MOTIVATION: Genomes contain biologically significant information that extends beyond that encoded in genes. Some of this information relates to various short dispersed repeats distributed throughout the genome. The goal of this work was to combine tools for detection of statistically significant dispersed repeats in DNA sequences with tools to aid development of hypotheses regarding their possible physiological functions in an easy-to-use web-based environment. RESULTS: Ab Initio Motif Identification Environment (AIMIE) was designed to facilitate investigations of dispersed sequence motifs in prokaryotic genomes. We used AIMIE to analyze the Escherichia coli and Haemophilus influenzae genomes in order to demonstrate the utility of the new environment. AIMIE detected repeated extragenic palindrome (REP) elements, CRISPR repeats, uptake signal sequences, intergenic dyad sequences and several other over-represented sequence motifs. Distributional patterns of these motifs were analyzed using the tools included in AIMIE. AVAILABILITY: AIMIE and the related software can be accessed at our web site http://www.cmbl.uga.edu/software.html.
MOTIVATION: Genomes contain biologically significant information that extends beyond that encoded in genes. Some of this information relates to various short dispersed repeats distributed throughout the genome. The goal of this work was to combine tools for detection of statistically significant dispersed repeats in DNA sequences with tools to aid development of hypotheses regarding their possible physiological functions in an easy-to-use web-based environment. RESULTS: Ab Initio Motif Identification Environment (AIMIE) was designed to facilitate investigations of dispersed sequence motifs in prokaryotic genomes. We used AIMIE to analyze the Escherichia coli and Haemophilus influenzae genomes in order to demonstrate the utility of the new environment. AIMIE detected repeated extragenic palindrome (REP) elements, CRISPR repeats, uptake signal sequences, intergenic dyad sequences and several other over-represented sequence motifs. Distributional patterns of these motifs were analyzed using the tools included in AIMIE. AVAILABILITY: AIMIE and the related software can be accessed at our web site http://www.cmbl.uga.edu/software.html.
Authors: Yuchen Liu; Li Guo; Rong Guo; Richard L Wong; Hilda Hernandez; Jinchuan Hu; Yindi Chu; I Jonathan Amster; William B Whitman; Li Huang Journal: J Bacteriol Date: 2009-01-23 Impact factor: 3.490
Authors: Ashley C Bono; Christine E Hartman; Sina Solaimanpour; Hao Tong; Steffen Porwollik; Michael McClelland; Jonathan G Frye; Jan Mrázek; Anna C Karls Journal: J Bacteriol Date: 2017-05-25 Impact factor: 3.490
Authors: Jennifer E Kurasz; Christine E Hartman; David J Samuels; Bijoy K Mohanty; Anquilla Deleveaux; Jan Mrázek; Anna C Karls Journal: J Bacteriol Date: 2018-11-06 Impact factor: 3.490
Authors: Sura Ali Al-Asadi; Rusul Emaduldeen S Al-Kahachi; Wifaq M Ali Alwattar; Jamila Bootwala; Majeed Arsheed Sabbah Journal: Microbiol Spectr Date: 2022-04-04
Authors: Tesfalem R Zere; Christopher A Vakulskas; Yuanyuan Leng; Archana Pannuri; Anastasia H Potts; Raquel Dias; Dongjie Tang; Bryan Kolaczkowski; Dimitris Georgellis; Brian M M Ahmer; Tony Romeo Journal: PLoS One Date: 2015-12-16 Impact factor: 3.240