Bioinformatic principles underlying the information content of transcription factor binding sites

Kim, Jan T., Martinetz, Thomas and Polani, Daniel (2003) Bioinformatic principles underlying the information content of transcription factor binding sites. Journal of Theoretical Biology, 220 (4). pp. 529-544. ISSN 0022-5193

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Abstract

Empirically, it has been observed in several cases that the information content of transcription factor binding site sequences (Rsequence) approximately equals the information content of binding site positions (Rfrequency). A general framework for formal models of transcription factors and binding sites is developed to address this issue. Measures for information content in transcription factor binding sites are revisited and theoretic analyses are compared on this basis. These analyses do not lead to consistent results. A comparative review reveals that these inconsistent approaches do not include a transcription factor state space. Therefore, a state space for mathematically representing transcription factors with respect to their binding site recognition properties is introduced into the modelling framework. Analysis of the resulting comprehensive model shows that the structure of genome state space favours equality of Rsequence and Rfrequency indeed, but the relation between the two information quantities also depends on the structure of the transcription factor state space. This might lead to significant deviations between Rsequence and Rfrequency. However, further investigation and biological arguments show that the effects of the structure of the transcription factor state space on the relation of Rsequence and Rfrequency are strongly limited for systems which are autonomous in the sense that all DNA-binding proteins operating on the genome are encoded in the genome itself. This provides a theoretical explanation for the empirically observed equality.

Item Type: Article
Faculty \ School: Faculty of Science > School of Computing Sciences
UEA Research Groups: Faculty of Science > Research Groups > Computational Biology
Depositing User: Vishal Gautam
Date Deposited: 13 Jun 2011 11:46
Last Modified: 22 Apr 2023 01:56
URI: https://ueaeprints.uea.ac.uk/id/eprint/22696
DOI: 10.1006/jtbi.2003.3153

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