Analysis and prediction of gene splice sites in four Aspergillus genomes

Kai Wang, David Ussery, Søren Brunak

    Research output: Contribution to journalJournal articlepeer-review

    Abstract

    Several Aspergillus fungal genomic sequences have been published, with many more in progress. Obviously, it is essential to have high-quality, consistently annotated sets of proteins from each of the genomes, in order to make meaningful comparisons. We have developed a dedicated, publicly available, splice site prediction program called NetAspGene, for the genus Aspergillus. Gene sequences from Aspergillus fumigatus, the most common mould pathogen, were used to build and test our model. Compared to many animals and plants, Aspergillus contains smaller introns; thus we have applied a larger window size on single local networks for training, to cover both donor and acceptor site information. We have applied NetAspGene to other Aspergilli, including Aspergillus nidulans, Aspergillus oryzae, and Aspergillus niger. Evaluation with independent data sets reveal that NetAspGene performs substantially better splice site prediction than other available tools. NetAspGene will be very helpful for the study in Aspergillus splice sites and especially in alternative splicing. A webpage for NetAspGene is publicly available at http://www.cbs.dtu.dk/services/NetAspGene.
    Original languageEnglish
    JournalFungal Genetics and Biology
    Volume46
    Pages (from-to)S14-S18
    ISSN1087-1845
    DOIs
    Publication statusPublished - 2009

    Keywords

    • Artificial neural networks (ANNs)
    • Splice site predictor
    • Bioinformatics
    • Aspergillus
    • Web server

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