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emiRIT: a text-mining-based resource for microRNA information

microRNAs (miRNAs) are essential gene regulators, and their dysregulation often leads to diseases. Easy access to miRNA information is crucial for interpreting generated experimental data, connecting facts across publications and developing new hypotheses built on previous knowledge. Here, we presen...

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Autores principales: Roychowdhury, Debarati, Gupta, Samir, Qin, Xihan, Arighi, Cecilia N, Vijay-Shanker, K
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8163238/
https://www.ncbi.nlm.nih.gov/pubmed/34048547
http://dx.doi.org/10.1093/database/baab031
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author Roychowdhury, Debarati
Gupta, Samir
Qin, Xihan
Arighi, Cecilia N
Vijay-Shanker, K
author_facet Roychowdhury, Debarati
Gupta, Samir
Qin, Xihan
Arighi, Cecilia N
Vijay-Shanker, K
author_sort Roychowdhury, Debarati
collection PubMed
description microRNAs (miRNAs) are essential gene regulators, and their dysregulation often leads to diseases. Easy access to miRNA information is crucial for interpreting generated experimental data, connecting facts across publications and developing new hypotheses built on previous knowledge. Here, we present extracting miRNA Information from Text (emiRIT), a text-miningbased resource, which presents miRNA information mined from the literature through a user-friendly interface. We collected 149 ,233 miRNA –PubMed ID pairs from Medline between January 1997 and May 2020. emiRIT currently contains ‘miRNA –gene regulation’ (69 ,152 relations), ‘miRNA disease (cancer)’ (12 ,300 relations), ‘miRNA –biological process and pathways’ (23, 390 relations) and circulatory ‘miRNAs in extracellular locations’ (3782 relations). Biological entities and their relation to miRNAs were extracted from Medline abstracts using publicly available and in-house developed text-mining tools, and the entities were normalized to facilitate querying and integration. We built a database and an interface to store and access the integrated data, respectively. We provide an up-to-date and user-friendly resource to facilitate access to comprehensive miRNA information from the literature on a large scale, enabling users to navigate through different roles of miRNA and examine them in a context specific to their information needs. To assess our resource’s information coverage, we have conducted two case studies focusing on the target and differential expression information of miRNAs in the context of cancer and a third case study to assess the usage of emiRIT in the curation of miRNA information. Database URL: https://research.bioinformatics.udel.edu/emirit/
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spelling pubmed-81632382021-06-02 emiRIT: a text-mining-based resource for microRNA information Roychowdhury, Debarati Gupta, Samir Qin, Xihan Arighi, Cecilia N Vijay-Shanker, K Database (Oxford) Original Article microRNAs (miRNAs) are essential gene regulators, and their dysregulation often leads to diseases. Easy access to miRNA information is crucial for interpreting generated experimental data, connecting facts across publications and developing new hypotheses built on previous knowledge. Here, we present extracting miRNA Information from Text (emiRIT), a text-miningbased resource, which presents miRNA information mined from the literature through a user-friendly interface. We collected 149 ,233 miRNA –PubMed ID pairs from Medline between January 1997 and May 2020. emiRIT currently contains ‘miRNA –gene regulation’ (69 ,152 relations), ‘miRNA disease (cancer)’ (12 ,300 relations), ‘miRNA –biological process and pathways’ (23, 390 relations) and circulatory ‘miRNAs in extracellular locations’ (3782 relations). Biological entities and their relation to miRNAs were extracted from Medline abstracts using publicly available and in-house developed text-mining tools, and the entities were normalized to facilitate querying and integration. We built a database and an interface to store and access the integrated data, respectively. We provide an up-to-date and user-friendly resource to facilitate access to comprehensive miRNA information from the literature on a large scale, enabling users to navigate through different roles of miRNA and examine them in a context specific to their information needs. To assess our resource’s information coverage, we have conducted two case studies focusing on the target and differential expression information of miRNAs in the context of cancer and a third case study to assess the usage of emiRIT in the curation of miRNA information. Database URL: https://research.bioinformatics.udel.edu/emirit/ Oxford University Press 2021-05-28 /pmc/articles/PMC8163238/ /pubmed/34048547 http://dx.doi.org/10.1093/database/baab031 Text en © The Author(s) 2021. Published by Oxford University Press. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/ (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 Original Article
Roychowdhury, Debarati
Gupta, Samir
Qin, Xihan
Arighi, Cecilia N
Vijay-Shanker, K
emiRIT: a text-mining-based resource for microRNA information
title emiRIT: a text-mining-based resource for microRNA information
title_full emiRIT: a text-mining-based resource for microRNA information
title_fullStr emiRIT: a text-mining-based resource for microRNA information
title_full_unstemmed emiRIT: a text-mining-based resource for microRNA information
title_short emiRIT: a text-mining-based resource for microRNA information
title_sort emirit: a text-mining-based resource for microrna information
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8163238/
https://www.ncbi.nlm.nih.gov/pubmed/34048547
http://dx.doi.org/10.1093/database/baab031
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