Comprehensive Analysis of the Lysine Succinylome and Protein Co-modifications in Developing Rice Seeds
Comprehensive Analysis of the Lysine Succinylome and Protein Co-modifications in Developing Rice Seeds is a research paper published in Molecular & Cellular Proteomics (2019). On theSindex it has a DataRank of 1.4. It has been cited 53 times, with 39 citing works in its 1-hop citation network.
›Data sources & pipeline
FAIR Checklist
Context only (not used in score)- Has DOI
- Indexed in repositories
- DataCite relations
- Linked datasets
FAIR checklist signals are shown for context only and do not affect DataRank scoring.
DataRank Breakdown
Base Score Contribution
0.598
From this paper's citation signal
Citation Network Contribution
0.806
From 27 citing papers with measurable signal
Top 5 citers driving the network score
Ranked by citation count — the same ordering the engine uses when summing log1p(Cq) over citers.
- Identification of lysine succinylation as a new post-translational modificationNature Chemical Biology20111,037 citationsDataRank 14.7
- Lysine Succinylation Is a Frequently Occurring Modification in Prokaryotes and Eukaryotes and Extensively Overlaps with AcetylationCell Reports2013769 citationsDataRank 12.7
- Lysine Succinylation and Lysine Malonylation in HistonesMolecular & Cellular Proteomics2012609 citationsDataRank 12.9
- Identification of Lysine Succinylation Substrates and the Succinylation Regulatory Enzyme CobB in Escherichia coliMolecular & Cellular Proteomics2013286 citationsDataRank 10.3
- Global Analysis of Protein Lysine Succinylation Profiles and Their Overlap with Lysine Acetylation in the Marine Bacterium <i>Vibrio parahemolyticus</i>Journal of Proteome Research201598 citationsDataRank 4.7
Why this DataRank?
DataRank blends this paper's own citation count with the influence of the papers that cite it. Here, roughly 43% comes from its base citations and 57% from the citation network (27 citing papers contributed measurable signal).
- Base score B(p)
- log1p(citation_count) — grows sub-linearly, so a paper with 1,000 citations is not 10× a paper with 100.
- Network N(p)
- Σ over citers of log1p(Cq) ÷ max(outdegreeq, 1). Being cited by a highly-cited paper with few references counts most.
- Damping factor d = 0.85
- DataRank = (1−d)·B(p) + d·N(p) — the two cards above are each already multiplied by their share.
- Self-citations excluded
- Citers sharing any OpenAlex author ID with this paper are filtered out before the network sum.
Citers are pulled from OpenAlex sorted by cited_by_count:descand capped per paper, so when the cap binds we keep the highest-signal references and the score is reproducible across reruns.
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