title: A novel bioinformatics method for efficient knowledge discovery by BLSOM from big genomic sequence data.
abstract: With remarkable increase of genomic sequence data of a wide range of species, novel tools are needed for comprehensive analyses of the big sequence data. Self-Organizing Map (SOM) is an effective tool for clustering and visualizing high-dimensional data such as oligonucleotide composition on one map. By modifying the conventional SOM, we have previously developed Batch-Learning SOM (BLSOM), which allows classification of sequence fragments according to species, solely depending on the oligonucleotide composition. In the present study, we introduce the oligonucleotide BLSOM used for characterization of vertebrate genome sequences. We first analyzed pentanucleotide compositions in 100 kb sequences derived from a wide range of vertebrate genomes and then the compositions in the human and mouse genomes in order to investigate an efficient method for detecting differences between the closely related genomes. BLSOM can recognize the species-specific key combination of oligonucleotide frequencies in each genome, which is called a "genome signature," and the specific regions specifically enriched in transcription-factor-binding sequences. Because the classification and visualization power is very high, BLSOM is an efficient powerful tool for extracting a wide range of information from massive amounts of genomic sequences (i.e., big sequence data).
authors.affiliation: Graduate School of Information Science, Nara Institute of Science and Technology, 8916-5 Takayama-cho, Ikoma-shi, Nara 630-0192, Japan.
authors.forename: Yu
authors.identifier: 0000-0002-8237-9514
authors.initials: Y
authors.lastname: Bai
authors.affiliation: Department of Bioscience, Nagahama Institute of Bio-Science and Technology, Nagahama-shi, Shiga-ken 526-0829, Japan.
authors.forename: Yuki
authors.initials: Y
authors.lastname: Iwasaki
authors.affiliation: Graduate School of Information Science, Nara Institute of Science and Technology, 8916-5 Takayama-cho, Ikoma-shi, Nara 630-0192, Japan.
authors.forename: Shigehiko
authors.initials: S
authors.lastname: Kanaya
authors.affiliation: Sino-Dutch Biomedical and Information Engineering School, Northeastern University, Shenyang, Liaoning 110004, China.
authors.forename: Yue
authors.initials: Y
authors.lastname: Zhao
authors.affiliation: Department of Bioscience, Nagahama Institute of Bio-Science and Technology, Nagahama-shi, Shiga-ken 526-0829, Japan.
authors.forename: Toshimichi
authors.initials: T
authors.lastname: Ikemura
mesh_terms: D000465:Algorithms; D000818:Animals; D002874:Chromosome Mapping; D019295:Computational Biology / Q000379:methods*; D016678:Genome; D023281:Genomics / Q000379:methods*; D006801:Humans; D051379:Mice; D017422:Sequence Analysis, DNA