Identifying anticancer peptides by using a generalized chaos game representation
type: Item
instance of: scholarly article
title: Identifying anticancer peptides by using a generalized chaos game representation
zbMATH Open document ID: 1410.92083
author: Li Ge
author: Jiaguo Liu
author: Yusen Zhang
author: Matthias Dehmer
published in: Journal of Mathematical Biology
publication date: 2019-03-29T00:00:00Z
Mathematics Subject Classification ID: 92D20
Mathematics Subject Classification ID: 92-08
Mathematics Subject Classification ID: 91A80
zbMATH DE Number: 7045243
zbMATH Keywords: chaos game representation
zbMATH Keywords: similarity analysis
zbMATH Keywords: anticancer peptides
zbMATH Keywords: support vector machine
describes a project that uses: e1071
describes a project that uses: LIBSVM
describes a project that uses: IsoRank
describes a project that uses: iACP
describes a project that uses: ape
describes a project that uses: ClustalW
describes a project that uses: Cd-hit
MaRDI profile type: Publication
full work available at URL: s00285-018-1279-x
OpenAlex ID: W2895742595
Wikidata QID: Q57022254
cites work: Support-vector networks
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cites work: Comparative analysis of protein primary sequences with graph energy
cites work: Prediction of protein structural classes by recurrence quantification analysis based on chaos game representation
cites work: Chaos game representation of protein sequences based on the detailed HP model and their multifractal and correlation analyses
cites work: A novel representation for apoptosis protein subcellular localization prediction using support vector machine
DOI: 10.1007/S00285-018-1279-X
description: scientific article; zbMATH DE number 7045243