Detecting Boolean Asymmetric Relationships With a Loop Counting Technique and its Implications for Analyzing Heterogeneity Within Gene Expression Datasets
Zhou H, Lin W, Labra S, Lipton S, Elman J, Schork N, Rangan A. Detecting Boolean Asymmetric Relationships With a Loop Counting Technique and its Implications for Analyzing Heterogeneity Within Gene Expression Datasets. IEEE/ACM Transactions On Computational Biology And Bioinformatics 2024, 22: 27-38. PMID: 39471117, DOI: 10.1109/tcbb.2024.3487434.Peer-Reviewed Original ResearchSubsets of genesGene-gene relationshipsGene expression dataGene-gene interactionsGene expression datasetsRNA-sequencing data setsDetected biclustersExpression datasetsGene pathwaysSubsets of cellsGenesRegulatory effectsBiclusteringCorrelated expressionAsymmetric interactionsSymmetric interactionsInteractionExpressionCells
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