Common data models to streamline metabolomics processing and annotation, and implementation in a Python pipeline is a research paper published in bioRxiv (Cold Spring Harbor Laboratory) (2024). On theSindex it has a DataRank of 0.169. It has been cited 2 times, with 1 citing works in its 1-hop citation network.
Scored on demand from live citation data
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
0.165
From this paper's citation signal
Citation Network Contribution
4.58 × 10⁻³
From 1 citing papers with measurable signal
Ranked by each citer's contribution to N(p) — log1p(Cq) divided by its reference count — out of 1 citer.
National Institutes of Health
Grant: 1U01CA235493-01
Mummichog 3, aligning mass spectrometry data to biological networks
European Commission
Grant: 235493
The Cutting Edge: Insights from biomechanical tooth studies to explore the interaction of ecological diversity and evolutionary convergence.
National Institutes of Health
Grant: 5R01AI149746-06
ImmunoMetabolomics of Zoster Vaccines
National Institutes of Health
Grant: 5UM1HG012651-04
JAX MorPhiC Data Production Center
Fields of Study
Keywords