Contents Intro.

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

Details

Publication year

2011

Form

電子化映像資料(47分32秒)

Series title

情報科学研究科・ゼミナール講演 ; 平成23年度

Note

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

Country of publication

Japan

Title language

English (eng)

Language of texts

Japanese (jpn)

Author information

加藤, 有己 (カトウ, ユウキ)