Statistical bioinformatic methods in microbial genome analysis

Abstract

It is probable that, increasingly, genome investigations are going to be based on statistical formalization. This review summarizes the state of art and potentiality of using statistics in microbial genome analysis. First, I focus on recent advances in functional genomics, such as finding genes and operons, identifying gene conversion events, detecting DNA replication origins and analysing regulatory sites. Then I describe how to use phylogenetic methods in genome analysis and methods for genome-wide scanning for positively selected amino acids. I conclude with speculations on the future course of genome statistical modeling.

Self-organization and entropy reduction in a living cell

“…There has been significant progress in our quantitative understanding of information content involved in DNA, RNA championed by Schneider (2001) and transcription factors by Kim et al (2003) and by for macromolecules Sadovsky (2003) and even whole microbial genomes by Lio (2003).…”