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MicroPC (μPC): A comprehensive resource for predicting and comparing plant microRNAs

BACKGROUND: Plant microRNA (miRNA) has an important role in controlling gene regulation in various biological processes such as cell development, signal transduction, and environmental responses. While information on plant miRNAs and their targets is widely available, accessible online plant miRNA r...

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Detalles Bibliográficos
Autores principales: Mhuantong, Wuttichai, Wichadakul, Duangdao
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2009
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2907689/
https://www.ncbi.nlm.nih.gov/pubmed/19660144
http://dx.doi.org/10.1186/1471-2164-10-366
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author Mhuantong, Wuttichai
Wichadakul, Duangdao
author_facet Mhuantong, Wuttichai
Wichadakul, Duangdao
author_sort Mhuantong, Wuttichai
collection PubMed
description BACKGROUND: Plant microRNA (miRNA) has an important role in controlling gene regulation in various biological processes such as cell development, signal transduction, and environmental responses. While information on plant miRNAs and their targets is widely available, accessible online plant miRNA resources are limited; most of them are intended for economically important crops or plant model organisms. With abundant sequence data of numerous plants in public databases such as NCBI and PlantGDB, the identification of their miRNAs and targets would benefit researchers as a central resource for the comparative studies of plant miRNAs. RESULTS: MicroPC (μPC) is an online plant miRNA resource resulted from large-scale Expressed Sequence Tag (EST) analysis. It consists of 4,006 potential miRNA candidates in 128 families of 125 plant species and 2,995 proteins (4,953 EST sequences) potentially targeted by 78 families of miRNA candidates. In addition, it is incorporated with 1,727 previously reported plant mature miRNA sequences from miRBase. The μPC enables users to compare stored mature or precursor miRNAs and user-supplied sequences among plant species. The search utility allows users to investigate the predicted miRNAs and miRNA targets in detail via various search options such as miRNA family and plant species. To enhance the database usage, the prediction utility provides interactive steps for determining a miRNA or miRNA targets from an input nucleotide sequence and links the prediction results to their homologs in the μPC. CONCLUSION: The μPC constitutes the first online resource that enables users to comprehensively compare and predict plant miRNAs and their targets. It imparts a basis for further research on revealing miRNA conservation, function, and evolution across plant species and classification. The μPC is available at http://www.biotec.or.th/isl/micropc.
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spelling pubmed-29076892010-07-22 MicroPC (μPC): A comprehensive resource for predicting and comparing plant microRNAs Mhuantong, Wuttichai Wichadakul, Duangdao BMC Genomics Database BACKGROUND: Plant microRNA (miRNA) has an important role in controlling gene regulation in various biological processes such as cell development, signal transduction, and environmental responses. While information on plant miRNAs and their targets is widely available, accessible online plant miRNA resources are limited; most of them are intended for economically important crops or plant model organisms. With abundant sequence data of numerous plants in public databases such as NCBI and PlantGDB, the identification of their miRNAs and targets would benefit researchers as a central resource for the comparative studies of plant miRNAs. RESULTS: MicroPC (μPC) is an online plant miRNA resource resulted from large-scale Expressed Sequence Tag (EST) analysis. It consists of 4,006 potential miRNA candidates in 128 families of 125 plant species and 2,995 proteins (4,953 EST sequences) potentially targeted by 78 families of miRNA candidates. In addition, it is incorporated with 1,727 previously reported plant mature miRNA sequences from miRBase. The μPC enables users to compare stored mature or precursor miRNAs and user-supplied sequences among plant species. The search utility allows users to investigate the predicted miRNAs and miRNA targets in detail via various search options such as miRNA family and plant species. To enhance the database usage, the prediction utility provides interactive steps for determining a miRNA or miRNA targets from an input nucleotide sequence and links the prediction results to their homologs in the μPC. CONCLUSION: The μPC constitutes the first online resource that enables users to comprehensively compare and predict plant miRNAs and their targets. It imparts a basis for further research on revealing miRNA conservation, function, and evolution across plant species and classification. The μPC is available at http://www.biotec.or.th/isl/micropc. BioMed Central 2009-08-07 /pmc/articles/PMC2907689/ /pubmed/19660144 http://dx.doi.org/10.1186/1471-2164-10-366 Text en Copyright ©2009 Mhuantong and Wichadakul; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Database
Mhuantong, Wuttichai
Wichadakul, Duangdao
MicroPC (μPC): A comprehensive resource for predicting and comparing plant microRNAs
title MicroPC (μPC): A comprehensive resource for predicting and comparing plant microRNAs
title_full MicroPC (μPC): A comprehensive resource for predicting and comparing plant microRNAs
title_fullStr MicroPC (μPC): A comprehensive resource for predicting and comparing plant microRNAs
title_full_unstemmed MicroPC (μPC): A comprehensive resource for predicting and comparing plant microRNAs
title_short MicroPC (μPC): A comprehensive resource for predicting and comparing plant microRNAs
title_sort micropc (μpc): a comprehensive resource for predicting and comparing plant micrornas
topic Database
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2907689/
https://www.ncbi.nlm.nih.gov/pubmed/19660144
http://dx.doi.org/10.1186/1471-2164-10-366
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