1. Abe, T., Kanaya, S., & Ikemura, T. (2009). Batch-learning self-organizing map for predicting functions of poorly-characterized proteins massively accumulated. In: Principe, J., Miikkulainen, R. (eds). Lecture notes in computer science, pp. 1–9.
2. Abe, T., Kanaya, S., Kinouchi, M., Ichiba, Y., Kozuki, T., & Ikemura, T. (2002). A novel bioinformatic strategy for unveiling hidden genome signatures of eukaryotes: Self-organizing map of oligonucleotide frequency. Genome Informatics, 13, 12–20.
3. Abe, T., Kanaya, S., Kinouchi, M., et al. (1999). Gene classification method based on batch-learning SOM. In: Asai, K., Miyano, S., Takagi, T. (eds) Genome Informatics Series No. 10. Tokyo, Universal Academy Press, pp. 314–315.
4. Abe, T., Sugawara, H., Kanaya, S., & Ikemura, T. (2006a). A novel bioinformatics tool for phylogenetic classification of genomic sequence fragments derived from mixed genomes of environmental uncultured microbes. Polar Biosci., 20, 103–112.
5. Abe, T., Sugawara, H., Kinouchi, M., Kanaya, S., & Ikemura, T. (2006b). Self-organizing map (som) unveils and visualizes hidden sequence characteristics of a wide range of eukaryote genomes. Gene, 365, 27–34.