Biomedical subjects

Pietro Liò

Publications and source records attributed to Pietro Liò.

5 recordsLinked to original sources

PubMed2003

Statistical bioinformatic methods in microbial genome analysis.

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.

Computational Biology↗

PubMed2003

Dimensionality and dependence problems in statistical genomics.

Genome studies have become central to a wide range of biological areas. This paper is intended to discuss the state of art and potentiality of using statistics in genome comparison. The problem of dependence and dimensionality in genome data is addressed first. The focus is on using phylogenetic methods in genome comparison, on combining sequence and gene expression data to find transcription sites, and on multiple hypothesis testing in gene expression data. The paper concludes with speculations on the future course of statistical and bioinformatics analyses.

Animals↗

PubMed2003

Wavelets in bioinformatics and computational biology: state of art and perspectives.

MOTIVATION: At a recent meeting, the wavelet transform was depicted as a small child kicking back at its father, the Fourier transform. Wavelets are more efficient and faster than Fourier methods in capturing the essence of data. Nowadays there is a growing interest in using wavelets in the analysis of biological sequences and molecular biology-related signals. RESULTS: This review is intended to summarize the potential of state of the art wavelets, and in particular wavelet statistical methodology, in different areas of molecular biology: genome sequence, protein structure and microarray data analysis. I conclude by discussing the use of wavelets in modeling biological structures.

Algorithms↗

PubMed2002

Modeling mitochondrial protein evolution using structural information.

We present two new models of protein sequence evolution based on structural properties of mitochondrial proteins. We compare these models with others currently used in phylogenetic analyses, investigating their performance over both short and long evolutionary distances. We find that our models that incorporate secondary structure information from mitochondrial proteins are statistically comparable with existing models when studying 13 mitochondrial protein data sets from eutherian mammals. However, our models give a significantly improved description of the evolutionary process when used with 12 mitochondrial proteins from a broader range of organisms including fungi, plants, protists, and bacteria. Our models may thus be of use in estimating mitochondrial protein phylogenies and for the study of processes of mitochondrial protein evolution, in particular for distantly related organisms.

Evolution, Molecular↗

PubMed2002

Investigating the relationship between genome structure, composition, and ecology in prokaryotes.

Our thesis is that the DNA composition and structure of genomes are selected in part by mutation bias (GC pressure) and in part by ecology. To illustrate this point, we compare and contrast the oligonucleotide composition and the mosaic structure in 36 complete genomes and in 27 long genomic sequences from archaea and eubacteria. We report the following findings (1) High-GC-content genomes show a large underrepresentation of short distances between G(n) and C(n) homopolymers with respect to distances between A(n) and T(n) homopolymers; we discuss selection versus mutation bias hypotheses. (2) The oligonucleotide compositions of the genomes of Neisseria (meningitidis and gonorrhoea), Helicobacter pylori and Rhodobacter capsulatus are more biased than the other sequenced genomes. (3) The genomes of free-living species or nonchronic pathogens show more mosaic-like structure than genomes of chronic pathogens or intracellular symbionts. (4) Genome mosaicity of intracellular parasites has a maximum corresponding to the average gene length; in the genomes of free-living and nonchronic pathogens the maximum occurs at larger length scales. This suggests that free-living species can incorporate large pieces of DNA from the environment, whereas for intracellular parasites there are recombination events between homologous genes. We discuss the consequences in terms of evolution of genome size. (5) Intracellular symbionts and obligate pathogens show small, but not zero, amount of chromosome mosaicity, suggesting that recombination events occur in these species.

AT Rich Sequence↗