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Mapping of DNA sequences using Hidden Markov Model Self Organizing Maps

発表形態：
原著論文
主要業績：
主要業績
単著・共著：
共著
発表年月：
2013年04月
DOI：
会議属性：
国際会議（国内開催を含む）
査読：
有り
リンク情報：

日本語フィールド

著者：
Hiroshi Dozono, Gen Niina
題名：
Mapping of DNA sequences using Hidden Markov Model Self Organizing Maps
発表情報：
roceedings of the Proceedings of 2013 IEEE Symposium Series on Computational Intelligence (SSCI) ページ: 212-217
キーワード：
概要：
抄録：
Abstract—Recently, next generation sequencing techniques have begun to produce huge amounts of sequencing data. To analyze these data, an efficient method that can handle large amounts of information is required. In this paper, we proposed a method for classifying sets of DNA sequences by using a hidden Markov model self-organizing map. For this purpose, a learning algorithm that requires low computational costs was developed. The availability of this method was examined in experiments classifying DNA sequences of various types of genes.

英語フィールド

Author：
Hiroshi Dozono, Gen Niina
Title：
Mapping of DNA sequences using Hidden Markov Model Self Organizing Maps
Announcement information:
roceedings of the Proceedings of 2013 IEEE Symposium Series on Computational Intelligence (SSCI) Page: 212-217
An abstract：
Abstract—Recently, next generation sequencing techniques have begun to produce huge amounts of sequencing data. To analyze these data, an efficient method that can handle large amounts of information is required. In this paper, we proposed a method for classifying sets of DNA sequences by using a hidden Markov model self-organizing map. For this purpose, a learning algorithm that requires low computational costs was developed. The availability of this method was examined in experiments classifying DNA sequences of various types of genes.

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