Modeling Cellular Networks
نویسندگان
چکیده
Systems-level understanding of cellular dynamics is important for identifying biological principles and may serve as a critical foundation for developing therapeutic strategies. To date, numerous developments of therapeutics have been based on identification and comprehensive analysis of cellular dynamics, especially in the involved pathways. In cancer therapy, for instance, many researchers have focused on oncogenic pathways such as the Rb pathway, whose in-depth understanding of the pathway dynamics promises effective therapeutics [1–7]. The effectiveness of this approach in the development of cancer therapeutics has been illustrated in in vivo pre-clinical tests of the engineered adenovirus ONYX-015 and ONYX-411. These adenoviruses, engineered to target mutations in the Rb or p53 pathway for killing, have demonstrated high selectivity and efficiency in viral replication in tumor cells for cell killing [8, 9]. However, clinical application of these methods is hindered by lack of ability to precisely predict and regulate cellular responses. This ability is essential in minimizing complications and side effects. Especially, a large amount of biology data on these pathways generated by rapid advancements in biotechnologies and molecular biology renders integrated understanding of the pathway dynamics impossible by intuition alone. Therefore, a more systematic approach allowing incorporation of the multitude of information is necessary to improve prediction and regulation of cellular responses. To this end, mathematical modeling is becoming increasingly indispensable for basic and applied biological research. Essentially, a mathematical model is a systematic representation of biological systems, whose analysis can confer quantitative predicting power. In recent years, advanced computing power combined with improved numerical methods have made it possible to simulate and analyze dynamics of complex cellular networks [10–19]. Mathematical modeling is useful in a number of ways. One of the common applications of mathematical modeling is to analyze cellular networks systematically. For example, although the mitogen-activated protein kinase (MAPK) was known to control multiple cellular responses such as cell growth, survival, or differentiation, the molecular mechanisms for these divergent behaviors were not fully elucidated.
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تاریخ انتشار 2006