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Semi-supervised data-integrated feature importance enhances performance and interpretability of biological classification tasks

Bioinformatics(2025)10.1093/bioinformatics/btaf190Source: DataRank Database

Semi-supervised data-integrated feature importance enhances performance and interpretability of biological classification tasks is a research paper published in Bioinformatics (2025). 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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›Methodology & internals

datarank_citation_only_1hop_v6· scope data_onlyMethodology

Pipeline:MetadataData-paper checkEnrichmentCitation networkScoring

Enrichment:Funding (4 grants)Impact (FWCI 0.49)OA: goldTopics (38)IDs (PubMed, OpenAlex)

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 (2)

Russ B. Altman ORCID,Jun W. Kim ORCID

Live enrichment

PubMed:40662781 OpenAlex:https://openalex.org/W4412426857

NLM

Grant: T15007033

NIH

Grant: GM153195

National Institutes of Health

Grant: 1R35GM153195-01

Computational methods for characterizing sources of variability in drug response

NIGMS NIH HHS

Grant: R35 GM153195

FWCI

0.49

Citation Percentile

0.6%

Citation Trend

2026

goldLicense: cc-by

journalhttps://academic.oup.com/bioinformatics/article-pdf/41/Supplement_1/i373/63745304/btaf190.pdf

publisherhttps://academic.oup.com/bioinformatics/article-pdf/41/Supplement_1/i373/63745304/btaf190.pdf

journalhttps://doi.org/10.1093/bioinformatics/btaf190

repositoryhttps://pubmed.ncbi.nlm.nih.gov/40662781

repositoryhttps://www.ncbi.nlm.nih.gov/pmc/articles/12261460

Fields of Study

Gene expression and cancer classificationMachine Learning in BioinformaticsExplainable Artificial Intelligence (XAI)0206 medical engineering02 engineering and technologyHumansNeoplasmsNeural Networks, ComputerComputational BiologyAlgorithmsGene Expression ProfilingSupervised Machine Learning

MeSH Terms

Supervised Machine LearningAlgorithmsHumansNeoplasmsNeural Networks, ComputerComputational BiologyGene Expression Profiling

Keywords

InterpretabilityWeightingFeature (linguistics)Computer scienceArtificial intelligenceSimilarity (geometry)A priori and a posterioriMachine learningRelevance (law)Data miningPattern recognition (psychology)NeoplasmsGene Expression ProfilingHumansComputational BiologyNeural Networks, ComputerSupervised Machine LearningMacromolecular Sequence, Structure, and FunctionAlgorithms