Building a dynamic model of a complete biological cell is one of the great challenges of the 21st century. While this objective could appear unrealistic until recently, considerable improvements in high-throughput data collection techniques, computational performance, data integration, and modeling approaches now allow us to consider it within reach in the near future. In this chapter, we review recent developments that pave the way toward the construction of genome-scale dynamic models. We first describe methodologies for the integration of heterogeneous "omics" datasets, which enable the interpretation of cellular activity at the genome scale and in fluctuating conditions, providing the necessary input to models. We subsequently discuss principles of such models and describe a series of approaches that open perspectives toward the construction of genome-scale dynamic models. © 2011 Humana Press.
|Title of host publication||Methods in Molecular Biology|Methods Mol. Biol.|
|Subtitle of host publication||Methods in Molecular Biology 759|
|Number of pages||16|
|Publication status||Published - 2011|
- data integration
- dynamic model
- Systems biology