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DIANA-microT 2023: including predicted targets of virally encoded miRNAs

DIANA-microT-CDS is a state-of-the-art miRNA target prediction algorithm catering the scientific community since 2009. It is one of the first algorithms to predict miRNA binding sites in both the 3′ Untranslated Region (3′-UTR) and the coding sequence (CDS) of transcripts, with increased performance...

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Autores principales: Tastsoglou, Spyros, Alexiou, Athanasios, Karagkouni, Dimitra, Skoufos, Giorgos, Zacharopoulou, Elissavet, Hatzigeorgiou, Artemis G
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10320106/
https://www.ncbi.nlm.nih.gov/pubmed/37094027
http://dx.doi.org/10.1093/nar/gkad283
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author Tastsoglou, Spyros
Alexiou, Athanasios
Karagkouni, Dimitra
Skoufos, Giorgos
Zacharopoulou, Elissavet
Hatzigeorgiou, Artemis G
author_facet Tastsoglou, Spyros
Alexiou, Athanasios
Karagkouni, Dimitra
Skoufos, Giorgos
Zacharopoulou, Elissavet
Hatzigeorgiou, Artemis G
author_sort Tastsoglou, Spyros
collection PubMed
description DIANA-microT-CDS is a state-of-the-art miRNA target prediction algorithm catering the scientific community since 2009. It is one of the first algorithms to predict miRNA binding sites in both the 3′ Untranslated Region (3′-UTR) and the coding sequence (CDS) of transcripts, with increased performance. Its current version, DIANA-microT 2023 (www.microrna.gr/microt_webserver/), brings forward a significantly updated set of interactions. DIANA-microT-CDS has been executed utilizing annotation information from Ensembl v102, miRBase 22.1 and, for the first time, MirGeneDB 2.1, yielding more than 83 million interactions in human, mouse, rat, chicken, fly and worm species. Additionally, this version delivers predicted interactions of miRNAs encoded from 20 viruses against host transcripts from human, mouse and chicken species. Numerous resources have been interconnected into DIANA-microT, including DIANA-TarBase, plasmiR, HMDD, UCSC, dbSNP, ClinVar, as well as miRNA/gene abundance values for 369 distinct cell-lines/tissues. The server interface has been redesigned allowing users to use smart filtering options, identify abundance patterns of interest, pinpoint known SNPs residing on binding sites and obtain miRNA-disease information. The contents of DIANA-microT webserver are freely accessible and can also be locally downloaded without any login requirements.
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spelling pubmed-103201062023-07-06 DIANA-microT 2023: including predicted targets of virally encoded miRNAs Tastsoglou, Spyros Alexiou, Athanasios Karagkouni, Dimitra Skoufos, Giorgos Zacharopoulou, Elissavet Hatzigeorgiou, Artemis G Nucleic Acids Res Web Server Issue DIANA-microT-CDS is a state-of-the-art miRNA target prediction algorithm catering the scientific community since 2009. It is one of the first algorithms to predict miRNA binding sites in both the 3′ Untranslated Region (3′-UTR) and the coding sequence (CDS) of transcripts, with increased performance. Its current version, DIANA-microT 2023 (www.microrna.gr/microt_webserver/), brings forward a significantly updated set of interactions. DIANA-microT-CDS has been executed utilizing annotation information from Ensembl v102, miRBase 22.1 and, for the first time, MirGeneDB 2.1, yielding more than 83 million interactions in human, mouse, rat, chicken, fly and worm species. Additionally, this version delivers predicted interactions of miRNAs encoded from 20 viruses against host transcripts from human, mouse and chicken species. Numerous resources have been interconnected into DIANA-microT, including DIANA-TarBase, plasmiR, HMDD, UCSC, dbSNP, ClinVar, as well as miRNA/gene abundance values for 369 distinct cell-lines/tissues. The server interface has been redesigned allowing users to use smart filtering options, identify abundance patterns of interest, pinpoint known SNPs residing on binding sites and obtain miRNA-disease information. The contents of DIANA-microT webserver are freely accessible and can also be locally downloaded without any login requirements. Oxford University Press 2023-04-24 /pmc/articles/PMC10320106/ /pubmed/37094027 http://dx.doi.org/10.1093/nar/gkad283 Text en © The Author(s) 2023. Published by Oxford University Press on behalf of Nucleic Acids Research. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Web Server Issue
Tastsoglou, Spyros
Alexiou, Athanasios
Karagkouni, Dimitra
Skoufos, Giorgos
Zacharopoulou, Elissavet
Hatzigeorgiou, Artemis G
DIANA-microT 2023: including predicted targets of virally encoded miRNAs
title DIANA-microT 2023: including predicted targets of virally encoded miRNAs
title_full DIANA-microT 2023: including predicted targets of virally encoded miRNAs
title_fullStr DIANA-microT 2023: including predicted targets of virally encoded miRNAs
title_full_unstemmed DIANA-microT 2023: including predicted targets of virally encoded miRNAs
title_short DIANA-microT 2023: including predicted targets of virally encoded miRNAs
title_sort diana-microt 2023: including predicted targets of virally encoded mirnas
topic Web Server Issue
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10320106/
https://www.ncbi.nlm.nih.gov/pubmed/37094027
http://dx.doi.org/10.1093/nar/gkad283
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