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LnCeCell: a comprehensive database of predicted lncRNA-associated ceRNA networks at single-cell resolution

Within the tumour microenvironment, cells exhibit different behaviours driven by fine-tuning of gene regulation. Identification of cellular-specific gene regulatory networks will deepen the understanding of disease pathology at single-cell resolution and contribute to the development of precision me...

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Autores principales: Wang, Peng, Guo, Qiuyan, Hao, Yangyang, Liu, Qian, Gao, Yue, Zhi, Hui, Li, Xin, Shang, Shipeng, Guo, Shuang, Zhang, Yunpeng, Ning, Shangwei, Li, Xia
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7778920/
https://www.ncbi.nlm.nih.gov/pubmed/33219686
http://dx.doi.org/10.1093/nar/gkaa1017
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author Wang, Peng
Guo, Qiuyan
Hao, Yangyang
Liu, Qian
Gao, Yue
Zhi, Hui
Li, Xin
Shang, Shipeng
Guo, Shuang
Zhang, Yunpeng
Ning, Shangwei
Li, Xia
author_facet Wang, Peng
Guo, Qiuyan
Hao, Yangyang
Liu, Qian
Gao, Yue
Zhi, Hui
Li, Xin
Shang, Shipeng
Guo, Shuang
Zhang, Yunpeng
Ning, Shangwei
Li, Xia
author_sort Wang, Peng
collection PubMed
description Within the tumour microenvironment, cells exhibit different behaviours driven by fine-tuning of gene regulation. Identification of cellular-specific gene regulatory networks will deepen the understanding of disease pathology at single-cell resolution and contribute to the development of precision medicine. Here, we describe a database, LnCeCell (http://www.bio-bigdata.net/LnCeCell/ or http://bio-bigdata.hrbmu.edu.cn/LnCeCell/), which aims to document cellular-specific long non-coding RNA (lncRNA)-associated competing endogenous RNA (ceRNA) networks for personalised characterisation of diseases based on the ‘One Cell, One World’ theory. LnCeCell is curated with cellular-specific ceRNA regulations from >94 000 cells across 25 types of cancers and provides >9000 experimentally supported lncRNA biomarkers, associated with tumour metastasis, recurrence, prognosis, circulation, drug resistance, etc. For each cell, LnCeCell illustrates a global map of ceRNA sub-cellular locations, which have been manually curated from the literature and related data sources, and portrays a functional state atlas for a single cancer cell. LnCeCell also provides several flexible tools to infer ceRNA functions based on a specific cellular background. LnCeCell serves as an important resource for investigating the gene regulatory networks within a single cell and can help researchers understand the regulatory mechanisms underlying complex microbial ecosystems and individual phenotypes.
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spelling pubmed-77789202021-01-06 LnCeCell: a comprehensive database of predicted lncRNA-associated ceRNA networks at single-cell resolution Wang, Peng Guo, Qiuyan Hao, Yangyang Liu, Qian Gao, Yue Zhi, Hui Li, Xin Shang, Shipeng Guo, Shuang Zhang, Yunpeng Ning, Shangwei Li, Xia Nucleic Acids Res Database Issue Within the tumour microenvironment, cells exhibit different behaviours driven by fine-tuning of gene regulation. Identification of cellular-specific gene regulatory networks will deepen the understanding of disease pathology at single-cell resolution and contribute to the development of precision medicine. Here, we describe a database, LnCeCell (http://www.bio-bigdata.net/LnCeCell/ or http://bio-bigdata.hrbmu.edu.cn/LnCeCell/), which aims to document cellular-specific long non-coding RNA (lncRNA)-associated competing endogenous RNA (ceRNA) networks for personalised characterisation of diseases based on the ‘One Cell, One World’ theory. LnCeCell is curated with cellular-specific ceRNA regulations from >94 000 cells across 25 types of cancers and provides >9000 experimentally supported lncRNA biomarkers, associated with tumour metastasis, recurrence, prognosis, circulation, drug resistance, etc. For each cell, LnCeCell illustrates a global map of ceRNA sub-cellular locations, which have been manually curated from the literature and related data sources, and portrays a functional state atlas for a single cancer cell. LnCeCell also provides several flexible tools to infer ceRNA functions based on a specific cellular background. LnCeCell serves as an important resource for investigating the gene regulatory networks within a single cell and can help researchers understand the regulatory mechanisms underlying complex microbial ecosystems and individual phenotypes. Oxford University Press 2020-11-21 /pmc/articles/PMC7778920/ /pubmed/33219686 http://dx.doi.org/10.1093/nar/gkaa1017 Text en © The Author(s) 2020. Published by Oxford University Press on behalf of Nucleic Acids Research. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Database Issue
Wang, Peng
Guo, Qiuyan
Hao, Yangyang
Liu, Qian
Gao, Yue
Zhi, Hui
Li, Xin
Shang, Shipeng
Guo, Shuang
Zhang, Yunpeng
Ning, Shangwei
Li, Xia
LnCeCell: a comprehensive database of predicted lncRNA-associated ceRNA networks at single-cell resolution
title LnCeCell: a comprehensive database of predicted lncRNA-associated ceRNA networks at single-cell resolution
title_full LnCeCell: a comprehensive database of predicted lncRNA-associated ceRNA networks at single-cell resolution
title_fullStr LnCeCell: a comprehensive database of predicted lncRNA-associated ceRNA networks at single-cell resolution
title_full_unstemmed LnCeCell: a comprehensive database of predicted lncRNA-associated ceRNA networks at single-cell resolution
title_short LnCeCell: a comprehensive database of predicted lncRNA-associated ceRNA networks at single-cell resolution
title_sort lncecell: a comprehensive database of predicted lncrna-associated cerna networks at single-cell resolution
topic Database Issue
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7778920/
https://www.ncbi.nlm.nih.gov/pubmed/33219686
http://dx.doi.org/10.1093/nar/gkaa1017
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