{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2023,2,3]],"date-time":"2023-02-03T01:31:58Z","timestamp":1675387918115},"reference-count":28,"publisher":"Oxford University Press (OUP)","issue":"8","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2008,4,15]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>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.<\/jats:p>\n               <jats:p>Results: \u00a0Ab 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.<\/jats:p>\n               <jats:p>Availability: AIMIE and the related software can be accessed at our web site http:\/\/www.cmbl.uga.edu\/software.html.<\/jats:p>\n               <jats:p>Contact: \u00a0mrazek@uga.edu<\/jats:p>","DOI":"10.1093\/bioinformatics\/btn077","type":"journal-article","created":{"date-parts":[[2008,2,28]],"date-time":"2008-02-28T01:14:32Z","timestamp":1204161272000},"page":"1041-1048","source":"Crossref","is-referenced-by-count":13,"title":["AIMIE: a web-based environment for detection and interpretation of significant sequence motifs in prokaryotic genomes"],"prefix":"10.1093","volume":"24","author":[{"given":"Jan","family":"Mr\u00e1zek","sequence":"first","affiliation":[{"name":"1 Department of Microbiology, University of Georgia, Athens, GA 30602-2605, 2Institute of Bioinformatics, University of Georgia, Athens, GA 30602-7229 and 3Department of Computer Science, University of Georgia, Athens, GA 30602-7404, USA"},{"name":"1 Department of Microbiology, University of Georgia, Athens, GA 30602-2605, 2Institute of Bioinformatics, University of Georgia, Athens, GA 30602-7229 and 3Department of Computer Science, University of Georgia, Athens, GA 30602-7404, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shaohua","family":"Xie","sequence":"additional","affiliation":[{"name":"1 Department of Microbiology, University of Georgia, Athens, GA 30602-2605, 2Institute of Bioinformatics, University of Georgia, Athens, GA 30602-7229 and 3Department of Computer Science, University of Georgia, Athens, GA 30602-7404, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiangxue","family":"Guo","sequence":"additional","affiliation":[{"name":"1 Department of Microbiology, University of Georgia, Athens, GA 30602-2605, 2Institute of Bioinformatics, University of Georgia, Athens, GA 30602-7229 and 3Department of Computer Science, University of Georgia, Athens, GA 30602-7404, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Anuj","family":"Srivastava","sequence":"additional","affiliation":[{"name":"1 Department of Microbiology, University of Georgia, Athens, GA 30602-2605, 2Institute of Bioinformatics, University of Georgia, Athens, GA 30602-7229 and 3Department of Computer Science, University of Georgia, Athens, GA 30602-7404, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2008,2,26]]},"reference":[{"key":"2023020210001802500_B1","doi-asserted-by":"crossref","first-page":"51","DOI":"10.1007\/BF00993379","article-title":"Unsupervised learning of multiple motifs in biopolymers using expectation maximization","volume":"21","author":"Bailey","year":"1996","journal-title":"Machine Learning"},{"key":"2023020210001802500_B2","first-page":"329","article-title":"Poisson approximations for r-scan processes","volume":"2","author":"Dembo","year":"1988","journal-title":"Ann. 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