Detailed kinetic models at the network reaction level are usually constructed using enzymatic mechanistic rate equations and the associated kinetic parameters. However, during the cellular life cycle thousands of different reactions occur, which makes it very difficult to build a detailed large-scale ldnetic model. In this work, we provide a critical overview of specific limitations found during the reconstruct...
The recent progress in the high-throughput experimental technologies allows the reconstruction of many biological networks and to evaluate changes in proteins, genes and metabolites levels in different conditions. On the other hand, computational models, when complemented with regulatory information, can be used to predict the phenotype of an organism under different genetic and environmental conditions. These ...
Systems biology provides new approaches for metabolic engineering through the development of models and methods for simulation and optimization of microbial metabolism. Here we explore the relationship between two modeling frameworks in common use namely, dynamic models with kinetic rate laws and constraint-based flux models. We compare and analyze dynamic and constraint-based formulations of the same model of ...
Systems Biology has taken advantage of computational tools and high-throughput experimental data to model several biological processes. These include signaling, gene regulatory, and metabolic networks. However, most of these models are specific to each kind of network. Their interconnection demands a whole-cell modeling framework for a complete understanding of cellular systems. We describe the features require...
The construction of dynamic metabolic models at reaction network level requires the use of mechanistic enzymatic rate equations that comprise a large number of parameters. The lack of knowledge on these equations and the difficulty in the experimental identification of their associated parameters, represent nowadays the limiting factor in the construction of such models. In this study, we compare four alternati...
The different modeling approaches in Systems Biology create models with different levels of detail. The transformation techniques in Petri net theory can provide a solid framework for zooming between these different levels of abstraction and refinement. This work presents a Petri net based approach to Metabolic Engineering that implements model reduction methods to reduce the complexity of large-scale metabolic...
Integration of different kinds of biological networks, is within the holistic approach of Systems Biology. However, looking at metabolic networks only, one already finds a separation between dynamic [2] and steady-state [3] models of metabolism. This work reviews the differences between both modeling approaches and explores the gap between them. Common properties of both kind of models are studied in detail, us...
So far, few large scale kinetic models of metabolic networks have been successfully constructed. The main reasons for this are not only the associated mathematical complexity, but also the large number of unknown kinetic parameters required in the rate equations to define the system. In contrast to kinetic models, the constraint-based modelling approach bypasses these difficulties by using basically only stoich...
Detailed dynamic kinetic models at the network reaction level are traditionally constructed using mechanistic enzymatic rate equations and a large number of kinetic parameters have to be determined under nonphysiological conditions in vitro. However, the validity of these parameters under in vivo conditions is doubtful and the rates equations are usually highly complex. Therefore, one of the major obstacles in ...
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