Chemogenomic approaches to infer drug-target interaction networks

Yoshihiro Yamanishi

研究成果: Chapter in Book/Report/Conference proceedingChapter

26 被引用数 (Scopus)

抄録

The identification of drug-target interactions from heterogeneous biological data is critical in the drug development. In this chapter, we review recently developed in silico chemogenomic approaches to infer unknown drug-target interactions from chemical information of drugs and genomic information of target proteins. We review several kernel-based statistical methods from two different viewpoints: binary classification and dimension reduction. In the results, we demonstrate the usefulness of the methods on the prediction of drug-target interactions from chemical structure data and genomic sequence data. We also discuss the characteristics of each method, and show some perspectives toward future research direction.

本文言語英語
ホスト出版物のタイトルData Mining for Systems Biology: Methods and Protocols
ページ97-113
ページ数17
939
DOI
出版ステータス出版済み - 2013
外部発表はい

出版物シリーズ

名前Methods in Molecular Biology
939
ISSN(印刷版)10643745

All Science Journal Classification (ASJC) codes

  • 分子生物学
  • 遺伝学

フィンガープリント

「Chemogenomic approaches to infer drug-target interaction networks」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