gRNAde: Geometric Deep Learning for 3D RNA inverse design is a research paper published in bioRxiv (Cold Spring Harbor Laboratory) (2024). On theSindex it has a DataRank of 0.696. It has been cited 22 times, with 21 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
0.470
From this paper's citation signal
Citation Network Contribution
0.225
From 13 citing papers with measurable signal
Ranked by each citer's contribution to N(p) — log1p(Cq) divided by its reference count — out of 21 citers.
National Institutes of Health
Grant: 5R01GM093123-10
Distance-based ab initio protein structure prediction
National Institutes of Health
Grant: 5R01GM146340-03
Deep learning methods for automated and accurate reconstruction of protein structures from cryo-EM image data
UK Research and Innovation
Grant: EP/S022961/1
UKRI Centre for Doctoral Training in Application of Artificial Intelligence to the study of Environmental Risks (AI4ER)
National Science Foundation
Grant: 2308699
Deep transformers for integrating protein sequence, structure and interaction data to predict function
Fields of Study
Keywords