메뉴 건너뛰기




Volumn 47, Issue 6, 2011, Pages 1230-1235

Robust dynamical network structure reconstruction

Author keywords

Noise and unmodelled dynamics; Robust network reconstruction; Systems biology

Indexed keywords

BIOLOGICALLY INSPIRED NETWORKS; DYNAMICAL NETWORKS; LTI SYSTEMS; MEASURED DATA; NETWORK RECONSTRUCTION; NETWORK STRUCTURES; NON-LINEARITY; ROBUST NETWORK RECONSTRUCTION; SUFFICIENT CONDITIONS; SYSTEM IDENTIFICATIONS; SYSTEMS BIOLOGY; UNMODELLED DYNAMICS;

EID: 79956210094     PISSN: 00051098     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.automatica.2011.03.008     Document Type: Article
Times cited : (132)

References (27)
  • 2
    • 34548388925 scopus 로고    scopus 로고
    • Inference of gene networks from temporal gene expression profiles
    • DOI 10.1049/iet-syb:20060079
    • M. Bansal, and D. di Bernardo Inference of gene networks from temporal gene expression profiles IET Systems Biology 1 5 2007 306 312 (Pubitemid 47354629)
    • (2007) IET Systems Biology , vol.1 , Issue.5 , pp. 306-312
    • Bansal, M.1    Di Bernardo, D.2
  • 4
    • 33747813561 scopus 로고    scopus 로고
    • The inferelator: An algorithm for learning parsimonious regulatory networks from systems-biology data sets de novo
    • R. Bonneau, D. Reiss, P. Shannon, M. Facciotti, L. Hood, N. Baliga, and V. Thorsson The inferelator: an algorithm for learning parsimonious regulatory networks from systems-biology data sets de novo Genome Biology 7 2006 R36
    • (2006) Genome Biology , vol.7 , pp. 36
    • Bonneau, R.1    Reiss, D.2    Shannon, P.3    Facciotti, M.4    Hood, L.5    Baliga, N.6    Thorsson, V.7
  • 6
    • 0033655775 scopus 로고    scopus 로고
    • Mutual information relevance networks: Functional genomic clustering using pairwise entropy measurements
    • Butte, A.; Kohane, I. (2000). Mutual information relevance networks: functional genomic clustering using pairwise entropy measurements. In Pac. symp. biocomput. pp. 418429.
    • (2000) . Symp. Biocomput , pp. 418-429
    • Butte, A.1    Kohane, I.2
  • 8
    • 77957110013 scopus 로고    scopus 로고
    • Advantages and limitations of current network inference methods
    • R. De Smet, and K. Marchal Advantages and limitations of current network inference methods Nature Reviews Microbiology 8 2010
    • (2010) Nature Reviews Microbiology , vol.8
    • De Smet, R.1    Marchal, K.2
  • 12
    • 0038048325 scopus 로고    scopus 로고
    • Inferring genetic networks and identifying compound mode of action via expression profiling
    • T. Gardner, D. Bernardo, D. Lorenz, and J. Colins Inferring genetic networks and identifying compound mode of action via expression profiling Science 301 2003
    • (2003) Science , vol.301
    • Gardner, T.1    Bernardo, D.2    Lorenz, D.3    Colins, J.4
  • 13
    • 52249116064 scopus 로고    scopus 로고
    • Necessary and sufficient conditions for dynamical structure reconstruction of LTI networks
    • J. Gonalves, and S. Warnick Necessary and sufficient conditions for dynamical structure reconstruction of LTI networks IEEE Transactions on Automatic Control 53 2008
    • (2008) IEEE Transactions on Automatic Control , vol.53
    • Gonalves, J.1    Warnick, S.2
  • 14
  • 15
    • 61349180117 scopus 로고    scopus 로고
    • Gene regulatory network inference: Data integration in dynamic modelsa review
    • M. Hecker, S. Lambeck, S. Toepfer, E. Someren, and R. Guthke Gene regulatory network inference: data integration in dynamic modelsa review BioSystems 2009
    • (2009) BioSystems
    • Hecker, M.1    Lambeck, S.2    Toepfer, S.3    Someren, E.4    Guthke, R.5
  • 16
    • 0016355478 scopus 로고
    • A new look at the statistical model identification
    • A. Hirotugu A new look at the statistical model identification IEEE Transactions on Automatic Control 19 6 1974 716 723
    • (1974) IEEE Transactions on Automatic Control , vol.19 , Issue.6 , pp. 716-723
    • Hirotugu, A.1
  • 17
    • 79952196617 scopus 로고    scopus 로고
    • Algorithmic and analytical methods in network biology
    • M. Koyuturk Algorithmic and analytical methods in network biology WIREs Systems Biology and Medicine 2 3 2010 277 292
    • (2010) WIREs Systems Biology and Medicine , vol.2 , Issue.3 , pp. 277-292
    • Koyuturk, M.1
  • 19
    • 70349548793 scopus 로고    scopus 로고
    • Interampattenessa generic property of biochemical networks
    • T. Nordling, and E. Jacobsen Interampattenessa generic property of biochemical networks IET Systems Biology 2009
    • (2009) IET Systems Biology
    • Nordling, T.1    Jacobsen, E.2
  • 20
    • 71049191527 scopus 로고    scopus 로고
    • A model invalidation-based approach for elucidating biological signalling pathways, applied to the chemotaxis pathway in R. sphaeroides
    • M. Roberts, E. August, A. Hamadeh, P. Maini, P. McSharry, J. Armitage, and A. Papachristodoulou A model invalidation-based approach for elucidating biological signalling pathways, applied to the chemotaxis pathway in R. sphaeroides BMC Systems Biology 3 105 2009
    • (2009) BMC Systems Biology , vol.3 , Issue.105
    • Roberts, M.1    August, E.2    Hamadeh, A.3    Maini, P.4    McSharry, P.5    Armitage, J.6    Papachristodoulou, A.7
  • 21
    • 58149234398 scopus 로고    scopus 로고
    • Network reconstruction based on steady-state data
    • E. Sontag Network reconstruction based on steady-state data Essays in Biochemistry 45 2008 161 176
    • (2008) Essays in Biochemistry , vol.45 , pp. 161-176
    • Sontag, E.1
  • 22
    • 10044252242 scopus 로고    scopus 로고
    • Making sense of it all: Bacterial chemotaxis
    • DOI 10.1038/nrm1524
    • G. Wadhams, and J. Armitage Making sense of it all: bacterial chemotaxis Nature Reviews Molecular Cell Biology 5 2004 1024 1037 (Pubitemid 39611538)
    • (2004) Nature Reviews Molecular Cell Biology , vol.5 , Issue.12 , pp. 1024-1037
    • Wadhams, G.H.1    Armitage, J.P.2
  • 24
    • 12344259602 scopus 로고    scopus 로고
    • Advances to Bayesian network inference for generating causal networks from observational biological data
    • DOI 10.1093/bioinformatics/bth448
    • J. Yu, V. Smith, P. Wang, A. Hartemink, and E. Jarvis Advances to Bayesian network inference for generating causal networks from observational biological data Bioinformatics 20 18 2004 3594 3603 (Pubitemid 40136795)
    • (2004) Bioinformatics , vol.20 , Issue.18 , pp. 3594-3603
    • Yu, J.1    Smith, V.A.2    Wang, P.P.3    Hartemink, A.J.4    Jarvis, E.D.5


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.