Using Machine Learning and Western Blotting Techniques to Understand the Genomic Difference Between E-Cigarette Vapor and Cigarette Smoke and its Relation to Tumor Development

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This study examines the relationship between cigarettes and e-cigarettes using machine learning, data mining, and a clustering algorithm based on gene expression to understand patterns in how the affected pathways of genes expressed in the human bronchial epithelial cells vary. These comparisons reveal similarities and differences between cigarettes and e-cigarettes and make a suggestion towards whether e-cigarette vapor causes tumor growth.