High-throughput technologies now enable the study of cell biology at a systems level — from subcellular systems such as signalling networks, multiprotein complexes and organelles, to cells, tissues and even entire organisms. The diverse systems can be modelled through a combination of high-throughput experimental data and mathematical and computational approaches. This special Focus issue of Nature Reviews Molecular Cell Biology illustrates several cellular systems and describes the different approaches that can be used to model them. The articles of this Focus are freely available for a period of three months.
Foreword
Computational cellular dynamics: a network�physics integral
Hiroaki Kitano
doi:10.1038/nrm1904
Nature Reviews Molecular Cell Biology 7, 163
Research highlights
Proteomics: The yeast proteome: say cheese!
Sharon Ahmad
doi:10.1038/nrm1902
Nature Reviews Molecular Cell Biology 7, 156
In the news
MIRIAM, for fine modelling
Ekat Kritikou
doi:10.1038/nrm1906
Nature Reviews Molecular Cell Biology 7, 158
Reviews
Cell-signalling dynamics in time and space
Boris N. Kholodenko
doi:10.1038/nrm1838
Nature Reviews Molecular Cell Biology 7, p165
Spatial and temporal dynamics of signalling networks control the specificity of cellular responses to receptor stimulation. Computational models now provide insights into the mechanisms that are responsible for signal amplification, as well as the timing, amplitude, duration and spatial distribution of signalling responses.
Building mammalian signalling pathways with RNAi screens
Jason Moffat and David M. Sabatini
doi:10.1038/nrm1860
Nature Reviews Molecular Cell Biology 7, p177
Recent advances in RNA interference (RNAi)-mediated gene-knockdown technologies have opened up the possibility of large-scale functional discovery in mammalian systems. RNAi screening could help us to delineate the architecture of signalling pathways much faster than by using traditional approaches.
Structural systems biology: modelling protein interactions
Patrick Aloy and Robert B. Russell
doi:10.1038/nrm1859
Nature Reviews Molecular Cell Biology 7, 117-129
The difficulties that are associated with the experimental determination of atomic structures for interacting proteins mean that predictive methods are needed for progress. Such structural details can be used to turn abstract system representations into models that more accurately reflect biological reality.
The model organism as a system: integrating 'omics' data sets
Andrew R. Joyce and Bernhard �. Palsson
doi:10.1038/nrm1857
Nature Reviews Molecular Cell Biology 7, p198
Many genome-scale, or 'omics', data sets are becoming available for various model organisms. Although each of these data types is valuable on its own, further insights into whole systems can be gained through the integration of omics data sets.
Capturing complex 3D tissue physiology in vitro
Linda G. Griffith and Melody A. Swartz
doi:10.1038/nrm1858
Nature Reviews Molecular Cell Biology 7, p211
Tissue engineering has opened up the possibility of studying physiological and pathophysiological processes in vitro. The foundation of this technology is a set of design principles for building three-dimensional tissues that are based on the quantitative analyses of cell and tissue behaviour.
Perspectives
Innovation: A visual approach to proteomics
Stephan Nickell, Christine Kofler, Andrew P. Leis and Wolfgang Baumeister
doi:10.1038/nrm1861
Nature Reviews Molecular Cell Biology 7, p225
Cryo-electron tomography is an emerging imaging technique that will allow us to map molecular landscapes inside cells. This 'visual proteomics' will complement and extend mass-spectrometry-based inventories, and will provide a quantitative description of the macromolecular interactions that underlie cellular functions.
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