Detail Analysis of DNA Microarray Data by Using Self-Organizing Maps (in Genome Informatics 14) Bibliografi Author: Kato, Tomoyuki ; Fujimura, Kikuo ; Tokutaka, Heizo ; Kawata, Yasushi ; Ohkita, Masaaki Topik: Self-Organizing Maps; DNA Microarray; Genes Bahasa: (EN )    Edisi: 2003     Penerbit: Japanese Society for Bioinformatics     Tempat Terbit: Tokyo    Tahun Terbit: 2003     Jenis: Article - diterbitkan di jurnal ilmiah internasional Fulltext: GIW03P163.pdf (450.1KB; 0 download) [Informasi yang berkaitan dengan koleksi ini di internet] Abstract Self-Organizing Maps (SOM) is a kind of an arti_cial neural network. SOM is an unsupervised learning. By that, various, multi-dimensional data can be made visible and then clustered. Moreover, by making the component maps, it will be known what kind of inuence any arbitrary dimensional component can give for clustering. Then, an attractively new analytical technique which uses SOM is proposed and used for DNA microarray data in this article. MATLAB was used for the analysis. Opini Anda Klik untuk menuliskan opini Anda tentang koleksi ini! Lihat Sejarah Pengadaan  Konversi Metadata   Kembali

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