Scale-free networks in cell biology
- PMID: 16254242
- DOI: 10.1242/jcs.02714
Scale-free networks in cell biology
Abstract
A cell's behavior is a consequence of the complex interactions between its numerous constituents, such as DNA, RNA, proteins and small molecules. Cells use signaling pathways and regulatory mechanisms to coordinate multiple processes, allowing them to respond to and adapt to an ever-changing environment. The large number of components, the degree of interconnectivity and the complex control of cellular networks are becoming evident in the integrated genomic and proteomic analyses that are emerging. It is increasingly recognized that the understanding of properties that arise from whole-cell function require integrated, theoretical descriptions of the relationships between different cellular components. Recent theoretical advances allow us to describe cellular network structure with graph concepts and have revealed organizational features shared with numerous non-biological networks. We now have the opportunity to describe quantitatively a network of hundreds or thousands of interacting components. Moreover, the observed topologies of cellular networks give us clues about their evolution and how their organization influences their function and dynamic responses.
Similar articles
-
Biological impacts and context of network theory.J Exp Biol. 2007 May;210(Pt 9):1548-58. doi: 10.1242/jeb.003731. J Exp Biol. 2007. PMID: 17449819 Review.
-
ProtNet: a tool for stochastic simulations of protein interaction networks dynamics.BMC Bioinformatics. 2007 Mar 8;8 Suppl 1(Suppl 1):S4. doi: 10.1186/1471-2105-8-S1-S4. BMC Bioinformatics. 2007. PMID: 17430571 Free PMC article.
-
Signal transduction networks: topology, response and biochemical processes.J Theor Biol. 2006 Jan 21;238(2):416-25. doi: 10.1016/j.jtbi.2005.05.030. Epub 2005 Jul 20. J Theor Biol. 2006. PMID: 16045939
-
Dynamical and integrative cell signaling: challenges for the new biology.Biotechnol Bioeng. 2003 Dec 30;84(7):773-82. doi: 10.1002/bit.10854. Biotechnol Bioeng. 2003. PMID: 14708118 Review.
-
Getting connected: analysis and principles of biological networks.Genes Dev. 2007 May 1;21(9):1010-24. doi: 10.1101/gad.1528707. Genes Dev. 2007. PMID: 17473168 Review.
Cited by
-
Quantitative omnigenic model discovers interpretable genome-wide associations.Proc Natl Acad Sci U S A. 2024 Oct 29;121(44):e2402340121. doi: 10.1073/pnas.2402340121. Epub 2024 Oct 23. Proc Natl Acad Sci U S A. 2024. PMID: 39441639
-
GeneSPIDER2: large scale GRN simulation and benchmarking with perturbed single-cell data.NAR Genom Bioinform. 2024 Sep 18;6(3):lqae121. doi: 10.1093/nargab/lqae121. eCollection 2024 Sep. NAR Genom Bioinform. 2024. PMID: 39296931 Free PMC article.
-
Inference of single-cell network using mutual information for scRNA-seq data analysis.BMC Bioinformatics. 2024 Sep 5;25(Suppl 2):292. doi: 10.1186/s12859-024-05895-3. BMC Bioinformatics. 2024. PMID: 39237886 Free PMC article.
-
A comparative analysis of ENCODE and Cistrome in the context of TF binding signal.BMC Genomics. 2024 Aug 30;25(Suppl 3):817. doi: 10.1186/s12864-024-10668-6. BMC Genomics. 2024. PMID: 39210256 Free PMC article.
-
Network analysis of three-dimensional hard-soft tissue relationships in the lower 1/3 of the face: skeletal Class I-normodivergent malocclusion versus Class II-hyperdivergent malocclusion.BMC Oral Health. 2024 Aug 24;24(1):996. doi: 10.1186/s12903-024-04752-2. BMC Oral Health. 2024. PMID: 39182104 Free PMC article.
Publication types
MeSH terms
LinkOut - more resources
Full Text Sources
Other Literature Sources
