Pilot corpus: NIH-funded biomedical datasets. Any DOI can be scored on demand — network effects sharpen as coverage grows.

Evaluation of large language models for discovery of gene set function

Research Square(2023)10.21203/rs.3.rs-3270331/v1Source: DataRank Database

Evaluation of large language models for discovery of gene set function is a research paper published in Research Square (2023). On theSindex it has a DataRank of 0. It has been cited 9 times.

N/A

0DataRank · unranked

Scored on demand from live citation data

Open Access9 citations

Download PDF

Cite:

DataRank reads this dataset's downstream impact straight off the citation graph — no black box, no proprietary weighting. How is this computed?

›Methodology & internals

datarank_citation_only_1hop_v6· scope data_onlyMethodology

Pipeline:MetadataData-paper checkEnrichmentCitation networkScoring

Enrichment:Funding (10 grants)OA: greenTopics (45)IDs (PubMed, OpenAlex)SDGs (1)

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.

Run a calibrated FAIR evaluation for this paper →

We only score data papers we can read in full — never from an abstract alone.

Authors (7)

Mengzhou Hu ORCID,Sahar Alkhairy ORCID,Ingoo Lee ORCID,Rudolf Pillich ORCID,Robin E. Bachelder ORCID

Live enrichment

PubMed:37790547 OpenAlex:https://openalex.org/W4386810494

National Institutes of Health

Grant: 1U24CA269436-01A1

The Network Data Exchange - a Network Commons for Biologists

National Institutes of Health

Grant: 5U24HG012107-03

CYTOSCAPE: AN ECOSYSTEM FOR NETWORK GENOMICS

National Institutes of Health

Grant: 1U54CA274502-01

The Cancer Cell Map Initiative v2.0

National Institutes of Health

Grant: 5U01MH115747-03

The Psychiatric Cell Map Initiative: Connecting Genomics, Subcellular Networks, and Higher Order Phenotypes

National Institutes of Health

Grant: 3OT2OD032742-01S3

Bridge2AI: Cell Maps for AI (CM4AI) Data Generation Project

NCI NIH HHS

Grant: U54 CA274502

NHGRI NIH HHS

Grant: U24 HG012107

NIH HHS

Grant: OT2 OD032742

NIMH NIH HHS

Grant: U01 MH115747

NCI NIH HHS

Grant: U24 CA269436

greenLicense: cc-by

repositoryhttps://www.researchsquare.com/article/rs-3270331/latest.pdf

publisherhttps://www.researchsquare.com/article/rs-3270331/v1

publisherhttps://www.researchsquare.com/article/rs-3270331/v1.html

repositoryhttps://doi.org/10.21203/rs.3.rs-3270331/v1

Fields of Study

Biomedical Text Mining and OntologiesBioinformatics and Genomic NetworksGene expression and cancer classification0301 basic medicine03 medical and health sciences0303 health sciences

Keywords

Gene nomenclatureSet (abstract data type)Functional genomicsPipeline (software)Context (archaeology)GenomicsFunction (biology)Computational biologyGene ontologyGeneComputer scienceBenchmarkingGene AnnotationOntologyBiologyGeneticsGene expressionGenomeProgramming languageFOS: Computer and information sciencesComputer Science - Artificial IntelligenceMolecular Networks (q-bio.MN)610ArticleDatabasesLarge Language ModelsGeneticDatabases, GeneticHumansQuantitative Biology - GenomicsQuantitative Biology - Molecular NetworksGenomics (q-bio.GN)Computer Science - Computation and Language004Artificial Intelligence (cs.AI)FOS: Biological sciencesProgramming LanguagesComputation and Language (cs.CL)Software

Sustainable Development Goals

SDG 0: Quality Education