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

Ten quick tips for deep learning in biology

PLOS Computational Biology(2022)10.1371/journal.pcbi.1009803Source: DataRank Database

Ten quick tips for deep learning in biology is a research paper published in PLOS Computational Biology (2022). On theSindex it has a DataRank of 0.550. It has been cited 38 times.

N/A

0.550DataRank · unranked

Scored on demand from live citation data

Open Access38 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 (27 grants)Impact (FWCI 0.00)OA: goldTopics (16)IDs (PubMed, PMC, 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.

DataRank Breakdown

Base Score 100%Citation Network 0%

Base Score Contribution

0.550

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.

Learn more about DataRank methodology →

Authors (21)

Anthony Gitter ORCID,Casey S. Greene ORCID,Sebastian Raschka ORCID,Finlay Maguire ORCID,Alexander J. Titus ORCID

Live enrichment

PubMed:35324884 PMC:PMC8946751 OpenAlex:https://openalex.org/W3040460291

National Science Foundation

Grant: DBI 1553206

National Institutes of Health

Grant: R01GM135631

National Institutes of Health

Grant: R01 HG010067

Gordon and Betty Moore Foundation

Grant: GBMF 4552

Wisconsin Alumni Foundation

Grant: AAD5912

National Institutes of Health

Grant: R01DE027809

USDA National Institute of Food and Agriculture

Grant: 2020-67012-31772

Moffitt Cancer Center

Grant: P30-CA076292

National Institutes of Health

Grant: T32 HG003284

National Institute of General Medical Sciences

Grant: R35GM142879

Emerson Foundation

Grant: 640183

National Cancer Institute

Grant: U01CA212007, U01CA253403, P30CA006973

National Institute of Allergy and Infectious Diseases

Grant: R21AI153997

National Institutes of Health

Grant: R21 CA220398

NCI NIH HHS

Grant: P30 CA006973

NHLBI NIH HHS

Grant: R01 HL174679

NCI NIH HHS

Grant: U01 CA253403

NCI NIH HHS

Grant: P30 CA076292

NCI NIH HHS

Grant: U01 CA212007

Folz Fund for Cancer Research

Michelle Lunn Hope Foundation

Allegheny Health Network

Blavatnik Center for Computational Biomedicine

Donald Hill Family Fellowship

Lustgarten Foundation

National Science Foundation

Grand Rapids Community Foundation

FWCI

0.00

Citation Percentile

0.0%

goldLicense: cc-by

journalhttps://journals.plos.org/ploscompbiol/article/file?id=10.1371/journal.pcbi.1009803&type=printable

publisherhttps://journals.plos.org/ploscompbiol/article/file?id=10.1371/journal.pcbi.1009803&type=printable

publisherhttps://dx.plos.org/10.1371/journal.pcbi.1009803

journalhttps://doi.org/10.1371/journal.pcbi.1009803

repositoryhttps://pubmed.ncbi.nlm.nih.gov/35324884

Fields of Study

Genetics, Bioinformatics, and Biomedical ResearchBioinformatics and Genomic NetworksCell Image Analysis Techniques

MeSH Terms

Deep LearningComputational Biology

Keywords

Artificial intelligenceDeep learningMachine learningComputer scienceContext (archaeology)Active learning (machine learning)Task (project management)Instance-based learningSet (abstract data type)Data scienceEngineering

Sustainable Development Goals

SDG 0: Quality Education