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miRNEST database: an integrative approach in microRNA search and annotation

Despite accumulating data on animal and plant microRNAs and their functions, existing public miRNA resources usually collect miRNAs from a very limited number of species. A lot of microRNAs, including those from model organisms, remain undiscovered. As a result there is a continuous need to search f...

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Autores principales: Szcześniak, Michał Wojciech, Deorowicz, Sebastian, Gapski, Jakub, Kaczyński, Łukasz, Makałowska, Izabela
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3245016/
https://www.ncbi.nlm.nih.gov/pubmed/22135287
http://dx.doi.org/10.1093/nar/gkr1159
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author Szcześniak, Michał Wojciech
Deorowicz, Sebastian
Gapski, Jakub
Kaczyński, Łukasz
Makałowska, Izabela
author_facet Szcześniak, Michał Wojciech
Deorowicz, Sebastian
Gapski, Jakub
Kaczyński, Łukasz
Makałowska, Izabela
author_sort Szcześniak, Michał Wojciech
collection PubMed
description Despite accumulating data on animal and plant microRNAs and their functions, existing public miRNA resources usually collect miRNAs from a very limited number of species. A lot of microRNAs, including those from model organisms, remain undiscovered. As a result there is a continuous need to search for new microRNAs. We present miRNEST (http://mirnest.amu.edu.pl), a comprehensive database of animal, plant and virus microRNAs. The core part of the database is built from our miRNA predictions conducted on Expressed Sequence Tags of 225 animal and 202 plant species. The miRNA search was performed based on sequence similarity and as many as 10 004 miRNA candidates in 221 animal and 199 plant species were discovered. Out of them only 299 have already been deposited in miRBase. Additionally, miRNEST has been integrated with external miRNA data from literature and 13 databases, which includes miRNA sequences, small RNA sequencing data, expression, polymorphisms and targets data as well as links to external miRNA resources, whenever applicable. All this makes miRNEST a considerable miRNA resource in a sense of number of species (544) that integrates a scattered miRNA data into a uniform format with a user-friendly web interface.
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spelling pubmed-32450162012-01-10 miRNEST database: an integrative approach in microRNA search and annotation Szcześniak, Michał Wojciech Deorowicz, Sebastian Gapski, Jakub Kaczyński, Łukasz Makałowska, Izabela Nucleic Acids Res Articles Despite accumulating data on animal and plant microRNAs and their functions, existing public miRNA resources usually collect miRNAs from a very limited number of species. A lot of microRNAs, including those from model organisms, remain undiscovered. As a result there is a continuous need to search for new microRNAs. We present miRNEST (http://mirnest.amu.edu.pl), a comprehensive database of animal, plant and virus microRNAs. The core part of the database is built from our miRNA predictions conducted on Expressed Sequence Tags of 225 animal and 202 plant species. The miRNA search was performed based on sequence similarity and as many as 10 004 miRNA candidates in 221 animal and 199 plant species were discovered. Out of them only 299 have already been deposited in miRBase. Additionally, miRNEST has been integrated with external miRNA data from literature and 13 databases, which includes miRNA sequences, small RNA sequencing data, expression, polymorphisms and targets data as well as links to external miRNA resources, whenever applicable. All this makes miRNEST a considerable miRNA resource in a sense of number of species (544) that integrates a scattered miRNA data into a uniform format with a user-friendly web interface. Oxford University Press 2012-01 2011-11-30 /pmc/articles/PMC3245016/ /pubmed/22135287 http://dx.doi.org/10.1093/nar/gkr1159 Text en © The Author(s) 2011. Published by Oxford University Press. http://creativecommons.org/licenses/by-nc/3.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Articles
Szcześniak, Michał Wojciech
Deorowicz, Sebastian
Gapski, Jakub
Kaczyński, Łukasz
Makałowska, Izabela
miRNEST database: an integrative approach in microRNA search and annotation
title miRNEST database: an integrative approach in microRNA search and annotation
title_full miRNEST database: an integrative approach in microRNA search and annotation
title_fullStr miRNEST database: an integrative approach in microRNA search and annotation
title_full_unstemmed miRNEST database: an integrative approach in microRNA search and annotation
title_short miRNEST database: an integrative approach in microRNA search and annotation
title_sort mirnest database: an integrative approach in microrna search and annotation
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3245016/
https://www.ncbi.nlm.nih.gov/pubmed/22135287
http://dx.doi.org/10.1093/nar/gkr1159
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