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KSMoFinder—knowledge graph embedding of proteins and motifs for predicting kinases of human phosphosites

Bioinformatics Advances(2024)10.1093/bioadv/vbaf289Source: DataRank Database

KSMoFinder—knowledge graph embedding of proteins and motifs for predicting kinases of human phosphosites is a research paper published in Bioinformatics Advances (2024). On theSindex it has a DataRank of 0. It has been cited 1 time.

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0DataRank · unranked

Scored on demand from live citation data

Open Access1 citations

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Linked data & code

reactome go uniprot interpro

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›Methodology & internals

datarank_citation_only_1hop_v6· scope data_onlyMethodology

Pipeline:MetadataData-paper checkEnrichmentCitation networkScoring

Enrichment:Funding (2 grants)Impact (FWCI 0.16)OA: goldTopics (9)IDs (PubMed, PMC, OpenAlex)Annotations (4)

FAIR Checklist

Context only (not used in score)

Findable (1/2)

Has DOI

Accessible (1/2)

Open Access

Interoperable (0/2)

Reusable (0/3)

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Authors (5)

Karen Ross ORCID,Chuming Chen ORCID,K. Vijay‐Shanker ORCID,Cathy Wu ORCID,Manju Anandakrishnan ORCID

Live enrichment

PubMed:41323648 PMC:PMC12664573 OpenAlex:https://openalex.org/W4416121843

National Institutes of Health

Grant: R35GM141873

National Institutes of Health

Grant: U24OD038424

FWCI

0.16

Citation Percentile

0.5%

Citation Trend

2026

goldLicense: cc-by

journalhttps://doi.org/10.1093/bioadv/vbaf289

publisherhttps://doi.org/10.1093/bioadv/vbaf289

publisherhttps://academic.oup.com/bioinformaticsadvances/advance-article-pdf/doi/10.1093/bioadv/vbaf289/65270416/vbaf289.pdf

publisherhttps://academic.oup.com/bioinformaticsadvances/article-pdf/5/1/vbaf289/65270416/vbaf289.pdf

repositoryhttps://pubmed.ncbi.nlm.nih.gov/41323648

Fields of Study

Bioinformatics and Genomic NetworksGraph Theory and AlgorithmsMachine Learning in Bioinformatics

Keywords

EmbeddingGraphKinaseSource codeCode (set theory)Human proteins

KSMoFinder—knowledge graph embedding of proteins and motifs for predicting kinases of human phosphosites

FAIR Checklist

Authors (5)

Funding (2 grants)

Impact

Open Access

Topics

Annotations (Europe PMC)