Understanding biological functions through molecular networks - PubMed (original) (raw)
Review
Understanding biological functions through molecular networks
Jing-Dong Jackie Han. Cell Res. 2008 Feb.
Abstract
The completion of genome sequences and subsequent high-throughput mapping of molecular networks have allowed us to study biology from the network perspective. Experimental, statistical and mathematical modeling approaches have been employed to study the structure, function and dynamics of molecular networks, and begin to reveal important links of various network properties to the functions of the biological systems. In agreement with these functional links, evolutionary selection of a network is apparently based on the function, rather than directly on the structure of the network. Dynamic modularity is one of the prominent features of molecular networks. Taking advantage of such a feature may simplify network-based biological studies through construction of process-specific modular networks and provide functional and mechanistic insights linking genotypic variations to complex traits or diseases, which is likely to be a key approach in the next wave of understanding complex human diseases. With the development of ready-to-use network analysis and modeling tools the networks approaches will be infused into everyday biological research in the near future.
Similar articles
- Genetic networks for the functional study of genomes.
Pisabarro AG, Pérez G, Lavín JL, Ramírez L. Pisabarro AG, et al. Brief Funct Genomic Proteomic. 2008 Jul;7(4):249-63. doi: 10.1093/bfgp/eln026. Epub 2008 Jun 25. Brief Funct Genomic Proteomic. 2008. PMID: 18579617 - Modeling genetic networks and their evolution: a complex dynamical systems perspective.
Bornholdt S. Bornholdt S. Biol Chem. 2001 Sep;382(9):1289-99. doi: 10.1515/BC.2001.161. Biol Chem. 2001. PMID: 11688712 Review. - Towards more biological mutation operators in gene regulation studies.
Watson J, Geard N, Wiles J. Watson J, et al. Biosystems. 2004 Aug-Oct;76(1-3):239-48. doi: 10.1016/j.biosystems.2004.05.016. Biosystems. 2004. PMID: 15351147 - Nonlinear regulation enhances the phenotypic expression of trans-acting genetic polymorphisms.
Gjuvsland AB, Hayes BJ, Meuwissen TH, Plahte E, Omholt SW. Gjuvsland AB, et al. BMC Syst Biol. 2007 Jul 25;1:32. doi: 10.1186/1752-0509-1-32. BMC Syst Biol. 2007. PMID: 17651484 Free PMC article. - Functional genomics and the study of development, variation and evolution.
White KP. White KP. Nat Rev Genet. 2001 Jul;2(7):528-37. doi: 10.1038/35080565. Nat Rev Genet. 2001. PMID: 11433359 Review.
Cited by
- Harnessing the complexity of gene expression data from cancer: from single gene to structural pathway methods.
Emmert-Streib F, Tripathi S, de Matos Simoes R. Emmert-Streib F, et al. Biol Direct. 2012 Dec 10;7:44. doi: 10.1186/1745-6150-7-44. Biol Direct. 2012. PMID: 23227854 Free PMC article. Review. - Systems medicine: the future of medical genomics and healthcare.
Auffray C, Chen Z, Hood L. Auffray C, et al. Genome Med. 2009 Jan 20;1(1):2. doi: 10.1186/gm2. Genome Med. 2009. PMID: 19348689 Free PMC article. - Robust Physiological Metrics From Sparsely Sampled Networks.
Cohen AA, Leblanc S, Roucou X. Cohen AA, et al. Front Physiol. 2021 Feb 10;12:624097. doi: 10.3389/fphys.2021.624097. eCollection 2021. Front Physiol. 2021. PMID: 33643068 Free PMC article. Review. - A biochemical network modeling of a whole-cell.
Burke PEP, Campos CBL, Costa LDF, Quiles MG. Burke PEP, et al. Sci Rep. 2020 Aug 6;10(1):13303. doi: 10.1038/s41598-020-70145-4. Sci Rep. 2020. PMID: 32764598 Free PMC article. - The implications of relationships between human diseases and metabolic subpathways.
Li X, Li C, Shang D, Li J, Han J, Miao Y, Wang Y, Wang Q, Li W, Wu C, Zhang Y, Li X, Yao Q. Li X, et al. PLoS One. 2011;6(6):e21131. doi: 10.1371/journal.pone.0021131. Epub 2011 Jun 17. PLoS One. 2011. PMID: 21695054 Free PMC article.
Publication types
MeSH terms
LinkOut - more resources
Full Text Sources
Other Literature Sources