Substance graphs are optimal simple-graph representations of metabolism

作     者：HOLME Petter HUSS Mikael 

作者机构：Department of PhysicsUme University Department of Energy ScienceSungkyunkwan University Science for Life Laboratory Stockholm Box 1031171 21 SolnaSweden Computational and Systems BiologyGenome Institute of Singapore 

出 版 物：《Chinese Science Bulletin》 (科学通报(英文版))

年 卷 期：2010年第55卷第27期

页      面：3161-3168页

核心收录：

学科分类：090502[农学-动物营养与饲料科学] 0905[农学-畜牧学] 09[农学] 

基　　金：PH acknowledges support from the Swedish Foundation for Strategic Research,the Swedish Research Foundation the Japan Society for the Promotion of Science the Project of Knowledge Innovation Program of Chinese Academy of Sciences via the Kavli Institute for Theoretical Physics China the WCU (World Class University) program through the National Research Foundation of Korea funded by the Ministry of Education,Science and Technology(R31-2008-000-10029-0) 

主　　题：图形表示 代谢物 物质 生物数据库 反应体系 化学反应系统 顶点表示 代谢产物 

摘      要：One approach to study the system-wide organization of biochemistry is to use statistical graph theory.In such heavily simplified methods,which disregard most of the dynamic aspects of biochemistry,one is faced with fundamental questions.One such question is how the chemical reaction systems should be reduced to a graph retaining as much functional information as possible from the original reaction system.In these graph representations,should the edges go between substrates and products,or substrates and substrates,or both?Should vertices represent substances or reactions?Different representations encode different information about the reaction system and affect network measures in different ways.This paper investigates which representation reflects the functional organization of the metabolic system in the best way,according to the defined criteria.Four different graph representations of metabolism(three where the vertices are metabolites,one where the vertices are reactions)are evaluated using data from different organisms and databases.The graph representations are evaluated by comparing the overlap between clusters(network modules)and annotated functions,and also by comparing the set of identified currency metabolites with those that other authors have identified using qualitative biological arguments.It is found that asubstance network,where all metabolites participating in a reaction are connected,is better than others,evaluated with respect to both the functional overlap between modules and functions and to the number and identity of the identified currency metabolites.