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

MegaLMM: Mega-scale linear mixed models for genomic predictions with thousands of traits

bioRxiv (Cold Spring Harbor Laboratory)(2020)10.1101/2020.05.26.116814Source: DataRank Database

MegaLMM: Mega-scale linear mixed models for genomic predictions with thousands of traits is a research paper published in bioRxiv (Cold Spring Harbor Laboratory) (2020). On theSindex it has a DataRank of 0. It has been cited 8 times.

N/A

0DataRank · unranked

Scored on demand from live citation data

Open Access8 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 (3 grants)OA: greenTopics (53)IDs (PubMed, OpenAlex)SDGs (2)

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 (4)

Jiayi Qu ORCID,Hao Cheng ORCID,Lorin Crawford ORCID,Daniel E. Runcie ORCID

Live enrichment

PubMed:19162232 OpenAlex:https://openalex.org/W3032686211

National Institutes of Health

Grant: 2U10CA180794-06

ECOG-ACRIN Network Group Statistics and Data Management Center

National Institutes of Health

Grant: 5P20GM103645-02

Development of vision and attention in typical and ASD individuals

National Institutes of Health

Grant: 2P20GM109035-06

COBRE: Center for Computational Biology of Human Disease

greenLicense: cc-by

repositoryhttps://www.biorxiv.org/content/biorxiv/early/2021/05/07/2020.05.26.116814.full.pdf

publisherhttps://syndication.highwire.org/content/doi/10.1101/2020.05.26.116814

repositoryhttps://doi.org/10.1101/2020.05.26.116814

repositoryhttps://escholarship.org/uc/item/9m69b0h8

Fields of Study

Genetic and phenotypic traits in livestockGenetic Mapping and Diversity in Plants and AnimalsGenetics and Plant Breeding

Keywords

Leverage (statistics)Mixed modelTraitLinear modelGeneralized linear mixed modelBiologyQuantitative trait locusGenomic selectionComputational biologyComputer scienceMachine learningGeneticsGenotypeSingle-nucleotide polymorphism570BioinformaticsQH301-705.5ArabidopsisMethodQH426-470Zea maysQuantitative TraitQuantitative Trait, HeritableGenetic2.5 Research design and methodologies (aetiology)ModelsInformation and Computing SciencesHumansAetiologyBiology (General)HeritableTriticumGenomeGenomic predictionMulti-environment trialModels, GeneticHuman Genome500Bayes TheoremPlantGenomicsBiological SciencesMulti-trait Linear Mixed ModelPlant BreedingPhenotypeHigh-throughput phenotypingGene-Environment InteractionEnvironmental SciencesGenome, PlantSoftware

Sustainable Development Goals

SDG 2: 2. Zero hungerSDG 3: 3. Good health