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LncRNA-miRNA interaction prediction through sequence-derived linear neighborhood propagation method with information combination

BACKGROUND: Researchers discover lncRNAs can act as decoys or sponges to regulate the behavior of miRNAs. Identification of lncRNA-miRNA interactions helps to understand the functions of lncRNAs, especially their roles in complicated diseases. Computational methods can save time and reduce cost in i...

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Detalles Bibliográficos
Autores principales: Zhang, Wen, Tang, Guifeng, Zhou, Shuang, Niu, Yanqing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6923828/
https://www.ncbi.nlm.nih.gov/pubmed/31856716
http://dx.doi.org/10.1186/s12864-019-6284-y
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author Zhang, Wen
Tang, Guifeng
Zhou, Shuang
Niu, Yanqing
author_facet Zhang, Wen
Tang, Guifeng
Zhou, Shuang
Niu, Yanqing
author_sort Zhang, Wen
collection PubMed
description BACKGROUND: Researchers discover lncRNAs can act as decoys or sponges to regulate the behavior of miRNAs. Identification of lncRNA-miRNA interactions helps to understand the functions of lncRNAs, especially their roles in complicated diseases. Computational methods can save time and reduce cost in identifying lncRNA-miRNA interactions, but there have been only a few computational methods. RESULTS: In this paper, we propose a sequence-derived linear neighborhood propagation method (SLNPM) to predict lncRNA-miRNA interactions. First, we calculate the integrated lncRNA-lncRNA similarity and the integrated miRNA-miRNA similarity by combining known lncRNA-miRNA interactions, lncRNA sequences and miRNA sequences. We consider two similarity calculation strategies respectively, namely similarity-based information combination (SC) and interaction profile-based information combination (PC). Second, the integrated lncRNA similarity-based graph and the integrated miRNA similarity-based graph are respectively constructed, and the label propagation processes are implemented on two graphs to score lncRNA-miRNA pairs. Finally, the weighted averages of their outputs are adopted as final predictions. Therefore, we construct two editions of SLNPM: sequence-derived linear neighborhood propagation method based on similarity information combination (SLNPM-SC) and sequence-derived linear neighborhood propagation method based on interaction profile information combination (SLNPM-PC). The experimental results show that SLNPM-SC and SLNPM-PC predict lncRNA-miRNA interactions with higher accuracy compared with other state-of-the-art methods. The case studies demonstrate that SLNPM-SC and SLNPM-PC help to find novel lncRNA-miRNA interactions for given lncRNAs or miRNAs. CONCLUSION: The study reveals that known interactions bring the most important information for lncRNA-miRNA interaction prediction, and sequences of lncRNAs (miRNAs) also provide useful information. In conclusion, SLNPM-SC and SLNPM-PC are promising for lncRNA-miRNA interaction prediction.
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spelling pubmed-69238282019-12-30 LncRNA-miRNA interaction prediction through sequence-derived linear neighborhood propagation method with information combination Zhang, Wen Tang, Guifeng Zhou, Shuang Niu, Yanqing BMC Genomics Research BACKGROUND: Researchers discover lncRNAs can act as decoys or sponges to regulate the behavior of miRNAs. Identification of lncRNA-miRNA interactions helps to understand the functions of lncRNAs, especially their roles in complicated diseases. Computational methods can save time and reduce cost in identifying lncRNA-miRNA interactions, but there have been only a few computational methods. RESULTS: In this paper, we propose a sequence-derived linear neighborhood propagation method (SLNPM) to predict lncRNA-miRNA interactions. First, we calculate the integrated lncRNA-lncRNA similarity and the integrated miRNA-miRNA similarity by combining known lncRNA-miRNA interactions, lncRNA sequences and miRNA sequences. We consider two similarity calculation strategies respectively, namely similarity-based information combination (SC) and interaction profile-based information combination (PC). Second, the integrated lncRNA similarity-based graph and the integrated miRNA similarity-based graph are respectively constructed, and the label propagation processes are implemented on two graphs to score lncRNA-miRNA pairs. Finally, the weighted averages of their outputs are adopted as final predictions. Therefore, we construct two editions of SLNPM: sequence-derived linear neighborhood propagation method based on similarity information combination (SLNPM-SC) and sequence-derived linear neighborhood propagation method based on interaction profile information combination (SLNPM-PC). The experimental results show that SLNPM-SC and SLNPM-PC predict lncRNA-miRNA interactions with higher accuracy compared with other state-of-the-art methods. The case studies demonstrate that SLNPM-SC and SLNPM-PC help to find novel lncRNA-miRNA interactions for given lncRNAs or miRNAs. CONCLUSION: The study reveals that known interactions bring the most important information for lncRNA-miRNA interaction prediction, and sequences of lncRNAs (miRNAs) also provide useful information. In conclusion, SLNPM-SC and SLNPM-PC are promising for lncRNA-miRNA interaction prediction. BioMed Central 2019-12-20 /pmc/articles/PMC6923828/ /pubmed/31856716 http://dx.doi.org/10.1186/s12864-019-6284-y Text en © The Author(s). 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Zhang, Wen
Tang, Guifeng
Zhou, Shuang
Niu, Yanqing
LncRNA-miRNA interaction prediction through sequence-derived linear neighborhood propagation method with information combination
title LncRNA-miRNA interaction prediction through sequence-derived linear neighborhood propagation method with information combination
title_full LncRNA-miRNA interaction prediction through sequence-derived linear neighborhood propagation method with information combination
title_fullStr LncRNA-miRNA interaction prediction through sequence-derived linear neighborhood propagation method with information combination
title_full_unstemmed LncRNA-miRNA interaction prediction through sequence-derived linear neighborhood propagation method with information combination
title_short LncRNA-miRNA interaction prediction through sequence-derived linear neighborhood propagation method with information combination
title_sort lncrna-mirna interaction prediction through sequence-derived linear neighborhood propagation method with information combination
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6923828/
https://www.ncbi.nlm.nih.gov/pubmed/31856716
http://dx.doi.org/10.1186/s12864-019-6284-y
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AT zhoushuang lncrnamirnainteractionpredictionthroughsequencederivedlinearneighborhoodpropagationmethodwithinformationcombination
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