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ZENODO
Dataset . 2026
License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2026
License: CC BY
Data sources: Datacite
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Prediction results for: "ELE: Estimating tissue-specific lncRNA gene essentiality using graph neural networks"

Authors: Shi, Wan-Ting; Liu, Yin-Dong; Gong, Xiu-Jun; Du, Pu-Feng;

Prediction results for: "ELE: Estimating tissue-specific lncRNA gene essentiality using graph neural networks"

Abstract

This dataset contains the prediction results reported in the paper “ELE: Estimating tissue-specific lncRNA gene essentiality using graph neural networks”. The files include model-predicted essential lncRNA genes and non-essential lncRNA genes from three human tissues and three mouse tissues, as well as common essential lncRNA genes shared across the three tissues within each species. The dataset is provided to support transparency and reproducibility of the reported results. File format: Microsoft Excel (.xlsx). Related article: ELE: Estimating tissue-specific lncRNA gene essentiality using graph neural networks

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Keywords

tissue-specific essential gene, lncRNA gene

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average