TSSPlant: a new tool for prediction of plant Pol II promoters

Handle URI:
http://hdl.handle.net/10754/622722
Title:
TSSPlant: a new tool for prediction of plant Pol II promoters
Authors:
Shahmuradov, Ilham A.; Umarov, Ramzan; Solovyev, Victor V.
Abstract:
Our current knowledge of eukaryotic promoters indicates their complex architecture that is often composed of numerous functional motifs. Most of known promoters include multiple and in some cases mutually exclusive transcription start sites (TSSs). Moreover, TSS selection depends on cell/tissue, development stage and environmental conditions. Such complex promoter structures make their computational identification notoriously difficult. Here, we present TSSPlant, a novel tool that predicts both TATA and TATA-less promoters in sequences of a wide spectrum of plant genomes. The tool was developed by using large promoter collections from ppdb and PlantProm DB. It utilizes eighteen significant compositional and signal features of plant promoter sequences selected in this study, that feed the artificial neural network-based model trained by the backpropagation algorithm. TSSPlant achieves significantly higher accuracy compared to the next best promoter prediction program for both TATA promoters (MCC≃0.84 and F1-score≃0.91 versus MCC≃0.51 and F1-score≃0.71) and TATA-less promoters (MCC≃0.80, F1-score≃0.89 versus MCC≃0.29 and F1-score≃0.50). TSSPlant is available to download as a standalone program at http://www.cbrc.kaust.edu.sa/download/.
KAUST Department:
King Abdullah University of Science and Technology, Thuwal 23955-6900, Saudi Arabia.
Citation:
Shahmuradov IA, Umarov RK, Solovyev VV (2017) TSSPlant: a new tool for prediction of plant Pol II promoters. Nucleic Acids Research: gkw1353. Available: http://dx.doi.org/10.1093/nar/gkw1353.
Publisher:
Oxford University Press (OUP)
Journal:
Nucleic Acids Research
KAUST Grant Number:
URF/1/1976-02; FCS/1/2448-01
Issue Date:
13-Jan-2017
DOI:
10.1093/nar/gkw1353
Type:
Article
ISSN:
0305-1048; 1362-4962
Sponsors:
King Abdullah University of Science and Technology (KAUST) Office of Sponsored Research (OSR) [URF/1/1976-02, FCS/1/2448-01]; Science Development Foundation under the President of the Republic of Azerbaijan [Grant EİF-2010-1(1)-40/27-3]. Funding for open access charge: King Abdullah University of Science and Technology (Awards No URF/1/1976-02 and FCS/1/2448-01).
Additional Links:
https://academic.oup.com/nar/article/doi/10.1093/nar/gkw1353/2900189/TSSPlant-a-new-tool-for-prediction-of-plant-Pol-II
Appears in Collections:
Articles

Full metadata record

DC FieldValue Language
dc.contributor.authorShahmuradov, Ilham A.en
dc.contributor.authorUmarov, Ramzanen
dc.contributor.authorSolovyev, Victor V.en
dc.date.accessioned2017-01-24T08:30:07Z-
dc.date.available2017-01-24T08:30:07Z-
dc.date.issued2017-01-13en
dc.identifier.citationShahmuradov IA, Umarov RK, Solovyev VV (2017) TSSPlant: a new tool for prediction of plant Pol II promoters. Nucleic Acids Research: gkw1353. Available: http://dx.doi.org/10.1093/nar/gkw1353.en
dc.identifier.issn0305-1048en
dc.identifier.issn1362-4962en
dc.identifier.doi10.1093/nar/gkw1353en
dc.identifier.urihttp://hdl.handle.net/10754/622722-
dc.description.abstractOur current knowledge of eukaryotic promoters indicates their complex architecture that is often composed of numerous functional motifs. Most of known promoters include multiple and in some cases mutually exclusive transcription start sites (TSSs). Moreover, TSS selection depends on cell/tissue, development stage and environmental conditions. Such complex promoter structures make their computational identification notoriously difficult. Here, we present TSSPlant, a novel tool that predicts both TATA and TATA-less promoters in sequences of a wide spectrum of plant genomes. The tool was developed by using large promoter collections from ppdb and PlantProm DB. It utilizes eighteen significant compositional and signal features of plant promoter sequences selected in this study, that feed the artificial neural network-based model trained by the backpropagation algorithm. TSSPlant achieves significantly higher accuracy compared to the next best promoter prediction program for both TATA promoters (MCC≃0.84 and F1-score≃0.91 versus MCC≃0.51 and F1-score≃0.71) and TATA-less promoters (MCC≃0.80, F1-score≃0.89 versus MCC≃0.29 and F1-score≃0.50). TSSPlant is available to download as a standalone program at http://www.cbrc.kaust.edu.sa/download/.en
dc.description.sponsorshipKing Abdullah University of Science and Technology (KAUST) Office of Sponsored Research (OSR) [URF/1/1976-02, FCS/1/2448-01]; Science Development Foundation under the President of the Republic of Azerbaijan [Grant EİF-2010-1(1)-40/27-3]. Funding for open access charge: King Abdullah University of Science and Technology (Awards No URF/1/1976-02 and FCS/1/2448-01).en
dc.publisherOxford University Press (OUP)en
dc.relation.urlhttps://academic.oup.com/nar/article/doi/10.1093/nar/gkw1353/2900189/TSSPlant-a-new-tool-for-prediction-of-plant-Pol-IIen
dc.rightsThis is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.comen
dc.rights.urihttp://creativecommons.org/licenses/by-nc/4.0/en
dc.titleTSSPlant: a new tool for prediction of plant Pol II promotersen
dc.typeArticleen
dc.contributor.departmentKing Abdullah University of Science and Technology, Thuwal 23955-6900, Saudi Arabia.en
dc.identifier.journalNucleic Acids Researchen
dc.eprint.versionPublisher's Version/PDFen
dc.contributor.institutionInstitue of Molecular Biology and Biotechnologies, ANAS, 2 Matbuat strasse, Baku AZ1073, Azerbaijan.en
dc.contributor.institutionSoftberry Inc., Mount Kisco, NY 10549, USA victor@softberry.com.en
kaust.authorUmarov, Ramzanen
kaust.grant.numberURF/1/1976-02en
kaust.grant.numberFCS/1/2448-01en
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