메뉴 건너뛰기




Volumn , Issue , 2007, Pages 82-89

Inference of gene regulatory networks using S-system: A unified approach

Author keywords

[No Author keywords available]

Indexed keywords

DOWNHILL SIMPLEX ALGORITHMS; GENE INTERACTIONS; GENE REGULATORY NETWORKS; LARGE-SCALE GENE REGULATORY NETWORKS; OPTIMIZATION ALGORITHMS; POWELL ALGORITHMS; RECURSIVE LEAST SQUARE ESTIMATIONS; UNIFIED APPROACH;

EID: 84886012461     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (21)

References (18)
  • 1
    • 0031626858 scopus 로고    scopus 로고
    • Rules for the evolution of gene circuitry
    • M. A. Savageau, "Rules for the Evolution of Gene Circuitry", Pac. Symp. Biocomputing, 3: 54-65, 1998.
    • (1998) Pac. Symp. Biocomputing , vol.3 , pp. 54-65
    • Savageau, M.A.1
  • 5
    • 32444432616 scopus 로고    scopus 로고
    • Inference of gene regulatory networks using S-system and Differential Evolution
    • DOI 10.1145/1068009.1068079, GECCO 2005 - Genetic and Evolutionary Computation Conference
    • N. Norman and H. Iba, "Inference of Gene Regulatory Networks Using S-system and Differential Evolution", Proceedings of GECCO, pp.439-446, 2005. (Pubitemid 43226322)
    • (2005) GECCO 2005 - Genetic and Evolutionary Computation Conference , pp. 439-446
    • Noman, N.1    Iba, H.2
  • 7
    • 0037461033 scopus 로고    scopus 로고
    • Dynamics modeling of genetic networks using genetic algorithm and S-system
    • DOI 10.1093/bioinformatics/btg027
    • S. Kikuchi, et. al, "Dynamic modeling of genetic networks using genetic algorithm and s-system", Bioinformatics, 19(5), pp.643-650, 2003. (Pubitemid 36417059)
    • (2003) Bioinformatics , vol.19 , Issue.5 , pp. 643-650
    • Kikuchi, S.1    Tominaga, D.2    Arita, M.3    Takahashi, K.4    Tomita, M.5
  • 8
    • 16344364990 scopus 로고    scopus 로고
    • Inference of S-system models of genetic networks from noisy time-series data
    • DOI 10.1273/cbij.4.1
    • S. Kimura, et. al, "Inference of S-system models of genetic networks from noisy time-series data", Chem-Bio Informatics Journal, 4(1), pp.1-14, 2004. (Pubitemid 40632068)
    • (2004) Chem-Bio Informatics Journal , vol.4 , Issue.1 , pp. 1-14
    • Kimura, S.1    Hatakeyama, M.2    Konagaya, A.3
  • 9
    • 4344592548 scopus 로고    scopus 로고
    • Neural-network-based parameter estimation in s-system models of biological networks
    • J. Almeida and E. Voit, "Neural-network-based parameter estimation in s-system models of biological networks", Genome Informatics, vol.14, pp.114-123, 2003.
    • (2003) Genome Informatics , vol.14 , pp. 114-123
    • Almeida, J.1    Voit, E.2
  • 11
    • 77953953099 scopus 로고    scopus 로고
    • Downhill simplex methods for optimizing simulated annealing are effective
    • P. Bangert, "Downhill Simplex Methods for Optimizing Simulated Annealing are Effective", Proceedings of ALGORITMY, pp.341-347, 2005.
    • (2005) Proceedings of ALGORITMY , pp. 341-347
    • Bangert, P.1
  • 12
    • 84870580329 scopus 로고
    • C 2nd. Ed, Cambridge University Press
    • W. Press, et. al, Numerical Recipes in C, 2nd. Ed, Cambridge University Press, 1992.
    • (1992) Numerical Recipes
    • Press, W.1
  • 15
    • 0034729586 scopus 로고    scopus 로고
    • A fuzzy logic approach to analyzing gene expression data
    • P. Woolf and Y. Wang, "A fuzzy logic approach to analyzing gene expression data", Physiol. Genomics, 3:9-15, 2000.
    • (2000) Physiol. Genomics , vol.3 , pp. 9-15
    • Woolf, P.1    Wang, Y.2
  • 16
    • 0025999808 scopus 로고
    • 1 by HAP1 and HAP2/3/4
    • J. Schneider and L. Guarente, "Regulation of the Yeast CYTI Gene Encoding Cytochrome cl by HAP1 and HAP2/3/4", Molecular and Cellular Biology, 11(10): 4934-4942, 1991. (Pubitemid 21895254)
    • (1991) Molecular and Cellular Biology , vol.11 , Issue.10 , pp. 4934-4942
    • Schneider, J.C.1    Guarente, L.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.