
How cells utilize intracellular spatial features to optimize their signaling characteristics is still not clearly understood. The physical distance between the cell‐surface receptor and the gene expression machinery, fast reactions, and slow protein diffusion coefficients are some of the properties that contribute to their intricacy. This article reviews computational frameworks that can help biologists to elucidate the implications of space in signaling pathways. We argue that intracellular macromolecular crowding is an important modeling issue, and describe how recent simulation methods can reproduce this phenomenon in either implicit, semi‐explicit or fully explicit representation.
570, 1.1 Normal biological development and functioning, Excluded volume effect, Intracellular Space, 3101 Biochemistry and Cell Biology, Molecular crowding, Theoretical, Models, Animals, Humans, Computer Simulation, anzsrc-for: 31 Biological Sciences, anzsrc-for: 0304 Medicinal and Biomolecular Chemistry, Intracellular space, Stochastic Processes, Signaling pathway, anzsrc-for: 3101 Biochemistry and Cell Biology, Computational Biology, Models, Theoretical, 540, anzsrc-for: 0601 Biochemistry and Cell Biology, anzsrc-for: 0603 Evolutionary Biology, Systems biology, Simulation, Algorithms, 31 Biological Sciences, Signal Transduction
570, 1.1 Normal biological development and functioning, Excluded volume effect, Intracellular Space, 3101 Biochemistry and Cell Biology, Molecular crowding, Theoretical, Models, Animals, Humans, Computer Simulation, anzsrc-for: 31 Biological Sciences, anzsrc-for: 0304 Medicinal and Biomolecular Chemistry, Intracellular space, Stochastic Processes, Signaling pathway, anzsrc-for: 3101 Biochemistry and Cell Biology, Computational Biology, Models, Theoretical, 540, anzsrc-for: 0601 Biochemistry and Cell Biology, anzsrc-for: 0603 Evolutionary Biology, Systems biology, Simulation, Algorithms, 31 Biological Sciences, Signal Transduction
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