🏆 Finalist — NIH Data Sharing Index (“S-Index”) Challenge
Demo corpus. Scores are computed on a select set of biomedical paper/datasets and may be inaccurate for papers outside this corpus — DataRank relies on network effects that improve with scale. We aim to expand this into a fully open resource pending additional funding.

WAF1, a potential mediator of p53 tumor suppression

Cell(1993)10.1016/0092-8674(93)90500-pSource: DataRank Database

WAF1, a potential mediator of p53 tumor suppression is a research paper published in Cell (1993). On theSindex it has a DataRank of 1.4. It has been cited 8,374 times.

N/A
1.4DataRank · unranked
1.4
8374 citations · base score 9.0
Cite:
datarank_citation_only_1hop_v6· scope data_onlyMethodology

Abstract

The ability of p53 to activate transcription from specific sequences suggests that genes induced by p53 may mediate its biological role as a tumor suppressor. Using a subtractive hybridization approach, we identified a gene, named WAF1, whose induction was associated with wild-type but not mutant p53 gene expression in a human brain tumor cell line. The WAF1 gene was localized to chromosome 6p21.2, and its sequence, structure, and activation by p53 was conserved in rodents. Introduction of WAF1 cDNA suppressed the growth of human brain, lung, and colon tumor cells in culture. Using a yeast enhancer trap, a p53-binding site was identified 2.4 kb upstream of WAF1 coding sequences. The WAF1 promoter, including this p53-binding site, conferred p53-dependent inducibility upon a heterologous reporter gene. These studies define a gene whose expression is directly induced by p53 and that could be an important mediator of p53-dependent tumor growth suppression.

Data sources & pipeline
Pipeline:MetadataData-paper checkEnrichmentCitation networkScoring
Enrichment:Pending

FAIR Checklist

Context only (not used in score)
Findable (1/2)
  • Has DOI
Accessible (0/2)
    Interoperable (0/2)
      Reusable (0/3)

        FAIR checklist signals are shown for context only and do not affect DataRank scoring.

        DataRank Breakdown

        Base Score 100%Citation Network 0%

        Base Score Contribution

        1.4

        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 →
        Why this DataRank?

        DataRank blends this paper's own citation count with the influence of the papers that cite it. Here, roughly 100% comes from its base citations and 0% from the citation network.

        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.

        Read the full methodology →

        Authors (15)

        Takashi Tokino,Victor E. VelculescuORCID,Daniel B. Levy,Ramon ParsonsORCID,Jeffrey M. Trent

        Related Papers (10)

        Cell(2008)
        co-citedsame journal
        10.1016/j.cell.2007.12.018
        Surfing the p53 network
        N/A
        1.3DataRank · unranked
        Nature(2000)
        co-cited
        10.1038/35042675
        Nature(2000)
        co-cited
        10.1038/47412
        Nature Reviews Cancer(2007)
        co-cited
        10.1038/nrc2223