SELER: A database of super-enhancer-associated lncRNA-directed transcriptional regulation in human cancers
Database, ISSN: 1758-0463, Vol: 2019, Issue: 1
2019
- 19Citations
- 17Captures
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Metrics Details
- Citations19
- Citation Indexes19
- 19
- Captures17
- Readers17
- 17
Article Description
Super-enhancers (SEs) are enriched with a cluster of mediator binding sites, which are major contributors to cell-type-specific gene expression. Currently, a large quantity of long non-coding RNAs has been found to be transcribed from or to interact with SEs, which constitute super-enhancer associated long non-coding RNAs (SE-lncRNAs). These SE-lncRNAs play essential roles in transcriptional regulation through controlling SEs activity to regulate a broad range of physiological and pathological processes, especially tumorigenesis. However, the pathological functions of SE-lncRNAs in tumorigenesis are still obscure. In this paper, we characterized 5056 SE-lncRNAs and their associated genes by analysing 102 SE data sets. Then, we analysed their expression profiles and prognostic information derived from 19 cancer types to identify cancer-related SE-lncRNAs and to explore their potential functions. In total, 436 significantly differentially expressed SE-lncRNAs and 2035 SE-lncRNAs with high prognostic values were identified. Additionally, 3935 significant correlations between SE-lncRNAs and their regulatory genes were further validated by calculating their correlation coefficients in each cancer type. Finally, the SELER database incorporating the aforementioned data was provided for users to explore their physiological and pathological functions to comprehensively understand the blocks of living systems.
Bibliographic Details
Oxford University Press (OUP)
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