Network motifs emerge from interconnections that favour stability

Nature Physics

Volumn 11, Issue 10, 2015, Pages 848-852

  Angulo, Marco Tulio ^a,b   Liu, Yang Yu ^b,c   Slotine, Jean Jacques ^d,e  

^a NORTHEASTERN UNIVERSITY   (United States)

^b HARVARD MEDICAL SCHOOL   (United States)

^c DANA FARBER CANCER INSTITUTE   (United States)

^d MASSACHUSETTS INSTITUTE OF TECHNOLOGY   (United States)

^e Massachusetts Institute of Technology Cambridge   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

COMPLEX NETWORKS;

BIOLOGICAL NETWORKS; INTERCONNECTION PATTERNS; INTRINSIC STABILITY; LARGE NETWORKS; LARGER NETWORKS; MICROSCOPIC PRINCIPLES; RANDOM NETWORK; REAL NETWORKS;

INTERCONNECTION NETWORKS (CIRCUIT SWITCHING);

EID: 84943175194     PISSN: 17452473     EISSN: 17452481     Source Type: Journal    
DOI: 10.1038/nphys3402     Document Type: Article

References (30)

1. Milo, R. et al. Network motifs: Simple building blocks of complex networks. Science 298, 824-827 (2002).
2. Alon, U. Network motifs: Theory and experimental approaches. Nature Rev. Genetics 8, 450-461 (2007).
3. Mangan, S. & Alon, U. Structure and function of the feed-forward loop network motif. Proc. Natl Acad. Sci. USA 100, 11980-11985 (2003).
4. Mangan, S., Zaslaver, A. & Alon, U. The coherent feedforward loop serves as a sign-sensitive delay element in transcription networks. J. Mol. Biol. 334, 197-204 (2003).
5. Prill, R. J., Iglesias, P. A. & Levchenko, A. Dynamic properties of network motifs contribute to biological network organization. PLoS Biol. 3, e343 (2005).
6. Lodato, I., Boccaletti, S. & Latora, V. Synchronization properties of network motifs. Europhys. Lett. 78, 28001 (2007).
7. Ma,W., Trusina, A., El-Samad, H., Lim,W. A. & Tang, C. Defining network topologies that can achieve biochemical adaptation. Cell 138, 760-773 (2009).
8. Shoval, O. et al. Fold-change detection and scalar symmetry of sensory input fields. Proc. Natl Acad. Sci. USA 107, 15995-16000 (2010).
9. Rodrigo, G. & Elena, S. F. Structural discrimination of robustness in transcriptional feed-forward loops for pattern formation. PLoS ONE 6, e16904 (2011).
10. Wang, P., Lu, J. & Ogorzalek, M. J. Global relative parameter sensitivities of the feedforward loops in genetic networks. Neurocomputing 78, 155-165 (2012).
11. Hart, Y., Antebi, Y. E., Mayo, A. E., Friedman, N. & Alon, U. Design principles of cell circuits with paradoxical components. Proc. Natl Acad. Sci. USA 109, 8346-8351 (2012).
12. Genot, A. J., Fujii, T. & Rondelez, Y. Computing with competition in biochemical networks. Phys. Rev. Lett. 109, 208102 (2012).
13. Hart, Y. & Alon, U. The utility of paradoxical components in biological circuits. Mol. Cell 49, 213-221 (2013).
14. Hart, Y., Mayo, A. E., Shoval, O. & Alon, U. Comparing apples and oranges: Fold-change detection of multiple simultaneous inputs. PLoS ONE 8, e57455 (2013).
15. Adler, M., Mayo, A. & Alon, U. Logarithmic and power law input-output relations in sensory systems with fold-change detection. PLoS Comput. Biol. 10, e1003781 (2014).
16. Bernstein, N. A. The Co-ordination and Regulation of Movements (Pergamon Press, 1967).
17. Bizzi, E., Giszter, S. F., Loeb, E., Mussa-Ivaldi, F. A. & Saltiel, P. Modular organization of motor behavior in the frog's spinal cord. Trends Neurosci. 18, 442-446 (1995).
18. LeDoux, J. The Emotional Brain: The Mysterious Underpinnings of Emotional Life (Simon and Schuster, 1998).
19. Kashtan, N. & Alon, U. Spontaneous evolution of modularity and network motifs. Proc. Natl Acad. Sci. USA 102, 13773-13778 (2005).
20. Slotine, J.-J. & Lohmiller,W. Modularity, evolution, and the binding problem: A view from stability theory. Neural Netw. 14, 137-145 (2001).
21. Allesina, S. & Tang, S. Stability criteria for complex ecosystems. Nature 483, 205-208 (2012).
22. Han, S. K., Kurrer, C. & Kuramoto, Y. Dephasing and bursting in coupled neural oscillators. Phys. Rev. Lett. 75, 3190-3193 (1995).
23. Campbell, S. & Wang, D. Synchronization and desynchronization in a network of locally coupledWilson-Cowan oscillators. IEEE Trans. Neural Netw. 7, 541-554 (1996).
24. Nakao, H. & Mikhailov, A. S. Turing patterns in network-organized activator-inhibitor systems. Nature Phys. 6, 544-550 (2010).
25. Lohmiller,W. & Slotine, J.-J. E. On contraction analysis for non-linear systems. Automatica 34, 683-696 (1998).
26. Russo, G., di Bernardo, M. & Sontag, E. A contraction approach to the hierarchical analysis and design of networked systems. IEEE Trans. Autom. Control 58, 1328-1331 (2013).
27. Kashtan, N., Itzkovitz, S., Milo, R. & Alon, U. Topological generalizations of network motifs. Phys. Rev. E 70, 031909 (2004).
28. Simon, H. A. The architecture of complexity. Proc. Am. Phil. Soc. 106, 467-482 (1962).
29. Alon, U. Biological networks: The tinkerer as an engineer. Science 301, 1866-1867 (2003).
30. Itzkovitz, S. et al. Coarse-graining and self-dissimilarity of complex networks. Phys. Rev. E 71, 016127 (2005).