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.

ProfileChaser: searching microarray repositories based on genome-wide patterns of differential expression

Bioinformatics(2011)10.1093/bioinformatics/btr548Source: DataRank Database

ProfileChaser: searching microarray repositories based on genome-wide patterns of differential expression is a research paper published in Bioinformatics (2011). On theSindex it has a DataRank of 0.568. It has been cited 43 times.

N/A

0.568DataRank · unranked

0.568

Open Access43 citations · base score 3.8

Cite:

datarank_citation_only_1hop_v6· scope data_onlyMethodology

Abstract

SummaryWe introduce ProfileChaser, a web server that allows for querying the Gene Expression Omnibus based on genome-wide patterns of differential expression. Using a novel, content-based approach, ProfileChaser retrieves expression profiles that match the differentially regulated transcriptional programs in a user-supplied experiment. This analysis identifies statistical links to similar expression experiments from the vast array of publicly available data on diseases, drugs, phenotypes and other experimental conditions.Availabilityhttp://profilechaser.stanford.eduContactabutte@stanford.eduSupplementary informationSupplementary data are available at Bioinformatics online.

›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 (0/3)

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

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DataRank Breakdown

Base Score 100%Citation Network 0%

Base Score Contribution

0.568

From this paper's citation signal

Citation Network Contribution

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.

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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(C_q) ÷ max(outdegree_q, 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 →