소개글
최근 시스템 생물학의 진보는 연구자들로 하여금 ‘few-reactions-based`에서 `whole-cell-based` 혹은 `whole-organ-based` 모델로의 전환을 요구하고 있다. 시스템 생물학 분야에서 날로 증가하고 있는 막대한 양의 정보와 실험적 데이터에서 새로운 지식을 도출하기 위해서는 복잡한 생물학적 시스템의 전산 모델링 및 모사가 필수적이다. 생명체와 같은 복잡한 시스템을 이해하고 응용하기 위해서는 각각의 구성요소의 개별적 기능뿐 아니라 그들의 상호작용에 대한 이해가 필요한데 전산 모델은 전체 시스템에 대한 수식적 모사를 가능케 함으로서 동적 거동을 예측할 수 있게 한다. 이러한 노력의 일환으로 전산 모델 및 모사에 기반을 둔 정량적 분석을 위한 다양한 모델링 프로젝트가 이루어지고 있다. 본 논문에서는 Virtual Cell, E-Cell, MetaFluxNet 그리고 WebCell을 사례연구와 함께 소개하고 현 단계에서의 문제점과 향후 전망에 대해 논하고자 한다.목차
Ⅰ IntroductionⅡ Main discourse
1. Quantitative Cell Biology: Systemic and integrative strategy for developing improved strains
2. Virtual Cell
1) A look at the Virtual Cell System
2) A case study for quantitative cell biology with the Virtual Cell: Calcium dynamics in a neuronal cell
3. E-CELL
1) Program Overview
2) A case study for quantitative cell biology with the E-Cell: E. coli osmoregulatory switch
4. MetaFluxNet
1) Program overview
2) A case study for MFA with MetaFluxNet: Mannheimia succiniciproducens
5. WebCell
1) System overview
2) Unique feature
Ⅲ Conclusion
1. Future challenges
2. Concluding Remarks
Ⅳ References
본문내용
(1) Virtual Cell is a computational environment designed for cell biologists to facilitate the construction of models and the generation of predictive simulations from them, providing a formal framework for modeling biochemical, electrophysiological, and transport phenomena while considering the subcellular localization of the molecules that take part in them.[5] (2) E-CELL is a computational system for constructing whole cell models and allows the user to perform multi-algorithm calculations by incorporating both deterministic[2-3](which give more accurate pictures of metabolic and regulatory behavior but currently limited by the lack of kinetic data) and stochastic models(based on the steady state of a system by excluding the time-dependent characteristics of variables[6]), which are also provided in CellWare.[7] (3) MetaFluxNet is a program package for managing information on the metabolic reaction network[8] and for quantitatively analyzing metabolic fluxes in an interactive and customized way, allowing users to interpret and examine metabolic behavior in response to genetic and/or environmental modifications.[9-12] (4) WebCell, which is complementary to the MetaFluxNet, is a web-based environment for managing quantitative and qualitative information on cellular networks and for interactively exploring their steady-state and dynamic behaviors in response to systemic perturbations. (5) GEPASI has been one of the most widely used programs for dynamic simulation and metabolic control analysis.[11] (6) Jarnac/Scamp allows dynamic simulation, steady-state analysis and metabolic control analysis, and provides an interface to the Systems Biology Workbench(SBW). (7) DBSolve can handle both ordinary differential equations and non-linear algebraic equations with improved numerical solution algorithms. (6) BioSpice is a more recently developed modelling framework for metabolic as well as genetic networks with particular strengths in analyzing prokaryotic genetic circuits. (7) StochSim permits the user to follow individual molecules in a regulatory pathway through stochastic simulations. (8) MCell is another stochastic simulator that is designed for the study of subcellular processes such as synaptic transmission and is the only system other than Virtual Cell that can explicitly accommodate structural information. (9) CellWare offers a multi-algorithmic environment for modeling and simulating both deterministic and stochastic events in the cell. (10) A-Cell is a tool for constructing comprehensive models for complex and complicated biochemical reactions with commonly used graphical expressions by importing previously constructed models and combining them.[13]참고 자료
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