Functional Information, Biomolecular Messages and Complexity of BioSequences and Structures (Extended Abstract)

Structure Discovery in Biology: Motifs, Networks & Phylogenies

计算机科学;物理学;数学

Davide Corona ; Valeria Di Benedetto ; Alessandra Gabriele ; Raffaele Giancarlo ; Filippo Utro

Others  :  http://drops.dagstuhl.de/opus/volltexte/2010/2688/pdf/10231.GiancarloRaffaele.Paper.2688.pdf
PID  :  45007

学科分类：计算机科学（综合）

来源: CEUR

【 摘 要 】

In the quest for a mathematical measure able to capture and shed light on the dual notions of information and complexity in biosequences, Hazen et al. have introduced the notion of Functional Information (FI for short). It is also the result of earlier considerations and findings by Szostak and Carothers et al. Based on the experiments by Charoters et al., regarding FI in RNA binding activities, we decided to study the relation existing between FI and classic measures of complexity applied on protein-DNA interactions on a genome-wide scale. Using classic complexity measures, i.e, Shannon entropy and Kolmogorov Complexity as both estimated by data compression, we found that FI applied to protein-DNA interactions is genuinely different from them. Such a fact, together with the non-triviality of the biological function considered, contributes to the establishment of FI as a novel and useful measure of biocomplexity. Remarkably, we also found a relationship, on a genome-wide scale, between the redundancy of a genomic region and its ability to interact with a protein. This latter finding justifies even more some principles for the design of motif discovery algorithms. Finally, our experiments bring to light methodological limitations of Linguistic Complexity measures, i.e., a class of measures that is a function of the vocabulary richness of a sequence. Indeed, due to the technology and associated statistical preprocessing procedures used to conduct our studies, i.e., genome-wide ChIP-chip experiments, that class of measures cannot give any statistically significant indication about the relation between complexity and function. A serious limitation due to the widespread use of the technology.