Dempster-Shafer Theory for the Prediction of Auxin-Response Elements (AuxREs) in Plant Genomes.
Auxin is a major regulator of plant growth and development; its action involves transcriptional activation. The identification of Auxin-response element (AuxRE) is one of the most important issues to understand the Auxin regulation of gene expression. Over the past few years, a large number of motif...
| Publicado en: | BioMed Research International pp. 1 - 14 |
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| Autores principales: | , , , |
| Formato: | equations & formulas research tables/charts Journal Article |
| Publicado: |
Wiley-Blackwell
11/1/2018
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=132770509&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 132770509 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 23146133 FT2T jtl: BioMed Research International issn: 23146133 maglogo: N pubinfo: dt: 11/1/2018 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 132770509 132770509 132770509 10.1155/2018/3837060 132770509 ppf: 1 ppct: 13 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Dempster-Shafer Theory for the Prediction of Auxin-Response Elements (AuxREs) in Plant Genomes. aug: au: Sghaier, Nesrine Ben Ayed, Rayda Ben Marzoug, Riadh Rebai, Ahmed affil: Laboratory of Molecular and Cellular Screening Processes, Center of Biotechnology of Sfax, BP 1177, Sfax 3018, Tunisia sug: subj: Indoles Genome Plants Models, Theoretical Predictive Validity Sensitivity and Specificity Genes Gene Expression ab: Auxin is a major regulator of plant growth and development; its action involves transcriptional activation. The identification of Auxin-response element (AuxRE) is one of the most important issues to understand the Auxin regulation of gene expression. Over the past few years, a large number of motif identification tools have been developed. Despite these considerable efforts provided by computational biologists, building reliable models to predict regulatory elements has still been a difficult challenge. In this context, we propose in this work a data fusion approach for the prediction of AuxRE. Our method is based on the combined use of Dempster-Shafer evidence theory and fuzzy theory. To evaluate our model, we have scanning the DORNRÖSCHEN promoter by our model. All proven AuxRE present in the promoter has been detected. At the 0.9 threshold we have no false positive. The comparison of the results of our model and some previous motifs finding tools shows that our model can predict AuxRE more successfully than the other tools and produce less false positive. The comparison of the results before and after combination shows the importance of Dempster-Shafer combination in the decrease of false positive and to improve the reliability of prediction. For an overall evaluation we have chosen to present the performance of our approach in comparison with other methods. In fact, the results indicated that the data fusion method has the highest degree of sensitivity (Sn) and Positive Predictive Value (PPV). pubtype: Academic Journal doctype: equations & formulas research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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