Classification performance on Kidney based on the three-class HELP labelling.
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posted on 2024-09-27, 17:36 authored by Ilaria Granata, Lucia Maddalena, Mario Manzo, Mario Rosario Guarracino, Maurizio Giordano(left) Three-class labelling distribution for Kidney csEGs, and (right) Box plots of the performance metrics obtained for classification of “E vs sNE”, “E vs aE”, and “aE vs sNE” using Bio+CCcfs+N2V features.
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true positive ratespredictive models trainedpredicting human commondouble scope allowsl h e predicting essential genesidentifying essential genesdiv >< pidentifying genes basedessential gene annotationsessential gene annotationnetwork embedding featuresp new experimental dataessential genesexperimental datauman genegene essentialitygene attributessource datareference setsrediction ),performance predictionparticularly suitableneither binarymachine learningcomputational frameworkbest compromisebased approaches
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