A machine learning approach to predict gene expression levels based on stochastic simulation
Nada Al taweraqi,
Ross King
Abstract:Purpose: Genes are key players in cellular systems as they control different aspects of cell behaviour and progression. Abnormalities in gene activities are indicators of cancer development and pathogenesis. However, despite the many advances in prediction tools and algorithms, predicting gene expression levels is considered challenging due to the noisy measurements of genes and the high complexity of the cellar networks. This study highlights the role of literature knowledge represented as signalling pathways… Show more
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