Metabolic network visualization eliminating node redundance and preserving metabolic pathways

Author:

Bourqui Romain,Cottret Ludovic,Lacroix Vincent,Auber David,Mary Patrick,Sagot Marie-France,Jourdan Fabien

Abstract

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.

Publisher

Springer Science and Business Media LLC

Subject

Applied Mathematics,Computer Science Applications,Molecular Biology,Modeling and Simulation,Structural Biology

Reference47 articles.

1. Karp PD, Paley SM: Automated Drawing of Metabolic Pathways. Third International Conference on Bioinformatics and Genome Research. 1994

2. Salamonsen , Yee , Mok , Kolatkar : BioJAKE: a tool for the creation, visualization and manipulation of metabolic pathways. Pacific Symposium on Biocomputing. 1999, 4: 392-400.

3. Kanehisa M: Post-genome Informatics. 2000, Oxford University Press

4. Becker M, Rojas I: A Graph Layout Algorithm for Drawing Metabolic Pathways. Bioinformatics. 2001, 17: 461-467. 10.1093/bioinformatics/17.5.461

5. Seo J, Shneiderman B: Interactively Exploring Hierarchical Clustering Results. IEEE Computer. 2002, 35 (7): 80-86.

Cited by 36 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Plant genome-scale metabolic networks;Advances in Botanical Research;2021

2. Disease Biomarker Discovery;Encyclopedia of Bioinformatics and Computational Biology;2019

3. Graph Theory and Definitions;Encyclopedia of Bioinformatics and Computational Biology;2019

4. SCAN-Toolbox: Structural COBRA Add-oN (SCAN) for Analysing Large Metabolic Networks;Current Bioinformatics;2018-02-19

5. FindPrimaryPairs: An efficient algorithm for predicting element-transferring reactant/product pairs in metabolic networks;PLOS ONE;2018-02-15

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3