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

ZetaSuite, A Computational Method for Analyzing Multi-dimensional High-throughput Data, Reveals Genes with Opposite Roles in Cancer Dependency

bioRxiv (Cold Spring Harbor Laboratory)(2021)10.1101/2021.08.29.458095Source: DataRank Database

ZetaSuite, A Computational Method for Analyzing Multi-dimensional High-throughput Data, Reveals Genes with Opposite Roles in Cancer Dependency is a research paper published in bioRxiv (Cold Spring Harbor Laboratory) (2021). On theSindex it has a DataRank of 0.

N/A

0DataRank · unranked

Scored on demand from live citation data

Open Access0 citations

Download PDF

Cite:

Linked data & code

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 (1 grants)OA: greenTopics (24)Linked Datasets (2)DataCite Reuse (2)IDs (PubMed, OpenAlex)SDGs (1)

FAIR Checklist

Context only (not used in score)

Findable (2/2)

Has DOI
Indexed in repositories

Accessible (1/2)

Open Access

Interoperable (2/2)

DataCite relations
Linked datasets

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)

Changwei Shao ORCID,Guofeng Zhao ORCID,Xiang‐Dong Fu ORCID,Yajing Hao ORCID

Live enrichment

PubMed:19910364 OpenAlex:https://openalex.org/W3198581913

National Institutes of Health

Grant: 5R01DK098808-05

Synergestic roles of SRSF2 and RUNX1 in blood cell development and pathology

greenLicense: cc-by-nc-nd

repositoryhttps://www.biorxiv.org/content/biorxiv/early/2021/08/30/2021.08.29.458095.full.pdf

publisherhttps://syndication.highwire.org/content/doi/10.1101/2021.08.29.458095

repositoryhttps://doi.org/10.1101/2021.08.29.458095

https://dx.doi.org/10.1101/2021.08.29.458095

Fields of Study

CRISPR and Genetic EngineeringGenomics and Chromatin DynamicsRNA and protein synthesis mechanisms0301 basic medicine0303 health sciences03 medical and health sciences

Keywords

Dependency (UML)ThroughputComputer scienceGenomeComputational biologyStatisticDimension (graph theory)CancerConstruct (python library)Function (biology)GeneReplication (statistics)BiologyGeneticsMathematicsArtificial intelligenceStatisticsComputer network

Sustainable Development Goals

SDG 3: 3. Good health

Computational Analysis of Two-dimensional High-throughput Data from Large-scale RNAi Screens and Single-cell Transcriptomics

10.5281/zenodo.6395173Zenodo

Computational Analysis of Two-dimensional High-throughput Data from Large-scale RNAi Screens and Single-cell Transcriptomics

10.5281/zenodo.6395174Zenodo