Intelligent Computing Theories and Application: 16th International Conference, ICIC 2020, Bari, Italy, October 2–5, 2020, Proceedings, Part II

Learning latent feature representation embedding in highdimensional gene expression data is a crucial step for gene clustering application. Our clustering-framework method, incorporating Variational Autoencoders (VAE) into Self-Organizing Map (SOM), not only clustered gene expression data precisely, but also reduced the dimensionality of raw data effectively without any prior knowledge. The clustering results obtained from this method based on four gene datasets exhibited an impressive performance in efficiency and accuracy.