Metabolic network visualization eliminating node redundance and preserving metabolic pathways

Background 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 meta...
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Autor*in:	Bourqui, Romain [verfasserIn] Cottret, Ludovic Lacroix, Vincent Auber, David Mary, Patrick Sagot, Marie-France Jourdan, Fabien

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2007

Schlagwörter:	Metabolic Pathway Metabolic Network Dependence Graph Quotient Graph Mixed Graph

Anmerkung:	© Bourqui et al; licensee BioMed Central Ltd. 2007. This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (

Übergeordnetes Werk:	Enthalten in: BMC systems biology - London : BioMed Central, 2007, 1(2007), 1 vom: 03. Juli
Übergeordnetes Werk:	volume:1 ; year:2007 ; number:1 ; day:03 ; month:07

Links:	Volltext

DOI / URN:	10.1186/1752-0509-1-29

Katalog-ID:	SPR028403304

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520			\|a Background 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. Results We propose a method, called MetaViz, which enables to draw a genome-scale metabolic network and that also takes into account its structuration into pathways. This method consists in two steps: a clustering step which addresses the pathway overlapping problem and a drawing step which consists in drawing the clustered graph and each cluster. Conclusion The method we propose is original and addresses new drawing issues arising from the no-duplication constraint. We do not propose a single drawing but rather several alternative ways of presenting metabolism depending on the pathway on which one wishes to focus. We believe that this provides a valuable tool to explore the pathway structure of metabolism.
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allfields	10.1186/1752-0509-1-29 doi (DE-627)SPR028403304 (SPR)1752-0509-1-29-e DE-627 ger DE-627 rakwb eng Bourqui, Romain verfasserin aut Metabolic network visualization eliminating node redundance and preserving metabolic pathways 2007 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Bourqui et al; licensee BioMed Central Ltd. 2007. This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( Background 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. Results We propose a method, called MetaViz, which enables to draw a genome-scale metabolic network and that also takes into account its structuration into pathways. This method consists in two steps: a clustering step which addresses the pathway overlapping problem and a drawing step which consists in drawing the clustered graph and each cluster. Conclusion The method we propose is original and addresses new drawing issues arising from the no-duplication constraint. We do not propose a single drawing but rather several alternative ways of presenting metabolism depending on the pathway on which one wishes to focus. We believe that this provides a valuable tool to explore the pathway structure of metabolism. Metabolic Pathway (dpeaa)DE-He213 Metabolic Network (dpeaa)DE-He213 Dependence Graph (dpeaa)DE-He213 Quotient Graph (dpeaa)DE-He213 Mixed Graph (dpeaa)DE-He213 Cottret, Ludovic aut Lacroix, Vincent aut Auber, David aut Mary, Patrick aut Sagot, Marie-France aut Jourdan, Fabien aut Enthalten in BMC systems biology London : BioMed Central, 2007 1(2007), 1 vom: 03. Juli (DE-627)522897126 (DE-600)2265490-2 1752-0509 nnns volume:1 year:2007 number:1 day:03 month:07 https://dx.doi.org/10.1186/1752-0509-1-29 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 1 2007 1 03 07
spelling	10.1186/1752-0509-1-29 doi (DE-627)SPR028403304 (SPR)1752-0509-1-29-e DE-627 ger DE-627 rakwb eng Bourqui, Romain verfasserin aut Metabolic network visualization eliminating node redundance and preserving metabolic pathways 2007 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Bourqui et al; licensee BioMed Central Ltd. 2007. This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( Background 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. Results We propose a method, called MetaViz, which enables to draw a genome-scale metabolic network and that also takes into account its structuration into pathways. This method consists in two steps: a clustering step which addresses the pathway overlapping problem and a drawing step which consists in drawing the clustered graph and each cluster. Conclusion The method we propose is original and addresses new drawing issues arising from the no-duplication constraint. We do not propose a single drawing but rather several alternative ways of presenting metabolism depending on the pathway on which one wishes to focus. We believe that this provides a valuable tool to explore the pathway structure of metabolism. Metabolic Pathway (dpeaa)DE-He213 Metabolic Network (dpeaa)DE-He213 Dependence Graph (dpeaa)DE-He213 Quotient Graph (dpeaa)DE-He213 Mixed Graph (dpeaa)DE-He213 Cottret, Ludovic aut Lacroix, Vincent aut Auber, David aut Mary, Patrick aut Sagot, Marie-France aut Jourdan, Fabien aut Enthalten in BMC systems biology London : BioMed Central, 2007 1(2007), 1 vom: 03. Juli (DE-627)522897126 (DE-600)2265490-2 1752-0509 nnns volume:1 year:2007 number:1 day:03 month:07 https://dx.doi.org/10.1186/1752-0509-1-29 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 1 2007 1 03 07
