Factorizable language: from dynamics to bacterial complete genomes

Bailin Hao, Huimin Xie, Zuguo Yu and Guo-yi Chen

Physica A: Statistical Mechanics and its Applications, 2000, vol. 288, issue 1, 10-20

Abstract: Symbolic sequences generated by symbolic dynamics of a dynamical system belong to a special class of language in which any admissible word is factorisable as well as prolongable. From a complete genome sequence of an organism, one may also define a factorizable language. A factorizable language enjoys the nice property that it is entirely determined by the set of minimal fobidden words or distinct excluded blocks (DEBs). We use this property to calculate the fractal dimension of patterns related to a visualisation scheme of under-represented strings in bacterial complete genomes within the limit of infinitely long strings. The same problem may be solved by using a purely combinatorial approach. The methods described in this paper may be applied to other regular fractals with self-similar and self-overlapping structure.

Keywords: Language; Symbolic dynamics; Genome (search for similar items in EconPapers)
Date: 2000
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0378437100004118
Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:288:y:2000:i:1:p:10-20

DOI: 10.1016/S0378-4371(00)00411-8

Access Statistics for this article

Physica A: Statistical Mechanics and its Applications is currently edited by K. A. Dawson, J. O. Indekeu, H.E. Stanley and C. Tsallis

More articles in Physica A: Statistical Mechanics and its Applications from Elsevier
Bibliographic data for series maintained by Catherine Liu ().