메뉴 건너뛰기




Volumn 6, Issue 2, 2008, Pages 111-120

Applying Intelligent Computing Techniques to Modeling Biological Networks from Expression Data

Author keywords

expression data; genetic programming; recurrent neural network; reverse engineering; system modeling

Indexed keywords

ALGORITHM; ARTICLE; COMPUTER ANALYSIS; INFORMATION PROCESSING; SYSTEMS BIOLOGY;

EID: 54849411117     PISSN: 16720229     EISSN: None     Source Type: Journal    
DOI: 10.1016/S1672-0229(08)60026-1     Document Type: Article
Times cited : (10)

References (22)
  • 1
    • 20844447572 scopus 로고    scopus 로고
    • Sigmoid: a software infrastructure for pathway bioinformatics and systems biology
    • Cheng J., et al. Sigmoid: a software infrastructure for pathway bioinformatics and systems biology. IEEE Intell. Syst. 20 (2005) 68-75
    • (2005) IEEE Intell. Syst. , vol.20 , pp. 68-75
    • Cheng, J.1
  • 2
    • 0003065454 scopus 로고    scopus 로고
    • Systems biology: toward system-level understanding of biological systems
    • Kitano H. (Ed), MIT Press, Cambridage, USA
    • Kitano H. Systems biology: toward system-level understanding of biological systems. In: Kitano H. (Ed). Foundations of Systems Biology (2001), MIT Press, Cambridage, USA 1-36
    • (2001) Foundations of Systems Biology , pp. 1-36
    • Kitano, H.1
  • 3
    • 0036500834 scopus 로고    scopus 로고
    • Reverse engineering of biological complexity
    • Csete M.E., and Doyle J.C. Reverse engineering of biological complexity. Science 295 (2002) 1664-1669
    • (2002) Science , vol.295 , pp. 1664-1669
    • Csete, M.E.1    Doyle, J.C.2
  • 4
    • 0345824737 scopus 로고    scopus 로고
    • Network component analysis: reconstruction of regulatory signals in biological systems
    • Liao J.C., et al. Network component analysis: reconstruction of regulatory signals in biological systems. Proc. Natl. Acad. Sci. USA 100 (2003) 15522-15527
    • (2003) Proc. Natl. Acad. Sci. USA , vol.100 , pp. 15522-15527
    • Liao, J.C.1
  • 5
    • 0036207347 scopus 로고    scopus 로고
    • Modeling and simulation of genetic regulatory systems: a literature review
    • de Jong H. Modeling and simulation of genetic regulatory systems: a literature review. J. Comput. Biol. 9 (2002) 67-103
    • (2002) J. Comput. Biol. , vol.9 , pp. 67-103
    • de Jong, H.1
  • 7
    • 0004238344 scopus 로고    scopus 로고
    • Oxford University Press, Oxford, UK
    • Lewin B. Genes VII (1999), Oxford University Press, Oxford, UK
    • (1999) Genes VII
    • Lewin, B.1
  • 9
    • 15744367955 scopus 로고    scopus 로고
    • Overview of computational methods for the inference of gene regulatory networks
    • Styczynski M.P., and Stephanopoulos G. Overview of computational methods for the inference of gene regulatory networks. Comput. Chem. Eng. 29 (2005) 519-534
    • (2005) Comput. Chem. Eng. , vol.29 , pp. 519-534
    • Styczynski, M.P.1    Stephanopoulos, G.2
  • 10
    • 0033736476 scopus 로고    scopus 로고
    • Genetic network inference: from co-expression clustering to reverse engineering
    • D'haeseleer P., et al. Genetic network inference: from co-expression clustering to reverse engineering. Bioinformatics 16 (2000) 707-726
    • (2000) Bioinformatics , vol.16 , pp. 707-726
    • D'haeseleer, P.1
  • 11
    • 0036522639 scopus 로고    scopus 로고
    • Bayesian methods for elucidating genetic regulatory networks
    • Hartemink A.J., et al. Bayesian methods for elucidating genetic regulatory networks. IEEE Intell. Syst. 17 (2002) 37-43
    • (2002) IEEE Intell. Syst. , vol.17 , pp. 37-43
    • Hartemink, A.J.1
  • 12
    • 0344844807 scopus 로고    scopus 로고
    • Modeling regulatory pathways in E. coli from time series expression profiles
    • Ong I.M., et al. Modeling regulatory pathways in E. coli from time series expression profiles. Bioin-formatics 18 (2002) S241-S248
    • (2002) Bioin-formatics , vol.18
    • Ong, I.M.1
  • 13
    • 0037461033 scopus 로고    scopus 로고
    • Dynamic modeling of genetic networks using genetic algorithm and S-system
    • Kikuchi S., et al. Dynamic modeling of genetic networks using genetic algorithm and S-system. Bioinformatics 19 (2003) 643-650
    • (2003) Bioinformatics , vol.19 , pp. 643-650
    • Kikuchi, S.1
  • 14
    • 20144387371 scopus 로고    scopus 로고
    • Inference of S-system models of genetic networks using a cooperative coevolutionary algorithm
    • Kimura S., et al. Inference of S-system models of genetic networks using a cooperative coevolutionary algorithm. Bioinformatics 21 (2005) 1154-1163
    • (2005) Bioinformatics , vol.21 , pp. 1154-1163
    • Kimura, S.1
  • 15
    • 11444269718 scopus 로고    scopus 로고
    • A recursive network approach can identify constitutive regulatory circuits in gene expression data
    • Blasi M.F., et al. A recursive network approach can identify constitutive regulatory circuits in gene expression data. Physica A 348 (2005) 349-370
    • (2005) Physica A , vol.348 , pp. 349-370
    • Blasi, M.F.1
  • 16
    • 0035082045 scopus 로고    scopus 로고
    • Neural network model of gene expression
    • Vohradsky J. Neural network model of gene expression. FASEB J. 15 (2001) 846-854
    • (2001) FASEB J. , vol.15 , pp. 846-854
    • Vohradsky, J.1
  • 17
    • 0033555859 scopus 로고    scopus 로고
    • Emergent properties of networks of biological signaling pathways
    • Bhalla U.S., and Lyengar R. Emergent properties of networks of biological signaling pathways. Science 283 (1999) 381-397
    • (1999) Science , vol.283 , pp. 381-397
    • Bhalla, U.S.1    Lyengar, R.2
  • 20
    • 0025503558 scopus 로고
    • Backpropagation through time: what it does and how to do it
    • Werbos P.J. Backpropagation through time: what it does and how to do it. Proc. IEEE 78 (1990) 1550-1560
    • (1990) Proc. IEEE , vol.78 , pp. 1550-1560
    • Werbos, P.J.1
  • 21
    • 0024137490 scopus 로고
    • Increased rates of convergence through learning rate adaptation
    • Jacobs R.A. Increased rates of convergence through learning rate adaptation. Neural Networks 1 (1988) 295-307
    • (1988) Neural Networks , vol.1 , pp. 295-307
    • Jacobs, R.A.1
  • 22
    • 0025482241 scopus 로고
    • The wavelet transform, time-frequency localization and signal analysis
    • Daubechies I. The wavelet transform, time-frequency localization and signal analysis. IEEE Trans. Inf. Theory 36 (1990) 961-1005
    • (1990) IEEE Trans. Inf. Theory , vol.36 , pp. 961-1005
    • Daubechies, I.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.