Comparative genome analysis of filamentous fungi reveals gene family expansions associated with fungal pathogenesis.

Fungi and oomycetes are the causal agents of many of the most serious diseases of plants. Here we report a detailed comparative analysis of the genome sequences of thirty-six species of fungi and oomycetes, including seven plant pathogenic species, that aims to explore the common genetic features associated with plant disease-causing species. The predicted translational products of each genome have been clustered into groups of potential orthologues using Markov Chain Clustering and the data integrated into the e-Fungi object-oriented data warehouse (http://www.

Information quality in proteomics.

Proteomics, the study of the protein complement of a biological system, is generating increasing quantities of data from rapidly developing technologies employed in a variety of different experimental workflows. Experimental processes, e.g.

e-Fungi: a data resource for comparative analysis of fungal genomes.

Background: The number of sequenced fungal genomes is ever increasing, with about 200 genomes already fully sequenced or in progress. Only a small percentage of those genomes have been comprehensively studied, for example using techniques from functional genomics. Comparative analysis has proven to be a useful strategy for enhancing our understanding of evolutionary biology and of the less well understood genomes.

Comparative genome analysis across a kingdom of eukaryotic organisms: specialization and diversification in the fungi.

The recent proliferation of genome sequencing in diverse fungal species has provided the first opportunity for comparative genome analysis across a eukaryotic kingdom. Here, we report a comparative study of 34 complete fungal genome sequences, representing a broad diversity of Ascomycete, Basidiomycete, and Zygomycete species. We have clustered all predicted protein-encoding gene sequences from these species to provide a means of investigating gene innovations, gene family expansions, protein family diversification, and the conservation of essential gene functions-empirically determined in Saccharomyces cerevisiae-among the fungi.

A systematic strategy for large-scale analysis of genotype phenotype correlations: identification of candidate genes involved in African trypanosomiasis.

It is increasingly common to combine Microarray and Quantitative Trait Loci data to aid the search for candidate genes responsible for phenotypic variation. Workflows provide a means of systematically processing these large datasets and also represent a framework for the re-use and the explicit declaration of experimental methods. In this article, we highlight the issues facing the manual analysis of microarray and QTL data for the discovery of candidate genes underlying complex phenotypes.

Model-driven user interfaces for bioinformatics data resources: regenerating the wheel as an alternative to reinventing it.

Background: The proliferation of data repositories in bioinformatics has resulted in the development of numerous interfaces that allow scientists to browse, search and analyse the data that they contain. Interfaces typically support repository access by means of web pages, but other means are also used, such as desktop applications and command line tools. Interfaces often duplicate functionality amongst each other, and this implies that associated development activities are repeated in different laboratories.

GIMS: an integrated data storage and analysis environment for genomic and functional data.

Effective analyses in functional genomics require access to many kinds of biological data. For example, the analysis of upregulated genes in a microarray experiment might be aided by information concerning protein interactions or proteins' cellular locations. However, such information is often stored in different formats at different sites, in ways that may not be amenable to integrated analysis.