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AtPAN: an integrated system for reconstructing transcriptional regulatory networks in Arabidopsis thaliana

Overview of attention for article published in BMC Genomics, March 2012
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Title
AtPAN: an integrated system for reconstructing transcriptional regulatory networks in Arabidopsis thaliana
Published in
BMC Genomics, March 2012
DOI 10.1186/1471-2164-13-85
Pubmed ID
Authors

Yi-An Chen, Ying-Chi Wen, Wen-Chi Chang

Abstract

Construction of transcriptional regulatory networks (TRNs) is of priority concern in systems biology. Numerous high-throughput approaches, including microarray and next-generation sequencing, are extensively adopted to examine transcriptional expression patterns on the whole-genome scale; those data are helpful in reconstructing TRNs. Identifying transcription factor binding sites (TFBSs) in a gene promoter is the initial step in elucidating the transcriptional regulation mechanism. Since transcription factors usually co-regulate a common group of genes by forming regulatory modules with similar TFBSs. Therefore, the combinatorial interactions of transcription factors must be modeled to reconstruct the gene regulatory networks. Description For systems biology applications, this work develops a novel database called Arabidopsis thaliana Promoter Analysis Net (AtPAN), capable of detecting TFBSs and their corresponding transcription factors (TFs) in a promoter or a set of promoters in Arabidopsis. For further analysis, according to the microarray expression data and literature, the co-expressed TFs and their target genes can be retrieved from AtPAN. Additionally, proteins interacting with the co-expressed TFs are also incorporated to reconstruct co-expressed TRNs. Moreover, combinatorial TFs can be detected by the frequency of TFBSs co-occurrence in a group of gene promoters. In addition, TFBSs in the conserved regions between the two input sequences or homologous genes in Arabidopsis and rice are also provided in AtPAN. The output results also suggest conducting wet experiments in the future.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 48 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 4%
Spain 1 2%
Turkey 1 2%
Germany 1 2%
Unknown 43 90%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 13 27%
Researcher 10 21%
Student > Master 10 21%
Student > Bachelor 4 8%
Student > Postgraduate 2 4%
Other 6 13%
Unknown 3 6%
Readers by discipline Count As %
Agricultural and Biological Sciences 30 63%
Biochemistry, Genetics and Molecular Biology 8 17%
Nursing and Health Professions 1 2%
Computer Science 1 2%
Social Sciences 1 2%
Other 0 0%
Unknown 7 15%
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 12 March 2012.
All research outputs
#18,305,470
of 22,663,969 outputs
Outputs from BMC Genomics
#8,144
of 10,614 outputs
Outputs of similar age
#121,128
of 156,269 outputs
Outputs of similar age from BMC Genomics
#47
of 55 outputs
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