Why network approach can promote a new way of thinking in biology

Frontiers in Genetics

Volumn 5, Issue APR, 2014, Pages

  Giuliani, Alessandro ^a   Filippi, Simonetta ^b   Bertolaso, Marta ^b  

^a ISTITUTO SUPERIORE DI SANITÀ   (Italy)

^b UNIVERSITY CAMPUS BIO MEDICO   (Italy)

Author keywords

Complex networks analysis; Graph theory; Mesoscopic descriptors; Middle out approaches; Systems biology

Indexed keywords

ARTICLE; CHEMISTRY; GENE EXPRESSION; GRAPH; INFORMATION PROCESSING; MATHEMATICAL ANALYSIS; MATHEMATICS; METABOLIC NETWORK; NETWORK ANALYSIS; SYSTEMS BIOLOGY; THEORY;

EID: 84898031551     PISSN: None     EISSN: 16648021     Source Type: Journal    
DOI: 10.3389/fgene.2014.00083     Document Type: Article

References (30)

1. Bender, A., and Glen, R. C. (2005). A discussion of measures of enrichment in virtual screening: comparing the information content of descriptors with increasing levels of sophistication. J. Chem. Inf. Model. 45, 1369-1375. doi: 10.1021/ci0500177
2. Blasi, M. F., Casorelli, I., Colosimo, A., Blasi, F. S., Bignami, M., and Giuliani, A. (2005). A recursive network can identify constitutive regulatory circuits in gene expression data. Physica A 348, 349-370. doi: 10.1016/j.physa.2004.09.005
3. Csermely, P., Agoston, V., and Pongor, S. (2005). The efficiency of multi-target drugs: the network approach might help drug design. Trends Phramacol. Sci. 26, 178-182. doi: 10.1016/j.tips.2005.02.007
4. de Abreu, N. M. M., Gutman, I., Robbiano, M., and So, W. (2010). Applications of a theorem by Ky Fan in the theory of graph energy. Linear Algebra Appl. 432, 2163-2169. doi: 10.1016/j.laa.2009.01.006
5. Dehmer, M., Mueller, L. A. J., and Emmert-Streib, F. (2013). Quantitative network measures as biomarkers for classifying prostate cancer disease states: a systems approach to diagnostic biomarkers. PLoS ONE 8:e77602. doi: 10.1371/journal.pone.0077602
6. Di Paola, L., De Ruvo, M., Paci, P., Santoni, D., and Giuliani, A. (2013). Protein contact networks: an emerging paradigm in chemistry. Chem. Rev. 113, 1598-1613. doi: 10.1021/cr3002356
7. Donner, R. V., Small, M., Donges, J. F., Marwan, N., Zou, Y., Xiang, R., et al. (2011). Recurrence-based time series analysis by means of complex network methods. Int. J. Bifurcat. Chaos 21, 1019-1046. doi: 10.1142/S0218127411029021
8. Eulero, L. (1741). Solutio problematis ad geometriam situs pertinentis. Comment. Acad. Scient. Petropol. 8, 128-140.
9. Giuliani, A. (2010). Collective motions and specific effectors: a statistical mechanics perspective on biological regulation. BMC Genomics 11(Suppl. 1):S2. doi: 10.1186/1471-2164-11-S1-S2
10. Gunthard, H. H., and Primas, H. (1956). Zusammenhang von graphentheorie und MO-theorie von molekeln mit systemen konjugierter bindungen. Helv. Chim. Acta 39, 1645-1653. doi: 10.1002/hlca.19560390623
11. Gutenkunst, R., Waterfall, J., Casey, F., Brown, K., Myers, C., and Sethna, J. (2007). Universally sloppy parameter sensitivities in systems biology models. PLoS Comput. Biol. 3:e189. doi: 10.1371/journal.pcbi.0030189
12. Gutman, I., and Zhou, B. (2006). Laplacian energy of a graph. Linear Algebra Appl. 414, 29-37. doi: 10.1016/j.laa.2005.09.008
