0000000000803570

AUTHOR

Senol Isci

showing 2 related works from this author

Pathway analysis of high-throughput biological data within a Bayesian network framework

2011

Abstract Motivation: Most current approaches to high-throughput biological data (HTBD) analysis either perform individual gene/protein analysis or, gene/protein set enrichment analysis for a list of biologically relevant molecules. Bayesian Networks (BNs) capture linear and non-linear interactions, handle stochastic events accounting for noise, and focus on local interactions, which can be related to causal inference. Here, we describe for the first time an algorithm that models biological pathways as BNs and identifies pathways that best explain given HTBD by scoring fitness of each network. Results: Proposed method takes into account the connectivity and relatedness between nodes of the p…

Statistics and ProbabilityComputer scienceHigh-throughput screeningGene regulatory networkcomputer.software_genreModels BiologicalBiochemistrySynthetic dataBiological pathwayBayes' theoremHumansGene Regulatory NetworksCarcinoma Renal CellMolecular BiologyGeneBiological dataMicroarray analysis techniquesGene Expression ProfilingBayesian networkRobustness (evolution)Bayes TheoremPathway analysisKidney NeoplasmsHigh-Throughput Screening AssaysComputer Science ApplicationsGene expression profilingComputational MathematicsComputational Theory and MathematicsCausal inferenceData miningcomputerAlgorithmsSoftwareBioinformatics
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Bayesian network based pathway analysis of microarray data

2011

Microarray analysis techniquesComputer scienceBiomedical EngineeringMicroarray databasesBayesian networkBioengineeringComputational biologyPathway analysisBiotechnologyCurrent Opinion in Biotechnology
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