Improving SIM-based Annotation Method of Protein Sequence Using Support Vector Machine
スポンサーリンク
概要
- 論文の詳細を見る
In this paper, we present a protein sequence annotation system, named as MAPS (Multiple Annotation for Protein Sequences), which provides a mechanism to extract multiple annotations from various types of biological data including the SwissProt keywords, InterPro signatures and GO terms. Meanwhile, MAPS can automatically eliminate the error annotations by a pre-trained SVM classifier. It assigns an annotation to the input protein sequence by considering all hit proteins with this annotation entirely, not only single hit protein. The experimental results show that the error annotations can be eliminated effectively and keep high accuracy on different types of annotations.
- 日本知能情報ファジィ学会の論文
日本知能情報ファジィ学会 | 論文
- FCNによる自律エージェントの行動制御と行動解析 : タルタロス問題への応用
- コンフリクト, 迷いと意思決定(意思決定)
- 認知心理学における類似性研究(類似尺度と情報検索)
- アメリカ留学体験記
- 文脈への意味の位置付けを用いた対話システムとその評価(言語,テキストの知能情報処理)