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Web tools to perform long non-coding RNAs analysis in oncology research
Accumulated evidence suggests that the widely expressed long-non-coding RNAs (lncRNAs) are involved in biogenesis. Some aberrant lncRNAs are closely related to pathological changes, for instance, in cancer. Both in tumorigenesis and cancer progression, depending on the interplay with cellular molecu...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8299716/ https://www.ncbi.nlm.nih.gov/pubmed/34296748 http://dx.doi.org/10.1093/database/baab047 |
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author | Gu, Shixing Zhang, Guangjie Si, Qin Dai, Jiawen Song, Zhen Wang, Yingshuang |
author_facet | Gu, Shixing Zhang, Guangjie Si, Qin Dai, Jiawen Song, Zhen Wang, Yingshuang |
author_sort | Gu, Shixing |
collection | PubMed |
description | Accumulated evidence suggests that the widely expressed long-non-coding RNAs (lncRNAs) are involved in biogenesis. Some aberrant lncRNAs are closely related to pathological changes, for instance, in cancer. Both in tumorigenesis and cancer progression, depending on the interplay with cellular molecules, lncRNAs can modulate transcriptional interference, chromatin remodeling, post-translational regulation and protein modification, and further interfere with signaling pathways. Aiming to the diagnosis/ prognosis markers or potential therapeutical targets, it is important to figure out the specific mechanism and the tissue-specific expressing patterns of lncRNAs. Generally, the bioinformatics analysis is the first step. More and more in silico databases are increasing. But the existing integrative online platforms’ functions are not only having their unique features but also share some common features, which may lead to a waste of time for researchers. Here, we reviewed these web tools according to the functions. For each database, we clarified the data source, analysis method and the evidence that the analysis result is derived from. This review also illustrated examples in practical use for a specific lncRNA by these web tools. It will provide convenience for researchers to quickly choose the appropriate bioinformatics web tools in oncology studies. |
format | Online Article Text |
id | pubmed-8299716 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-82997162021-07-26 Web tools to perform long non-coding RNAs analysis in oncology research Gu, Shixing Zhang, Guangjie Si, Qin Dai, Jiawen Song, Zhen Wang, Yingshuang Database (Oxford) Review Accumulated evidence suggests that the widely expressed long-non-coding RNAs (lncRNAs) are involved in biogenesis. Some aberrant lncRNAs are closely related to pathological changes, for instance, in cancer. Both in tumorigenesis and cancer progression, depending on the interplay with cellular molecules, lncRNAs can modulate transcriptional interference, chromatin remodeling, post-translational regulation and protein modification, and further interfere with signaling pathways. Aiming to the diagnosis/ prognosis markers or potential therapeutical targets, it is important to figure out the specific mechanism and the tissue-specific expressing patterns of lncRNAs. Generally, the bioinformatics analysis is the first step. More and more in silico databases are increasing. But the existing integrative online platforms’ functions are not only having their unique features but also share some common features, which may lead to a waste of time for researchers. Here, we reviewed these web tools according to the functions. For each database, we clarified the data source, analysis method and the evidence that the analysis result is derived from. This review also illustrated examples in practical use for a specific lncRNA by these web tools. It will provide convenience for researchers to quickly choose the appropriate bioinformatics web tools in oncology studies. Oxford University Press 2021-07-23 /pmc/articles/PMC8299716/ /pubmed/34296748 http://dx.doi.org/10.1093/database/baab047 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 | Review Gu, Shixing Zhang, Guangjie Si, Qin Dai, Jiawen Song, Zhen Wang, Yingshuang Web tools to perform long non-coding RNAs analysis in oncology research |
title | Web tools to perform long non-coding RNAs analysis in oncology research |
title_full | Web tools to perform long non-coding RNAs analysis in oncology research |
title_fullStr | Web tools to perform long non-coding RNAs analysis in oncology research |
title_full_unstemmed | Web tools to perform long non-coding RNAs analysis in oncology research |
title_short | Web tools to perform long non-coding RNAs analysis in oncology research |
title_sort | web tools to perform long non-coding rnas analysis in oncology research |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8299716/ https://www.ncbi.nlm.nih.gov/pubmed/34296748 http://dx.doi.org/10.1093/database/baab047 |
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