Journalartikel

Development of joint application strategies for two microbial gene finders


AutorenlisteMcHardy, AC; Goesmann, A; Pühler, A; Meyer, F

Jahr der Veröffentlichung2004

Seiten1622-1631

ZeitschriftBioinformatics

Bandnummer20

Heftnummer10

ISSN1367-4803

eISSN1460-2059

DOI Linkhttps://doi.org/10.1093/bioinformatics/bth137

VerlagOxford University Press


Abstract
Motivation: As a starting point in annotation of bacterial genomes, gene finding programs are used for the prediction of functional elements in the DNA sequence. Due to the faster pace and increasing number of genome projects currently underway, it is becoming especially important to have performant methods for this task.Results: This study describes the development of joint application strategies that combine the strengths of two microbial gene finders to improve the overall gene finding performance. Critica is very specific in the detection of similarity-supported genes as it uses a comparative sequence analysis-based approach. Glimmer employs a very sophisticated model of genomic sequence properties and is sensitive also in the detection of organism-specific genes. Based on a data set of 113 microbial genome sequences, we optimized a combined application approach using different parameters with relevance to the gene finding problem. This results in a significant improvement in specificity while there is similarity in sensitivity to Glimmer. The improvement is especially pronounced for GC rich genomes. The method is currently being applied for the annotation of several microbial genomes.



Autoren/Herausgeber




Zitierstile

Harvard-ZitierstilMcHardy, A., Goesmann, A., Pühler, A. and Meyer, F. (2004) Development of joint application strategies for two microbial gene finders, Bioinformatics, 20(10), pp. 1622-1631. https://doi.org/10.1093/bioinformatics/bth137

APA-ZitierstilMcHardy, A., Goesmann, A., Pühler, A., & Meyer, F. (2004). Development of joint application strategies for two microbial gene finders. Bioinformatics. 20(10), 1622-1631. https://doi.org/10.1093/bioinformatics/bth137


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