allfields_unstemmed	10.1186/1752-0509-1-29 doi (DE-627)SPR028403304 (SPR)1752-0509-1-29-e DE-627 ger DE-627 rakwb eng Bourqui, Romain verfasserin aut Metabolic network visualization eliminating node redundance and preserving metabolic pathways 2007 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Bourqui et al; licensee BioMed Central Ltd. 2007. This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( Background 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. Results We propose a method, called MetaViz, which enables to draw a genome-scale metabolic network and that also takes into account its structuration into pathways. This method consists in two steps: a clustering step which addresses the pathway overlapping problem and a drawing step which consists in drawing the clustered graph and each cluster. Conclusion The method we propose is original and addresses new drawing issues arising from the no-duplication constraint. We do not propose a single drawing but rather several alternative ways of presenting metabolism depending on the pathway on which one wishes to focus. We believe that this provides a valuable tool to explore the pathway structure of metabolism. Metabolic Pathway (dpeaa)DE-He213 Metabolic Network (dpeaa)DE-He213 Dependence Graph (dpeaa)DE-He213 Quotient Graph (dpeaa)DE-He213 Mixed Graph (dpeaa)DE-He213 Cottret, Ludovic aut Lacroix, Vincent aut Auber, David aut Mary, Patrick aut Sagot, Marie-France aut Jourdan, Fabien aut Enthalten in BMC systems biology London : BioMed Central, 2007 1(2007), 1 vom: 03. Juli (DE-627)522897126 (DE-600)2265490-2 1752-0509 nnns volume:1 year:2007 number:1 day:03 month:07 https://dx.doi.org/10.1186/1752-0509-1-29 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 1 2007 1 03 07
allfieldsGer	10.1186/1752-0509-1-29 doi (DE-627)SPR028403304 (SPR)1752-0509-1-29-e DE-627 ger DE-627 rakwb eng Bourqui, Romain verfasserin aut Metabolic network visualization eliminating node redundance and preserving metabolic pathways 2007 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Bourqui et al; licensee BioMed Central Ltd. 2007. This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( Background 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. Results We propose a method, called MetaViz, which enables to draw a genome-scale metabolic network and that also takes into account its structuration into pathways. This method consists in two steps: a clustering step which addresses the pathway overlapping problem and a drawing step which consists in drawing the clustered graph and each cluster. Conclusion The method we propose is original and addresses new drawing issues arising from the no-duplication constraint. We do not propose a single drawing but rather several alternative ways of presenting metabolism depending on the pathway on which one wishes to focus. We believe that this provides a valuable tool to explore the pathway structure of metabolism. Metabolic Pathway (dpeaa)DE-He213 Metabolic Network (dpeaa)DE-He213 Dependence Graph (dpeaa)DE-He213 Quotient Graph (dpeaa)DE-He213 Mixed Graph (dpeaa)DE-He213 Cottret, Ludovic aut Lacroix, Vincent aut Auber, David aut Mary, Patrick aut Sagot, Marie-France aut Jourdan, Fabien aut Enthalten in BMC systems biology London : BioMed Central, 2007 1(2007), 1 vom: 03. Juli (DE-627)522897126 (DE-600)2265490-2 1752-0509 nnns volume:1 year:2007 number:1 day:03 month:07 https://dx.doi.org/10.1186/1752-0509-1-29 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 1 2007 1 03 07
allfieldsSound	10.1186/1752-0509-1-29 doi (DE-627)SPR028403304 (SPR)1752-0509-1-29-e DE-627 ger DE-627 rakwb eng Bourqui, Romain verfasserin aut Metabolic network visualization eliminating node redundance and preserving metabolic pathways 2007 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Bourqui et al; licensee BioMed Central Ltd. 2007. This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( Background 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. Results We propose a method, called MetaViz, which enables to draw a genome-scale metabolic network and that also takes into account its structuration into pathways. This method consists in two steps: a clustering step which addresses the pathway overlapping problem and a drawing step which consists in drawing the clustered graph and each cluster. Conclusion The method we propose is original and addresses new drawing issues arising from the no-duplication constraint. We do not propose a single drawing but rather