Literature DB >> 27187990

Minimum steering node set of complex networks and its applications to biomolecular networks.

Lin Wu1, Min Li2, Jianxin Wang2, Fang-Xiang Wu3.   

Abstract

Many systems of interests in practices can be represented as complex networks. For biological systems, biomolecules do not perform their functions alone but interact with each other to form so-called biomolecular networks. A system is said to be controllable if it can be steered from any initial state to any other final state in finite time. The network controllability has become essential to study the dynamics of the networks and understand the importance of individual nodes in the networks. Some interesting biological phenomena have been discovered in terms of the structural controllability of biomolecular networks. Most of current studies investigate the structural controllability of networks in notion of the minimum driver node sets (MDSs). In this study, the authors analyse the network structural controllability in notion of the minimum steering node sets (MSSs). They first develop a graph-theoretic algorithm to identify the MSS for a given network and then apply it to several biomolecular networks. Application results show that biomolecules identified in the MSSs play essential roles in corresponding biological processes. Furthermore, the application results indicate that the MSSs can reflect the network dynamics and node importance in controlling the networks better than the MDSs.

Entities:  

Mesh:

Substances:

Year:  2016        PMID: 27187990      PMCID: PMC8687185          DOI: 10.1049/iet-syb.2015.0077

Source DB:  PubMed          Journal:  IET Syst Biol        ISSN: 1751-8849            Impact factor:   1.615


  19 in total

1.  Controllability of complex networks.

Authors:  Yang-Yu Liu; Jean-Jacques Slotine; Albert-László Barabási
Journal:  Nature       Date:  2011-05-12       Impact factor: 49.962

2.  Control profiles of complex networks.

Authors:  Justin Ruths; Derek Ruths
Journal:  Science       Date:  2014-03-21       Impact factor: 47.728

3.  Identifying Driver Nodes in the Human Signaling Network Using Structural Controllability Analysis.

Authors:  Xueming Liu; Linqiang Pan
Journal:  IEEE/ACM Trans Comput Biol Bioinform       Date:  2015 Mar-Apr       Impact factor: 3.710

Review 4.  C/EBPalpha induces PU.1 and interacts with AP-1 and NF-kappaB to regulate myeloid development.

Authors:  Alan D Friedman
Journal:  Blood Cells Mol Dis       Date:  2007-07-31       Impact factor: 3.039

5.  A novel network integrating a miRNA-203/SNAI1 feedback loop which regulates epithelial to mesenchymal transition.

Authors:  Michèle Moes; Antony Le Béchec; Isaac Crespo; Christina Laurini; Aliaksandr Halavatyi; Guillaume Vetter; Antonio Del Sol; Evelyne Friederich
Journal:  PLoS One       Date:  2012-04-13       Impact factor: 3.240

6.  Transittability of complex networks and its applications to regulatory biomolecular networks.

Authors:  Fang-Xiang Wu; Lin Wu; Jianxin Wang; Juan Liu; Luonan Chen
Journal:  Sci Rep       Date:  2014-04-28       Impact factor: 4.379

7.  Target control of complex networks.

Authors:  Jianxi Gao; Yang-Yu Liu; Raissa M D'Souza; Albert-László Barabási
Journal:  Nat Commun       Date:  2014-11-12       Impact factor: 14.919

8.  Finding multiple target optimal intervention in disease-related molecular network.

Authors:  Kun Yang; Hongjun Bai; Qi Ouyang; Luhua Lai; Chao Tang
Journal:  Mol Syst Biol       Date:  2008-11-04       Impact factor: 11.429

9.  Control capacity and a random sampling method in exploring controllability of complex networks.

Authors:  Tao Jia; Albert-László Barabási
Journal:  Sci Rep       Date:  2013       Impact factor: 4.379

10.  Detection of driver metabolites in the human liver metabolic network using structural controllability analysis.

Authors:  Xueming Liu; Linqiang Pan
Journal:  BMC Syst Biol       Date:  2014-05-03
View more
  1 in total

1.  Control Analysis of Protein-Protein Interaction Network Reveals Potential Regulatory Targets for MYCN.

Authors:  Chunyu Pan; Yuyan Zhu; Meng Yu; Yongkang Zhao; Changsheng Zhang; Xizhe Zhang; Yang Yao
Journal:  Front Oncol       Date:  2021-04-21       Impact factor: 6.244

  1 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.