Treffer: Finding prokaryotic genes by the frame-by-frame' algorithm : targeting gene starts and overlapping genes

Title:
Finding prokaryotic genes by the frame-by-frame' algorithm : targeting gene starts and overlapping genes
Source:
Special Issue containing a selection of papers presented at the Second Georgia Tech International Conference on Bioinformatics, in Silico Biology, on Sequence, Structure and Function at Atlanta, GA, November 11-14, 1999Bioinformatics (Oxford. Print). 15(11):874-886
Publisher Information:
Oxford: Oxford University Press, 1999.
Publication Year:
1999
Physical Description:
print, 32 ref
Original Material:
INIST-CNRS
Document Type:
Konferenz Conference Paper
File Description:
text
Language:
English
Author Affiliations:
Russian Academy of Science, The Institute for Problems in Mechanics, Moscow 11526, Russian Federation
School of Biology Georgia Institute of Technology, Atlanta, GA 30033, United States
ISSN:
1367-4803
Rights:
Copyright 2000 INIST-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Biological sciences. Generalities. Modelling. Methods

Generalities in biological sciences

Microbiology
Accession Number:
edscal.1359654
Database:
PASCAL Archive

Weitere Informationen

Motivation: Tightly packed prokaryotic genes frequently overlap with each other. This feature, rarely seen in eukaryotic DNA, makes detection of translation initiation sites and, therefore, exact predictions of prokaryotic genes notoriously difficult. Improving the accuracy of precise gene prediction in prokaryotic genomic DNA remains an important open problem. Results: A software program implementing a new algorithm utilizing a uniform Hidden Markov Model for prokaryotic gene prediction was developed. The algorithm analyzes a given DNA sequence in each of six possible global reading frames independently. Twelve complete prokaryotic genomes were analyzed using the new tool. The accuracy of gene finding, predicting locations of protein-coding ORFs, as well as the accuracy of precise gene prediction, and detecting the whole gene including translation initiation codon were assessed by comparison with existing annotation. It was shown that in terms of gene finding, the program performs at least as well as the previously developed tools, such as GeneMark and GLIMMER. In terms of precise gene prediction the new program was shown to be more accurate, by several percentage points, than earlier developed tools, such as GeneMark.hmm, ECOPARSE and ORPHEUS. The results of testing the program indicated the possibility of systematic bias in start codon annotation in several early sequenced prokaryotic genomes. Availability: The new gene-finding program can be accessed through the Web site: http://dixie.biology.gatech. edu/GeneMark/fbf.cgi.