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Emmersen, J.* ; Rudd, S.* ; Mewes, H.-W. ; Tetko, I.V.

Separation of sequences from host-pathogen interface using triplet nucleotide frequencies.

Fungal Genet. Biol. 44, 231-241 (2007)
DOI PMC
Open Access Green möglich sobald Postprint bei der ZB eingereicht worden ist.
The identification of genes involved in host-pathogen interactions is important for the elucidation of mechanisms of disease resistance and host susceptibility. A traditional way to classify the origin of genes sampled from a pool of mixed cDNA is through sequence similarity to known genes from either the pathogen or host organism or other closely related species. This approach does not work when the identified sequence has no close homologues in the sequence databases. In our previous studies, we classified genes using their codon frequencies. This method, however, explicitly required the prediction of CDS regions and thus could not be applied to sequences composed from the non-coding regions of genes. In this study, we show that the use of sliding-window triplet frequencies extends the application of the algorithm to both coding and non-coding sequences and also increases the prediction accuracy of a Support Vector Machine classifier from 95.6+/-0.3 to 96.5+/-0.2. Thus the use of the triplet frequencies increased the prediction accuracy of the new method by more than 20% compared to our previous approach. A functional analysis of sequences detected gene families having significantly higher or lower probability to be correctly classified compared to the average accuracy of the method is described. The server to perform classification of EST sequences using triplet frequencies is available at (URL: http://mips.gsf.de/proj/est3).
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Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Korrespondenzautor
Schlagwörter Bioinformatics ; Codon Bias ; Codon Usage ; Est Data Analysis ; Plant-fungi Interactions
ISSN (print) / ISBN 1087-1845
e-ISSN 1096-0937
Zeitschrift Fungal Genetics and Biology
Quellenangaben Band: 44, Heft: 4, Seiten: 231-241 Artikelnummer: , Supplement: ,
Verlag Elsevier
Verlagsort Amsterdam [u.a.]
Nichtpatentliteratur Publikationen
Begutachtungsstatus Peer reviewed
Institut(e) Institute of Bioinformatics and Systems Biology (IBIS)