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An integrative and applicable phylogenetic footprinting framework for cis-regulatory motifs identification in prokaryotic genomes

Overview of attention for article published in BMC Genomics, August 2016
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Title
An integrative and applicable phylogenetic footprinting framework for cis-regulatory motifs identification in prokaryotic genomes
Published in
BMC Genomics, August 2016
DOI 10.1186/s12864-016-2982-x
Pubmed ID
Authors

Bingqiang Liu, Hanyuan Zhang, Chuan Zhou, Guojun Li, Anne Fennell, Guanghui Wang, Yu Kang, Qi Liu, Qin Ma

Abstract

Phylogenetic footprinting is an important computational technique for identifying cis-regulatory motifs in orthologous regulatory regions from multiple genomes, as motifs tend to evolve slower than their surrounding non-functional sequences. Its application, however, has several difficulties for optimizing the selection of orthologous data and reducing the false positives in motif prediction. Here we present an integrative phylogenetic footprinting framework for accurate motif predictions in prokaryotic genomes (MP(3)). The framework includes a new orthologous data preparation procedure, an additional promoter scoring and pruning method and an integration of six existing motif finding algorithms as basic motif search engines. Specifically, we collected orthologous genes from available prokaryotic genomes and built the orthologous regulatory regions based on sequence similarity of promoter regions. This procedure made full use of the large-scale genomic data and taxonomy information and filtered out the promoters with limited contribution to produce a high quality orthologous promoter set. The promoter scoring and pruning is implemented through motif voting by a set of complementary predicting tools that mine as many motif candidates as possible and simultaneously eliminate the effect of random noise. We have applied the framework to Escherichia coli k12 genome and evaluated the prediction performance through comparison with seven existing programs. This evaluation was systematically carried out at the nucleotide and binding site level, and the results showed that MP(3) consistently outperformed other popular motif finding tools. We have integrated MP(3) into our motif identification and analysis server DMINDA, allowing users to efficiently identify and analyze motifs in 2,072 completely sequenced prokaryotic genomes. The performance evaluation indicated that MP(3) is effective for predicting regulatory motifs in prokaryotic genomes. Its application may enhance progress in elucidating transcription regulation mechanism, thus provide benefit to the genomic research community and prokaryotic genome researchers in particular.

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Mendeley readers

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The data shown below were compiled from readership statistics for 39 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 39 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 12 31%
Student > Ph. D. Student 8 21%
Researcher 5 13%
Student > Bachelor 5 13%
Professor 2 5%
Other 1 3%
Unknown 6 15%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 13 33%
Agricultural and Biological Sciences 6 15%
Computer Science 5 13%
Medicine and Dentistry 2 5%
Psychology 1 3%
Other 2 5%
Unknown 10 26%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 11 August 2016.
All research outputs
#15,381,002
of 22,882,389 outputs
Outputs from BMC Genomics
#6,701
of 10,668 outputs
Outputs of similar age
#233,708
of 361,768 outputs
Outputs of similar age from BMC Genomics
#176
of 265 outputs
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So far Altmetric has tracked 10,668 research outputs from this source. They receive a mean Attention Score of 4.7. This one is in the 28th percentile – i.e., 28% of its peers scored the same or lower than it.
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We're also able to compare this research output to 265 others from the same source and published within six weeks on either side of this one. This one is in the 27th percentile – i.e., 27% of its contemporaries scored the same or lower than it.