Variational autoencoders learn transferrable representations of metabolomics data is a research paper published in Communications Biology (2022). On theSindex it has a DataRank of 1.4. It has been cited 54 times, with 53 citing works in its 1-hop citation network.
Scored on demand from live citation data
Linked data & code
DataRank reads this dataset's downstream impact straight off the citation graph — no black box, no proprietary weighting. How is this computed?
FAIR checklist signals are shown for context only and do not affect DataRank scoring.
We only score data papers we can read in full — never from an abstract alone.
Base Score Contribution
0.601
From this paper's citation signal
Citation Network Contribution
0.799
From 37 citing papers with measurable signal
Ranked by each citer's contribution to N(p) — log1p(Cq) divided by its reference count — out of 53 citers.
NIA NIH HHS
Grant: U19 AG063744
NCI NIH HHS
Grant: UG1 CA189859
NCI NIH HHS
Grant: U10 CA180820
NCI NIH HHS
Grant: U24 CA196172
National Institutes of Health
Grant: 5U19AG063744-02
Alzheimer's Gut Microbiome Project
National Institutes of Health
Grant: 5UG1CA189859-03
Minority-Based Community Oncology Research Program
National Institutes of Health
Grant: 3U10CA180820-02S3
ECOG-ACRIN Operations Center
Wellcome Trust
Grant: unidentified
unidentified
Medical Research Council
National Institute for Health Research (NIHR)
Wellcome Trust
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