k- Strong Inference Algorithm: A Hybrid Information Theory Based Gene Network Inference Algorithm

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dc.contributor.authorCingiz, Mustafa Özgür
dc.date.accessioned2026-02-08T15:11:05Z
dc.date.available2026-02-08T15:11:05Z
dc.date.issued2024
dc.departmentBursa Teknik Üniversitesi
dc.description.abstractGene networks allow researchers to understand the underlying mechanisms between diseases and genes while reducing the need for wet lab experiments. Numerous gene network inference (GNI) algorithms have been presented in the literature to infer accurate gene networks. We proposed a hybrid GNI algorithm, k-Strong Inference Algorithm (ksia), to infer more reliable and robust gene networks from omics datasets. To increase reliability, ksia integrates Pearson correlation coefficient (PCC) and Spearman rank correlation coefficient (SCC) scores to determine mutual information scores between molecules to increase diversity of relation predictions. To infer a more robust gene network, ksia applies three different elimination steps to remove redundant and spurious relations between genes. The performance of ksia was evaluated on microbe microarrays database in the overlap analysis with other GNI algorithms, namely ARACNE, C3NET, CLR, and MRNET. Ksia inferred less number of relations due to its strict elimination steps. However, ksia generally performed better on Escherichia coli (E.coli) and Saccharomyces cerevisiae (yeast) gene expression datasets due to F- measure and precision values. The integration of association estimator scores and three elimination stages slightly increases the performance of ksia based gene networks. Users can access ksia R package and user manual of package via https://github.com/ozgurcingiz/ksia. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2023.
dc.identifier.doi10.1007/s12033-023-00929-2
dc.identifier.endpage3225
dc.identifier.issn1073-6085
dc.identifier.issue11
dc.identifier.pmid37950851
dc.identifier.scopus2-s2.0-85176613737
dc.identifier.scopusqualityQ2
dc.identifier.startpage3213
dc.identifier.urihttps://doi.org/10.1007/s12033-023-00929-2
dc.identifier.urihttps://hdl.handle.net/20.500.12885/5234
dc.identifier.volume66
dc.indekslendigikaynakScopus
dc.indekslendigikaynakPubMed
dc.language.isoen
dc.publisherSpringer
dc.relation.ispartofMolecular Biotechnology
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzScopus_KA_20260207
dc.subjectAssociation estimators
dc.subjectGene co-expression networks
dc.subjectGene network inference algorithms
dc.subjectGene regulatory networks
dc.subjectOverlap analysis
dc.titlek- Strong Inference Algorithm: A Hybrid Information Theory Based Gene Network Inference Algorithm
dc.typeArticle

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