pone.0257084.s002.tif (1.01 MB)
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posted on 2021-09-10, 17:37 authored by Doris Kafita, Panji Nkhoma, Mildred Zulu, Musalula Sinkala(a) Evaluating the optimum number of clusters: The plot displays the Calinski-Harabasz evaluation method [66]. The optimum number of clusters is the number of cluster values that correspond to the highest Calinski-Harabasz value. In this case, the optimum number of clusters is two. (b) Range of values assessed by the Bayesian optimisation objective function to select the optimal machine learning hyperparameters for the Kernel naïve Bayes supervised learning model [77,78].
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molecular alterations associateddifferent molecular processescopy number alterationsapply unsupervised clusteringintegrative bioinformatics analysisvarious molecular aberrationsaltered molecular processestwo distinct subtypespancreatic cancer patientspathway analysis basedpancreatic cancer subtypespancreatic cancerproteogenomic analysissignalling aberrationspancreatic tumoursaltered amongwnt pathwaynotch pathwayusing functionalusing datasetstumour cellsspecific genomicrising incidenceproteomic landscapeproteogenomic landscapemtor pathwaysgenomics landscapeclinical characteristics
