The importance of residue‐level filtering and the Top2018 best‐parts dataset of high‐quality protein residues
The importance of residue‐level filtering and the Top2018 best‐parts dataset of high‐quality protein residues is a dataset published in Protein Science (2021). On theSindex it has a DataRank of 0.795, placing it in the top 25.3% of the data-sharing corpus. It has been cited 18 times, with 14 citing works in its 1-hop citation network.
Ranks in the top 25% for downstream scientific impact
DataRank reads this dataset's downstream impact straight off the citation graph — no black box, no proprietary weighting. How is this computed?
›Methodology & internals
FAIR Checklist
Context only (not used in score)- Has DOI
- Open Access
- Dataset classification
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.
DataRank Breakdown
Base Score Contribution
0.442
From this paper's citation signal
Citation Network Contribution
0.353
From 11 citing papers with measurable signal
Top 5 citers driving the network score
Ranked by each citer's contribution to N(p) — log1p(Cq) divided by its reference count — out of 14 citers.
- RamPlot: a webserver to draw 2D, 3D and assorted Ramachandran (φ, ψ) mapsJournal of Applied Crystallography202542 citations40 referencesContributes 0.094
- ATLAS: protein flexibility description from atomistic molecular dynamics simulationsNucleic Acids Research2023121 citations71 referencesContributes 0.068
- Designing microplate layouts using artificial intelligenceArtificial Intelligence in the Life Sciences202315 citations52 referencesContributes 0.053
- Physics-Grounded Evaluation to Guide Accurate Biomolecular PredictionbioRxiv (Cold Spring Harbor Laboratory)20258 citations55 referencesContributes 0.040
- Invariant point message passing for protein side chain packingProteins Structure Function and Bioinformatics202410 citations68 referencesContributes 0.035