Biomedical subjects

Gaston Gonnet

Publications and source records attributed to Gaston Gonnet.

3 recordsLinked to original sources

PubMed2006

A phylogenomic study of human, dog, and mouse.

In recent years the phylogenetic relationship of mammalian orders has been addressed in a number of molecular studies. These analyses have frequently yielded inconsistent results with respect to some basal ordinal relationships. For example, the relative placement of primates, rodents, and carnivores has differed in various studies. Here, we attempt to resolve this phylogenetic problem by using data from completely sequenced nuclear genomes to base the analyses on the largest possible amount of data. To minimize the risk of reconstruction artifacts, the trees were reconstructed under different criteria-distance, parsimony, and likelihood. For the distance trees, distance metrics that measure independent phenomena (amino acid replacement, synonymous substitution, and gene reordering) were used, as it is highly improbable that all of the trees would be affected the same way by any reconstruction artifact. In contradiction to the currently favored classification, our results based on full-genome analysis of the phylogenetic relationship between human, dog, and mouse yielded overwhelming support for a primate-carnivore clade with the exclusion of rodents.

Animals↗

PubMed2005

Scoring functions for transcription factor binding site prediction.

BACKGROUND: Transcription factor binding site (TFBS) prediction is a difficult problem, which requires a good scoring function to discriminate between real binding sites and background noise. Many scoring functions have been proposed in the literature, but it is difficult to assess their relative performance, because they are implemented in different software tools using different search methods and different TFBS representations. RESULTS: Here we compare how several scoring functions perform on both real and semi-simulated data sets in a common test environment. We have also developed two new scoring functions and included them in the comparison. The data sets are from the yeast (S. cerevisiae) genome. Our new scoring function LLBG (least likely under the background model) performs best in this study. It achieves the best average rank for the correct motifs. Scoring functions based on positional bias performed quite poorly in this study. CONCLUSION: LLBG may provide an interesting alternative to current scoring functions for TFBS prediction.

Algorithms↗

PubMed2004

Limitations of codon adaptation index and other coding DNA-based features for prediction of protein expression in Saccharomyces cerevisiae.

The relationship between codon usage and protein/mRNA expression in S. cerevisiae has been extensively studied. Recently, protein expression data for the whole yeast genome was published. We investigate which properties of coding DNA sequences can be used to predict expression levels. The new algorithm by Carbone et al. for computing dominating codon bias in a genome is evaluated. It is concluded that it works at least as well as existing methods, and eliminates the need to arbitrarily choose a set of highly expressed genes. Also, the hypothesis that information on codon pair frequencies can be used to predict expression is investigated. Our conclusion is that codon pairs do not contribute more information than do single codon frequencies. Overall correlation between predicted and actual expression data using properties of coding DNA sequences is around 0.65. Hence, while being a useful source of information, the expression levels predicted by these methods should only be used as a rule of thumb.

Algorithms↗