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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.

The microbiome of the buffalo digestive tract

Nature Communications(2022)10.1038/s41467-022-28402-9Source: DataRank Database

The microbiome of the buffalo digestive tract is a dataset published in Nature Communications (2022). On theSindex it has a DataRank of 2.2, placing it in the top 34.7% of the data-sharing corpus. It has been cited 101 times, with 86 citing works in its 1-hop citation network. Its calibrated FAIR score is 50/100.

Top 35%percentile
2.2DataRank
2.2Top 35%
Dataset Open Access101 citations · base score 4.5
Cite:
datarank_citation_only_1hop_v6· scope data_onlyMethodology

Abstract

Buffalo is an important livestock species. Here, we present a comprehensive metagenomic survey of the microbial communities along the buffalo digestive tract. We analysed 695 samples covering eight different sites in three compartments (four-chambered stomach, intestine, and rectum). We mapped ~85% of the raw sequence reads to 4,960 strain-level metagenome-assembled genomes (MAGs) and 3,255 species-level MAGs, 90% of which appear to correspond to new species. In addition, we annotated over 5.8 million nonredundant proteins from the MAGs. In comparison with the rumen microbiome of cattle, the buffalo microbiota seems to present greater potential for fibre degradation and less potential for methane production. Our catalogue of microbial genomes and the encoded proteins provides insights into microbial functions and interactions at distinct sites along the buffalo digestive tract.

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

FAIR Checklist

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

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

    50FAIR score
    F Findable
    53
    A Accessible
    68
    I Interoperable
    38
    R Reusable
    42
    Top 22% by FAIRLLM-assessed✓ full text read

    Calibrated FAIR score — a parallel quality metric, independent of the DataRank citation score. See the full evaluation →

    DataRank Breakdown

    Base Score 30%Citation Network 70%

    Base Score Contribution

    0.675

    From this paper's citation signal

    Citation Network Contribution

    1.5

    From 59 citing papers with measurable signal

    Learn more about DataRank methodology →

    Top 5 citers driving the network score

    Ranked by citation count — the same ordering the engine uses when summing log1p(Cq) over citers.

    1. The Sequence Alignment/Map format and SAMtools
      Bioinformatics200966,179 citationsDataRank 1.7
    2. Fast gapped-read alignment with Bowtie 2
      Nature Methods201259,681 citationsDataRank 1.6
    3. Metagenomic biomarker discovery and explanation
      Genome Biology201116,383 citationsDataRank 1.5
    Why this DataRank?

    DataRank blends this paper's own citation count with the influence of the papers that cite it. Here, roughly 30% comes from its base citations and 70% from the citation network (59 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.

    Read the full methodology →

    Click a node to highlight its connections. Use scroll to zoom. Drag to pan.

    Node colors:CenterData PaperData + Open AccessNon-dataSelected & links| Node size = percentile rank

    Authors (19)

    Teng WangORCID,Na L Gao,Ziying LiuORCID,Kuiqing CuiORCID,Yiqian DuanORCID