several alternative ways of presenting metabolism depending on the pathway on which one wishes to focus. We believe that this provides a valuable tool to explore the pathway structure of metabolism. Metabolic Pathway (dpeaa)DE-He213 Metabolic Network (dpeaa)DE-He213 Dependence Graph (dpeaa)DE-He213 Quotient Graph (dpeaa)DE-He213 Mixed Graph (dpeaa)DE-He213 Cottret, Ludovic aut Lacroix, Vincent aut Auber, David aut Mary, Patrick aut Sagot, Marie-France aut Jourdan, Fabien aut Enthalten in BMC systems biology London : BioMed Central, 2007 1(2007), 1 vom: 03. Juli (DE-627)522897126 (DE-600)2265490-2 1752-0509 nnns volume:1 year:2007 number:1 day:03 month:07 https://dx.doi.org/10.1186/1752-0509-1-29 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 1 2007 1 03 07
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This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Background 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. 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topic_title	Metabolic network visualization eliminating node redundance and preserving metabolic pathways Metabolic Pathway (dpeaa)DE-He213 Metabolic Network (dpeaa)DE-He213 Dependence Graph (dpeaa)DE-He213 Quotient Graph (dpeaa)DE-He213 Mixed Graph (dpeaa)DE-He213
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title	Metabolic network visualization eliminating node redundance and preserving metabolic pathways
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title_sort	metabolic network visualization eliminating node redundance and preserving metabolic pathways
title_auth	Metabolic network visualization eliminating node redundance and preserving metabolic pathways
abstract	Background 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. Results We propose a method, called MetaViz, which enables to draw a genome-scale metabolic network and that also takes into account its structuration into pathways. This method consists in two steps: a clustering step which addresses the pathway overlapping problem and a drawing step which consists in drawing the clustered graph and each cluster. Conclusion The method we propose is original and addresses new drawing issues arising from the no-duplication constraint. We do not propose a single drawing but rather several alternative ways of presenting metabolism depending on the pathway on which one wishes to focus. We believe that this provides a valuable tool to explore the pathway structure of metabolism. © Bourqui et al; licensee BioMed Central Ltd. 2007. This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (
abstractGer	Background 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. Results We propose a method, called MetaViz, which enables to draw a genome-scale metabolic network and that also takes into account its structuration into pathways. This method consists in two steps: a clustering step which addresses the pathway overlapping problem and a drawing step which consists in drawing the clustered graph and each cluster. Conclusion The method we propose is original and addresses new drawing issues arising from the no-duplication constraint. We do not propose a single drawing but rather several alternative ways of presenting metabolism depending on the pathway on which one wishes to focus. We believe that this provides a valuable tool to explore the pathway structure of metabolism. © Bourqui et al; licensee BioMed Central Ltd. 2007. This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (
abstract_unstemmed	Background 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. Results We propose a method, called MetaViz, which enables to draw a genome-scale metabolic network and that also takes into account its structuration into pathways. This method consists in two steps: a clustering step which addresses the pathway overlapping problem and a drawing step which consists in drawing the clustered graph and each cluster. Conclusion The method we propose is original and addresses new drawing issues arising from the no-duplication constraint. We do not propose a single drawing but rather several alternative ways of presenting metabolism depending on the pathway on which one wishes to focus. We believe that this provides a valuable tool to explore the pathway structure of metabolism. © Bourqui et al; licensee BioMed Central Ltd. 2007. This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (
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title_short	Metabolic network visualization eliminating node redundance and preserving metabolic pathways
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author2	Cottret, Ludovic Lacroix, Vincent Auber, David Mary, Patrick Sagot, Marie-France Jourdan, Fabien
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Metabolic network visualization eliminating node redundance and preserving metabolic pathways

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