Inferring protein sequence-function relationships with large-scale positive-unlabeled learning is a research paper published in bioRxiv (Cold Spring Harbor Laboratory) (2020). On theSindex it has a DataRank of 0.330. It has been cited 8 times.
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
0.330
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 →National Science Foundation
Grant: 1811767
Estimation, inference and testing for large-scale directed network models
National Institutes of Health
Grant: 5R35GM119854-02
Data-driven analysis of protein structure, function, and regulation
National Institutes of Health
Grant: 5R01GM131381-03
Novel Methods for Large Scale Presence only Data in Biological Systems Engineering
Influential Citations
2
Citation Trend
Fields of Study
Keywords