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Quantitative Analysis of Biological Models under the Internet Environment

인터넷 환경을 통한 생물학적 모델의 정량적 분석

  • 윤좌문 (한국과학기술원 생명화학공학과) ;
  • 이동엽 (싱가포르 국립대학교 생물공정기술연구소) ;
  • 조아연 (한국과학기술원 생명화학공학과) ;
  • 이상엽 (한국과학기술원 생명화학공학과) ;
  • 박선원 (한국과학기술원 생명화학공학과)
  • Published : 2005.10.01

Abstract

The computational modeling and simulation of complex biological systems are indispensable for new knowledge extraction from huge experimental data and ever growing vast amount of information in systems biology. Moreover, gathering and sharing of the existing information and newly-generated knowledge can speed up this research process. In this regard, several modeling projects have been undertaken for quantitatively analyzing the biological systems via the internet. They include Virtual Cell, JWS and OBIYagns. We also develop an integrated web-based environment, which facilitate investigation of dynamic behavior of cellular systems.

Keywords

References

  1. D.-Y. Lee, C. Yun, B. K. Hou, S. Park and S. Y. Lee, 'WebCell: a web-based environment for kinetic modeling and dynamic simulation of cellula networks,' submitted
  2. S. Y. Lee, D.-Y. Lee and T. Y. Kim, 'Systems biotechnology for strain improvement,' Trends in Biotechnology, vol. 23, pp. 349-358, 2005 https://doi.org/10.1016/j.tibtech.2005.05.003
  3. I. Goryanin, T. C. Hodgman and E. Selkov, 'Mathematical simulation and analysis of cellular metabolism and regulation,' Bioinformatics, vol. 15, pp. 749-758, 1999 https://doi.org/10.1093/bioinformatics/15.9.749
  4. U. M. Ascher and L. R. Petzold, 'Computer methods for ordinary differential equations and differential-algebraic equations,' SIAM, 1998
  5. T. C. Meng, S. Somani and P. Dhar, 'Modelling and simulation of biological systems with stochasticity,' In Silico Biology, vol. 4,0024,2004
  6. N. Novere and T. S. Shimizu, 'Stochsim: Modeling of Stochastic Biomolecular Processes,' Bioinformatics, vol. 6, pp. 575-576, 2001 https://doi.org/10.1093/bioinformatics/17.6.575
  7. T. R. Kiehl, R. M. Mattheyses and M. K. Simmons, 'Hybrid simulation of cellular behavior,' Bioinformatics, vol. 20, pp. 316-322, 2004 https://doi.org/10.1093/bioinformatics/btg409
  8. D.-Y. Lee, H. Yun, S. Park and S. Y. Lee, 'MetaFluxNet: the management of metabolic reaction information and quantitative metabolic flux analysis,' Bioinformatics, vol. 19, pp. 2144-2146, 2003 https://doi.org/10.1093/bioinformatics/btg271
  9. M. Tomita, K. Hashimoto, K. Takahashi, T. S. Shimizu, Y. Matsuzaki, F. Miyoshi et al., 'E-CELL: software environment for whole-cell simulation,' Bioinformatics, vol. 15, pp. 72-84, 1999 https://doi.org/10.1093/bioinformatics/15.1.72
  10. P. Mendes, 'Biochemistry by numbers: simulation of biochemical pathways with Gepasi3,' Trends Biochem. Sci., vol. 22, pp. 361-363, 1997 https://doi.org/10.1016/S0968-0004(97)01103-1
  11. L. M. Loew and J. C. Schaff, 'The Virtual Cell: A Software Environment for Computational Cell Biology,' Trends Biotechnol., vol. 19, pp. 401-406, 2001 https://doi.org/10.1016/S0167-7799(01)01740-1
  12. B. G. Olivier and J. L. Snoep, 'Web-based kinetic modeling using JWS Online,' Bioinformatics, vol. 20, pp. 2143-2144, 2004 https://doi.org/10.1093/bioinformatics/bth200
  13. M. Hucka, A. Finney, H. M. Sauro, H. Bolouri, J. C. Doyle and H. Kitano, 'The systems biology markup language (SBML): a medium for representation and exchange of biochemical network models,' Bioinformatics, vol. 19, pp. 524-531, 2002 https://doi.org/10.1093/bioinformatics/btg015
  14. M. Hucka, A. Finney, B. J. Bornstein et al., 'Evolving a lingua franca and associated software infrastructure for computational systems biology: the Systems Biology Markup Language (SBML) project,' Systems Biology, vol. 1, pp. 41-53, 2004 https://doi.org/10.1049/sb:20045008
  15. B. G. Oliver, J. M. Rohwer and J. S. Hofmeyr 'Modeling cellular systems with PySCeS,' Bioinformatics, vol. 21, pp. 560-561, 2005 https://doi.org/10.1093/bioinformatics/bti046
  16. S. Kimura, T. Kawasaki, M. Hatakeyarma, T. Naka, F. Konishi and A. Konagaya, 'OBIYagns: a grid-based biochemical simulator with a parameter estimator,' Bioinformatics, vol. 20, pp. 1646-1648, 2004 https://doi.org/10.1093/bioinformatics/bth122
  17. H. M. Sauro, B. Ingalls, 'Conservation analysis in biochemical networks: computational issues for software writers,' Biophys. Chem. J., vol. 109, pp. 1-15, 2004 https://doi.org/10.1016/j.bpc.2003.08.009
  18. D. A. Beard S. D. Liang and H. Qian, 'Energy balance for analysis of complex metabolic networks,' Biophys. J., vol. 83, pp. 79-86, 2002 https://doi.org/10.1016/S0006-3495(02)75150-3
  19. S. Okino and M. L. Mavrovouniotis, 'Simplification of mathematical models of chemical reaction systems,' Chemical Reviews, vol. 98, 1998
  20. M. Schauer, R. Heinrich, 'Quasi-steady-state approximation in the mathematical modeling of biochemical reaction networks,' Mathematical Biosciences, vol. 65, pp. 155-170, 1983 https://doi.org/10.1016/0025-5564(83)90058-5