Czy jesteśmy scale-free?

• Authors: Piotr H. Pawłowski

Title variants

EN

Are we scale-free

• Languages of publication: PL EN

Abstracts

EN

This article describes the scale-free property of biological networks. In practice, a scale-free network can be constructed by progressively adding nodes to an existing network by introducing new links to the existing nodes using preferential attachment mechanism. Are biological networks scale free? Is it an impact of universal mysterious power law on biological networks architecture?

• Journal: Kosmos
• Year: 2009
• Volume: 58
• Issue: 1-2
• Pages: 89-95

Dates

published

2009

Contributors

author

Piotr H. Pawłowski

• Instytut Biochemii i Biofizyki PAN, Pawińskiego 5a, 02-106 Warszawa, Polska

References

• Albert R., Jeong H., Barabasi A. L., 1999. Diameter of the world-wide web. Science 401, 130-131.
• Aloy P., Russell R. B., 2004. Taking the mystery out of biological networks. EMBO Rep. 5, 349-350.
• Barabasi A. L., Albert R., 1999. Emergence of scaling in random networks. Science 286, 509-512.
• Erdos P., Renyi A., 1959. On Random Graphs. I. Publicationes Mathematicae 6, 290-297.
• Erdos P., Renyi A., 1960. The evolution of Random Graphs. Magyar Tud. Akad. Mat. Kutato Int. Kozl. 5, 17-61.
• Jeong H., Tombor B., Albert R., Oltvai Z. N., Barabasi A. L., 2000. The large-scale organization of metabolic networks. Nature 407, 651-654.
• Khanin R, Wit E., 2006. How scale-free are biological networks. J. Comput. Biol. 13, 810-8.
• Li L., Alderson D., Doyle J. C., Willinger W., 2005. Towards a Theory of Scale-Free Graphs: Definition, Properties, and Implications. >Internet Math. 2, 431-523.
• Magwene P., Kim J., 2004. Estimating genomic coexpression networks using first-order conditional independence. Genome Biology 5, R100.
• Matsubara T., 2006. Statistics and Dynamics in the Large-scale Structure of the Universe. J. Physics: Conference Series 31, 27-34.
• Noort V., Snel B., Huynen M. A., 2004. The yeast coexpression network has a small-world, scale-free architecture and can be explained by a simple model. EMBO Rep. 5, 280-284.
• Pawlowski P. H., Kaczanowski S., Zielenkiewicz P., 2008. Protein interaction network. Double exponential model. JPB 1, 061-067.
• Song C., Havlin S., Makse H. A., 2005. Self-similarity of complex networks. Nature 433, 392-395.
• Tong A. H., Lesage G., Bader G. D., Ding H., Xu H., Xin X., Young J., Berriz G. F., Brost R. L., Chang M. i współaut., 2004. Global mapping of the yeast genetic interaction network. Science 303, 808-813.