in a domain-specific environment, allowing for further related analysis at any stage during the exploration. We describe the method, provide a use case and discuss the strengths and weaknesses of different decomposition methods.
AB - Motivation: Large metabolic models, including genome-scale metabolic models, are nowadays common in systems biology, biotechnology and pharmacology. They typically contain thousands of metabolites and reactions and therefore methods for their automatic visualization and interactive exploration can facilitate a better understanding of these models. Results: We developed a novel method for the visual exploration of large metabolic models and implemented it in LMME (Large Metabolic Model Explorer), an add-on for the biological network analysis tool VANTED. The underlying idea of our method is to analyze a large model as follows. Starting from a decomposition into several subsystems, relationships between these subsystems are identified and an overview is computed and visualized. From this overview, detailed subviews may be constructed and visualized in order to explore subsystems and relationships in greater detail. Decompositions may either be predefined or computed, using built-in or self-implemented methods. Realized as add-on for VANTED, LMME is embedded in a domain-specific environment, allowing for further related analysis at any stage during the exploration. We describe the method, provide a use case and discuss the strengths and weaknesses of different decomposition methods.
UR - https://www.scopus.com/pages/publications/85122215006
U2 - 10.1093/bioinformatics/btab335
DO - 10.1093/bioinformatics/btab335
M3 - Article
C2 - 33970212
AN - SCOPUS:85122215006
SN - 1367-4803
VL - 37
SP - 4460
EP - 4468
JO - Bioinformatics
JF - Bioinformatics
IS - 23
ER -