On the basis of functional and phylogenetic criteria, we have identified a total of 229 subfamilies and 111 singletons predicted to carry out transport or other membrane functions in Saccharomyces cerevisiae. We have extended the Transporter Classification (TC) and created a Membrane Classification (MC) for non-transporter membrane proteins. Using the preliminary phylogenetic digits X, Y, Z (for new families, subfamilies, and clusters, respectively), we allocated a five-digit number to 850 proteins predicted to contain more than two transmembrane domains. Compared with a previous TC of the yeast genome, we classified an additional set of 538 membrane proteins (transporters and non-transporters) and identified 111 novel phylogenetic subfamilies.
We have traced the evolution patterns of 2480 transmembrane transporters from five complete genome sequences spanning the entire Hemiascomycete phylum: Saccharomyces cerevisiae, Candida glabrata, Kluyveromyces lactis, Debaryomyces hansenii, and Yarrowia lipolytica. The use of nonambiguous functional and phylogenetic criteria derived from the TCDB classification system has allowed the identification within the Hemiascomycete phylum of 97 small phylogenetic transporter subfamilies comprising a
This work focuses on differential expression analysis of microarray datasets. One way to improve such statistical analyses is to integrate biological information in the design of these analyses. In this paper, we will use the relationship between the level of gene expression and variability. Using this biological information, we propose to integrate the information from multiple genes to get a better estimate of individual gene variance, when a small number of replicates are available, to increase the power of the statistical analysis. We describe a strategy named the "Window t test" that uses multiple genes which share a similar expression level to compute the variance which is then incorporated a classic t test. The performances of this new method are evaluated by comparison with classic and widely-used methods for differential expression analysis (the classic Student t test, the Regularized t test (reg t test), SAM, Limma, LPE and Shrinkage t). In each case tested, the results obtained were at least equivalent to the best performing method and, in most cases, outperformed it. Moreover, the Window t test relies on a very simple procedure requiring small computing power compared with other methods designed for microarray differential expression analysis.
BackgroundRecent reanalysis of spike-in datasets underscored the need for new and more accurate benchmark datasets for statistical microarray analysis. We present here a fresh method using biologically-relevant data to evaluate the performance of statistical methods.ResultsOur novel method ranks the probesets from a dataset composed of publicly-available biological microarray data and extracts subset matrices with precise information/noise ratios. Our method can be used to determine the capability of different methods to better estimate variance for a given number of replicates. The mean-variance and mean-fold change relationships of the matrices revealed a closer approximation of biological reality.ConclusionsPerformance analysis refined the results from benchmarks published previously.We show that the Shrinkage t test (close to Limma) was the best of the methods tested, except when two replicates were examined, where the Regularized t test and the Window t test performed slightly better.AvailabilityThe R scripts used for the analysis are available at http://urbm-cluster.urbm.fundp.ac.be/~bdemeulder/.
Stress-induced premature senescence (SIPS) has been proposed as an in-vitro model for testing the long-term effects of stressful events and to find molecules/natural extracts that protect against such stress. Premature senescence of human skin diploid fibroblasts (HDFs) can be induced by repeated subcytotoxic exposure to UVB, with the appearance of so-called biomarkers of senescence such as growth arrest, senescence-associated beta-galactosidase activity, senescence-associated gene over-expression and the common 4977-bp mitochondrial DNA deletion. This model of UVB-induced premature senescence has been acknowledged as a robust in-vitro model in photoageing research. In this study, the potential anti-photoageing effects of a series of algal extracts were tested. The appearance of the biomarkers of UVB-induced premature senescence of HDFs was studied with or without algal extracts. One algal extract was shown to be particularly protective against UVB-induced SIPS. The results obtained here reinforce the notion that UVB-induced premature senescence of HDFs can be used to screen potential anti-photoageing compounds.
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