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A probabilistic method for identifying start codons in bacterial genomes

Suzek, Baris E., Ermolaeva, Maria D., Schreiber, Mark, Salzberg, Steven L.·2001·Bioinformatics

Abstract

As the pace of genome sequencing has accelerated, the need for highly accurate gene prediction systems has grown. Computational systems for identifying genes in prokaryotic genomes have sensitivities of 98–99% or higher (Delcher et al. , Nucleic Acids Res. , 27, 4636–4641, 1999). These accuracy figures are calculated by comparing the locations of verified stop codons to the predictions. Determining the accuracy of start codon prediction is more problematic, however, due to the relatively small number of start sites that have been confirmed by independent, non-computational methods. Nonetheless, the accuracy of gene finders at predicting the exact gene boundaries at both the 5′ and 3′ ends of genes is of critical importance for microbial genome annotation, especially in light of the important signaling information that is sometimes found on the 5′ end of a protein coding region. In this paper we propose a probabilistic method to improve the accuracy of gene identification systems at finding precise translation start sites. The new system, RBSfinder, is tested on a validated set of genes from Escherichia coli , for which it improves the accuracy of start site locations predicted by computational gene finding systems from the range 67–77% to 90% correct. * To whom correspondence should be addressed.

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Metadata

Authors
Suzek, B. E., Ermolaeva, M. D., Schreiber, M., & Salzberg, S. L.
Venue
Bioinformatics
Published
2001-12-01
Volume
17
Issue
12
Pages
1123-1130
ISSN
  • 1367-4803 (ISSN-L)
  • 1367-4811
OpenAlex
W2168846269
Cited by
190
References
0
FWCI
2.93
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: A probabilistic method for identifying start codons in bacterial genomes. https://app.cochat.ai/papers/10.1093/bioinformatics/17.12.1123
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Suzek, B. E., Ermolaeva, M. D., Schreiber, M., & Salzberg, S. L. (2001). A probabilistic method for identifying start codons in bacterial genomes. Bioinformatics. https://doi.org/10.1093/bioinformatics/17.12.1123

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