Unraveling liver complexity from molecular to organ level: challenges and perspectives
Biological responses are determined by information processing at multiple and highly interconnected scales. Within a tissue the individual cells respond to extracellular stimuli by regulating intracellular signaling pathways that in turn determine cell fate decisions and influence the behavior of ne...
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| Main Authors: | , , , , |
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| Format: | Article (Journal) |
| Language: | English |
| Published: |
2015
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| In: |
Progress in biophysics & molecular biology
Year: 2014, Volume: 117, Issue: 1, Pages: 78-86 |
| ISSN: | 1873-1732 |
| DOI: | 10.1016/j.pbiomolbio.2014.11.005 |
| Online Access: | Resolving-System, lizenzpflichtig, Volltext: https://doi.org/10.1016/j.pbiomolbio.2014.11.005 Verlag, lizenzpflichtig, Volltext: http://www.sciencedirect.com/science/article/pii/S0079610714001849 
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| Author Notes: | L.A. D'Alessandro, S. Hoehme, A. Henney, D. Drasdo, U. Klingmüller |
| Summary: | Biological responses are determined by information processing at multiple and highly interconnected scales. Within a tissue the individual cells respond to extracellular stimuli by regulating intracellular signaling pathways that in turn determine cell fate decisions and influence the behavior of neighboring cells. As a consequence the cellular responses critically impact tissue composition and architecture. Understanding the regulation of these mechanisms at different scales is key to unravel the emergent properties of biological systems. In this perspective, a multidisciplinary approach combining experimental data with mathematical modeling is introduced. We report the approach applied within the Virtual Liver Network to analyze processes that regulate liver functions from single cell responses to the organ level using a number of examples. By facilitating interdisciplinary collaborations, the Virtual Liver Network studies liver regeneration and inflammatory processes as well as liver metabolic functions at multiple scales, and thus provides a suitable example to identify challenges and point out potential future application of multi-scale systems biology. |
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| Item Description: | Available online 26 November 2014 Gesehen am 14.10.2020 |
| Physical Description: | Online Resource |
| ISSN: | 1873-1732 |
| DOI: | 10.1016/j.pbiomolbio.2014.11.005 |