HMM with protein structure grammar

Kiyoshi Asai*, Satoru Hayamizu, Kentaro Onizuka

*この研究の対応する著者

研究成果: Conference contribution

20 被引用数 (Scopus)

抄録

The authors propose a structure-prediction framework for proteins that uses hidden Markov models (HMM) with a protein structure grammar. By adopting a protein structure grammar, the HMM makes it possible to treat global interactions, the interaction between two secondary structures which are apart in the sequence. In this framework, prediction of local and global structures are totally treated through global and local interactions which are expressed by the protein sequence grammar. The relations between some of the previous methods for secondary structure prediction and HMMs are discussed. Some experimental results on secondary structure prediction are included. The learning algorithms for the HMMs are presented.

本文言語English
ホスト出版物のタイトルProceedings of the 26th Hawaii International Conference on System Sciences, HICSS 1993
出版社IEEE Computer Society
ページ783-791
ページ数9
ISBN(電子版)0818632305
DOI
出版ステータスPublished - 1993
外部発表はい
イベント26th Hawaii International Conference on System Sciences, HICSS 1993 - Wailea, United States
継続期間: 1993 1 8 → …

出版物シリーズ

名前Proceedings of the Annual Hawaii International Conference on System Sciences
1
ISSN(印刷版)1530-1605

Conference

Conference26th Hawaii International Conference on System Sciences, HICSS 1993
国/地域United States
CityWailea
Period93/1/8 → …

ASJC Scopus subject areas

  • 工学(全般)

フィンガープリント

「HMM with protein structure grammar」の研究トピックを掘り下げます。これらがまとまってユニークなフィンガープリントを構成します。

引用スタイル