Abstract
The work considers the problem of selecting the most informative genes in the task of cancer tumors recognition based on the gene expression profile. The model of a cancer classifier based on a feedforward neural network is proposed. The most informative genes were selected using the layer-wise relevance propagation (LRP) method. The statistical methods were used to check the selected genes for relations to cancer.
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Kruzhalov, A., Philippovich, A. (2020). Selection of the Most Informative Genes in the Task of Cancer Tumors Recognition Based on the Gene Expression Profile. In: Silhavy, R., Silhavy, P., Prokopova, Z. (eds) Software Engineering Perspectives in Intelligent Systems. CoMeSySo 2020. Advances in Intelligent Systems and Computing, vol 1295. Springer, Cham. https://doi.org/10.1007/978-3-030-63319-6_83
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DOI: https://doi.org/10.1007/978-3-030-63319-6_83
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