13. Han, J., Bertin, N., Hao, T., Goldberg, D. S., Berriz, G. F., Zhang, L. V., et al. (2004). Evidence for dynamically organized modularity in the yeast protein interaction network. Nature 430, 88-93. doi: 10.1038/nature02555
14. Hartwell, L. H., Hopfield, J. J., Leibler, S., and Murray, A. W. (1999). From molecular to modular cell biology. Nature 402(Suppl. 6761), C47-C52. doi: 10.1038/35011540
15. Jeong, H., Mason, S., Barabasi, A., and Oltvai, Z. (2001). Lethality and centrality in protein networks. Nature 411, 41-42. doi: 10.1038/35075138
16. Jeong, H., Oltvai, Z. N., and Barabasi, A. L. (2003). Prediction of protein essentiality based on genomic data. Complexus 1, 19-28. doi: 10.1159/000067640
17. Jiang, Y. H., Bressler, J., and Beaudet, A. L. (2004). Epigenetics and human disease. Annu. Rev. Genomics Hum. Genet. 5, 479-510. doi: 10.1146/annurev.genom.5.061903.180014
18. Ma, H. W., Zhao, X. M., Yuan, Y. J., and Zeng, A. P. (2004). Decomposition of metabolic network into functional modules based on the global connectivity structure of reaction graph. Bioinformatics 20, 1870-1876. doi: 10.1093/bioinformatics/bth167
19. MacFarlane, R. G. (1964). An enzyme cascade in the blood clotting mechanism, and its function as a biochemical amplifier. Nature 202, 498-499. doi: 10.1038/202498a0
20. McCarthy, M. I., Abecasis, G. R., Cardon, L. R., Goldstein, D. B., Little, J., Ioannidis, J. P. A., et al. (2008). Genome-wide association studies for complex traits: consensus, uncertainty and challenges. Nat. Rev. Genet. 9, 356-369. doi: 10.1038/nrg2344
21. Mikulecki, D. C. (2001). Network thermodynamics and complexity: a transition to relational systems theory. Comput. Chem. 25, 369-391. doi: 10.1016/S0097-8485(01)00072-9
22. Noble, D. (2012). A theory of biological relativity: no privileged level of causation. Interface Focus 2, 55-64. doi: 10.1098/rsfs.2011.0067
23. Nordling, T. E., Hiroi, N., Funahashi, A., and Kitano, H. (2007). Deduction of intracellular sub-systems from a topological description of the network. Mol. Biosyst. 3, 523-529. doi: 10.1039/b702142a
24. Palumbo, M. C., Colosimo, A., Giuliani, A., and Farina, L. (2005). Functional essentiality from topology features in metabolic networks: a case study in yeast. FEBS Lett. 579, 4642-4646. doi: 10.1016/j.febslet.2005.07.033
25. Palumbo, M. C., Colosimo, A., Giuliani, A., and Farina, L. (2007). Essentiality is an emergent property of metabolic network wiring. FEBS Lett. 581, 2485-2489. doi: 10.1016/j.febslet.2007.04.067
26. Sun, J., Garibaldi, J. M., and Hodgman, C. (2012). Parameter estimation using metaheuristics in systems biology: a comprehensive review. IEEE/ACM Trans. Comput. Biol. Bioinform. 9, 185-202. doi: 10.1109/TCBB.2011.63
27. Tellegen, B. D. H. (1952). A general network theorem, with applications. Philips Res. Rep. 7, 259-269.
28. Todeschini, R., and Consonni, V. (2008). Handbook of Molecular Descriptors. New York: Wiley.
29. Tun, K., Menghini, M., D'Andrea, L., Tanaka, H., Dhar, P., and Giuliani, A. (2011). Why so few drug targets: a mathematical explanation? Curr. Comput. Aided Drug Des. 7, 206-213. doi: 10.2174/157340911796504297
30. Watts, D. J., and Strogatz, S. H. (1998). Collective dynamics of "small world" networks. Nature 393, 440-442. doi: 10.1038/30918