Um método de Estimação de Expressões Gênicas de Câncer de Mama com Base em Correlação

• Beatriz A. Rodrigues UFAM
• Rayol M. Neto UFAM
• Fabiola F. Nakamura UFAM
• Eduardo F. Nakamura UFAM

DOI: https://doi.org/10.5753/semish.2023.229914

Abstract

Gene expression data often suffer from lost value problems for various experimental reasons. In breast cancer databases, subsequent analysis and subtyping can suffer heavily from missing data, so addressing this issue is paramount. Several approaches for estimating these values in gene expression data have been developed. Still, the task is difficult due to factors such as the existence or not of a correlation structure in the data and the high dimensionality (number of genes x number of samples) of the data. In this research, we developed a method to treat missing values in breast cancer gene expressions, which deals with the high dimensionality of the data, performing the selection of genes that best characterize breast cancer based on the use of correlation information between genes. The method was evaluated using the RMSE and MAE metrics.

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