内容紹介

Considerable attention has been paid to the functions of RNAs, especially those of regulatory non-coding RNAs. It is widely believed that there is a strong correlation between the 3D structure of an RNA molecule and its function. A set of base pairs is called a secondary structure, which shapes the substructure of the 3D structure. Since experimental determination of RNA 3D structures is difficult and their structures are hierarchical, secondary structure prediction provides a major key to elucidating the potential functions of RNAs. In the former part of the talk, we present IPknot, a novel computational method for predicting RNA secondary structures with pseudoknots based on maximizing expected accuracy of a predicted structure. Pseudoknots, found in secondary structures of a number of functional RNAs, play various roles in biological processes. The problem of maximizing expected accuracy is solved by using integer programming with threshold cut. IPknot is validated through extensive experiments on various

詳細情報

刊年

2011

形態

電子化映像資料(47分32秒)

シリーズ名

情報科学研究科・ゼミナール講演 ; 平成23年度

注記

講演者所属: 奈良先端科学技術大学院大学 情報科学研究科 計算メカニズム学研究室

講演日: 平成23年4月13日

講演場所: 情報科学研究科大講義室L1

標題言語

英語 (eng)

本文言語

日本語 (jpn)

著者情報

加藤, 有己 (カトウ, ユウキ)