Parameter tuning is a key part of dimensionality reduction via deep variational autoencoders for single cell RNA transcriptomics is a research paper published in Biocomputing 2019 (2018). On theSindex it has a DataRank of 0.598. It has been cited 53 times.
Scored on demand from live citation data
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DataRank reads this dataset's downstream impact straight off the citation graph — no black box, no proprietary weighting. How is this computed?
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Base Score Contribution
0.598
From this paper's citation signal
Citation Network Contribution
0
Citation network not refreshed for this result
This paper's DataRank is currently driven only by its base citation score. Citation network data was not refreshed for this result.
Learn more about DataRank methodology →NHGRI NIH HHS
Grant: R01 HG010067
National Institutes of Health
Grant: 5R01HG010067-05
Network-based algorithms for target identification and drug repositioning from genetic associations
FWCI
33.42
Citation Percentile
1.0%
Citation Trend
Fields of Study
MeSH Terms
Keywords
Sustainable Development Goals
Additional file 1 of MethylNet: an automated and modular deep learning approach for DNA methylation analysis
Additional file 1 of MethylNet: an automated and modular deep learning approach for DNA methylation analysis