POODLE-S: Web application for predicting protein disorder by using physicochemical features and reduced amino acid set of a position-specific scoring matrix

Kana Shimizu; Shuichi Hirose; Tamotsu Noguchi

doi:10.1093/bioinformatics/btm330

POODLE-S: Web application for predicting protein disorder by using physicochemical features and reduced amino acid set of a position-specific scoring matrix

Kana Shimizu^*, Shuichi Hirose, Tamotsu Noguchi

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

100 Citations (Scopus)

Abstract

Summary: Protein disorder is characterized by a lack of a stable 3D structure, and is considered to be involved in a number of important protein functions such as regulatory and signalling events. We developed a web application, the POODLE-S, which predicts the disordered region from amino acid sequences by using physicochemical features and reduced amino acid set of a position-specific scoring matrix.

Original language	English
Pages (from-to)	2337-2338
Number of pages	2
Journal	Bioinformatics
Volume	23
Issue number	17
DOIs	https://doi.org/10.1093/bioinformatics/btm330
Publication status	Published - 2007 Sept 1
Externally published	Yes

ASJC Scopus subject areas

Statistics and Probability
Biochemistry
Molecular Biology
Computer Science Applications
Computational Theory and Mathematics
Computational Mathematics

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10.1093/bioinformatics/btm330

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abstract = "Summary: Protein disorder is characterized by a lack of a stable 3D structure, and is considered to be involved in a number of important protein functions such as regulatory and signalling events. We developed a web application, the POODLE-S, which predicts the disordered region from amino acid sequences by using physicochemical features and reduced amino acid set of a position-specific scoring matrix.",

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POODLE-S: Web application for predicting protein disorder by using physicochemical features and reduced amino acid set of a position-specific scoring matrix

Abstract

ASJC Scopus subject areas

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