title: Detection of driver metabolites in the human liver metabolic network using structural controllability analysis.
abstract: BACKGROUND
  Abnormal states in human liver metabolism are major causes of human liver diseases ranging from hepatitis to hepatic tumor. The accumulation in relevant data makes it feasible to derive a large-scale human liver metabolic network (HLMN) and to discover important biological principles or drug-targets based on network analysis. Some studies have shown that interesting biological phenomenon and drug-targets could be discovered by applying structural controllability analysis (which is a newly prevailed concept in networks) to biological networks. The exploration on the connections between structural controllability theory and the HLMN could be used to uncover valuable information on the human liver metabolism from a fresh perspective.
  
  
  RESULTS
  We applied structural controllability analysis to the HLMN and detected driver metabolites. The driver metabolites tend to have strong ability to influence the states of other metabolites and weak susceptibility to be influenced by the states of others. In addition, the metabolites were classified into three classes: critical, high-frequency and low-frequency driver metabolites. Among the identified 36 critical driver metabolites, 27 metabolites were found to be essential; the high-frequency driver metabolites tend to participate in different metabolic pathways, which are important in regulating the whole metabolic systems. Moreover, we explored some other possible connections between the structural controllability theory and the HLMN, and find that transport reactions and the environment play important roles in the human liver metabolism.
  
  
  CONCLUSIONS
  There are interesting connections between the structural controllability theory and the human liver metabolism: driver metabolites have essential biological functions; the crucial role of extracellular metabolites and transport reactions in controlling the HLMN highlights the importance of the environment in the health of human liver metabolism.
authors.forename: Xueming
authors.initials: X
authors.lastname: Liu
authors.affiliation: Key Laboratory of Image Information Processing and Intelligent Control, School of Automation, Huazhong University of Science and Technology, Luoyu Road 1037, 430074 Wuhan, China. lqpan@mail.hust.edu.cn.
authors.forename: Linqiang
authors.initials: L
authors.lastname: Pan
mesh_terms: D019295:Computational Biology / Q000379:methods*; D006801:Humans; D008099:Liver / Q000378:metabolism*; D053858:Metabolic Networks and Pathways; D015203:Reproducibility of Results