pLoc\_bal-mGneg: predict subcellular localization of Gram-negative bacterial proteins by quasi-balancing training dataset and general PseAAC
type: Item
instance of: scholarly article
title: pLoc\_bal-mGneg: predict subcellular localization of Gram-negative bacterial proteins by quasi-balancing training dataset and general PseAAC
zbMATH Open document ID: 1406.92173
author: Xiang Cheng
author: Xuan Xiao
author: Kuo-Chen Chou
published in: Journal of Theoretical Biology
publication date: 2019-02-01T00:00:00Z
Mathematics Subject Classification ID: 92C40
Mathematics Subject Classification ID: 92C37
Mathematics Subject Classification ID: 62P10
zbMATH DE Number: 7010296
zbMATH Keywords: multi-label system
zbMATH Keywords: Gram-negative bacterial proteins
zbMATH Keywords: IHTS
zbMATH Keywords: five-step rules
zbMATH Keywords: ML-GKR
zbMATH Keywords: Chou's intuitive metrics
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pLoc\_bal-mGneg: predict subcellular localization of Gram-negative bacterial proteins by quasi-balancing training dataset and general PseAAC (describes a project that uses)
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pLoc\_bal-mGneg: predict subcellular localization of Gram-negative bacterial proteins by quasi-balancing training dataset and general PseAAC (describes a project that uses)
describes a project that uses: Gneg-mPLoc

pLoc\_bal-mGneg: predict subcellular localization of Gram-negative bacterial proteins by quasi-balancing training dataset and general PseAAC (describes a project that uses)
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pLoc\_bal-mGneg: predict subcellular localization of Gram-negative bacterial proteins by quasi-balancing training dataset and general PseAAC (describes a project that uses)
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pLoc\_bal-mGneg: predict subcellular localization of Gram-negative bacterial proteins by quasi-balancing training dataset and general PseAAC (describes a project that uses)
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pLoc\_bal-mGneg: predict subcellular localization of Gram-negative bacterial proteins by quasi-balancing training dataset and general PseAAC (describes a project that uses)
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pLoc\_bal-mGneg: predict subcellular localization of Gram-negative bacterial proteins by quasi-balancing training dataset and general PseAAC (describes a project that uses)
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pLoc\_bal-mGneg: predict subcellular localization of Gram-negative bacterial proteins by quasi-balancing training dataset and general PseAAC (MaRDI profile type)
MaRDI profile type: Publication

pLoc\_bal-mGneg: predict subcellular localization of Gram-negative bacterial proteins by quasi-balancing training dataset and general PseAAC (full work available at URL)
full work available at URL: j.jtbi.2018.09.005

pLoc\_bal-mGneg: predict subcellular localization of Gram-negative bacterial proteins by quasi-balancing training dataset and general PseAAC (OpenAlex ID)
OpenAlex ID: W2891918406

pLoc\_bal-mGneg: predict subcellular localization of Gram-negative bacterial proteins by quasi-balancing training dataset and general PseAAC (Wikidata QID)
Wikidata QID: Q91367801

pLoc\_bal-mGneg: predict subcellular localization of Gram-negative bacterial proteins by quasi-balancing training dataset and general PseAAC (cites work)
cites work: Classification of membrane protein types using voting feature interval in combination with Chou's pseudo amino acid composition

pLoc\_bal-mGneg: predict subcellular localization of Gram-negative bacterial proteins by quasi-balancing training dataset and general PseAAC (cites work)
cites work: IMem-2LSAAC: a two-level model for discrimination of membrane proteins and their types by extending the notion of SAAC into Chou's pseudo amino acid composition

pLoc\_bal-mGneg: predict subcellular localization of Gram-negative bacterial proteins by quasi-balancing training dataset and general PseAAC (cites work)
cites work: Using LogitBoost classifier to predict protein structural classes

pLoc\_bal-mGneg: predict subcellular localization of Gram-negative bacterial proteins by quasi-balancing training dataset and general PseAAC (cites work)
cites work: Q4533353

pLoc\_bal-mGneg: predict subcellular localization of Gram-negative bacterial proteins by quasi-balancing training dataset and general PseAAC (cites work)
cites work: Some remarks on protein attribute prediction and pseudo amino acid composition

pLoc\_bal-mGneg: predict subcellular localization of Gram-negative bacterial proteins by quasi-balancing training dataset and general PseAAC (cites work)
cites work: Gram-positive and Gram-negative protein subcellular localization by incorporating evolutionary-based descriptors into Chou's general PseAAC

pLoc\_bal-mGneg: predict subcellular localization of Gram-negative bacterial proteins by quasi-balancing training dataset and general PseAAC (cites work)
cites work: Using the concept of Chou's pseudo amino acid composition for risk type prediction of human papillomaviruses

pLoc\_bal-mGneg: predict subcellular localization of Gram-negative bacterial proteins by quasi-balancing training dataset and general PseAAC (cites work)
cites work: Predicting mycobacterial proteins subcellular locations by incorporating pseudo-average chemical shift into the general form of Chou's pseudo amino acid composition

pLoc\_bal-mGneg: predict subcellular localization of Gram-negative bacterial proteins by quasi-balancing training dataset and general PseAAC (cites work)
cites work: Use of fuzzy clustering technique and matrices to classify amino acids and its impact to Chou's pseudo amino acid composition

pLoc\_bal-mGneg: predict subcellular localization of Gram-negative bacterial proteins by quasi-balancing training dataset and general PseAAC (cites work)
cites work: Predicting anticancer peptides with Chou's pseudo amino acid composition and investigating their mutagenicity via ames test

pLoc\_bal-mGneg: predict subcellular localization of Gram-negative bacterial proteins by quasi-balancing training dataset and general PseAAC (cites work)
cites work: pSuc-Lys: predict lysine succinylation sites in proteins with PseAAC and ensemble random forest approach

pLoc\_bal-mGneg: predict subcellular localization of Gram-negative bacterial proteins by quasi-balancing training dataset and general PseAAC (cites work)
cites work: Prediction of \(\beta\)-lactamase and its class by Chou's pseudo-amino acid composition and support vector machine

pLoc\_bal-mGneg: predict subcellular localization of Gram-negative bacterial proteins by quasi-balancing training dataset and general PseAAC (cites work)
cites work: Predicting plant protein subcellular multi-localization by Chou's PseAAC formulation based multi-label homolog knowledge transfer learning

pLoc\_bal-mGneg: predict subcellular localization of Gram-negative bacterial proteins by quasi-balancing training dataset and general PseAAC (cites work)
cites work: Prediction of GABA\(_{\mathrm A}\) receptor proteins using the concept of Chou's pseudo-amino acid composition and support vector machine

pLoc\_bal-mGneg: predict subcellular localization of Gram-negative bacterial proteins by quasi-balancing training dataset and general PseAAC (cites work)
cites work: Chou's pseudo amino acid composition improves sequence-based antifreeze protein prediction

pLoc\_bal-mGneg: predict subcellular localization of Gram-negative bacterial proteins by quasi-balancing training dataset and general PseAAC (cites work)
cites work: Prediction of protein structure classes by incorporating different protein descriptors into general Chou's pseudo amino acid composition

pLoc\_bal-mGneg: predict subcellular localization of Gram-negative bacterial proteins by quasi-balancing training dataset and general PseAAC (cites work)
cites work: A novel feature representation method based on Chou's pseudo amino acid composition for protein structural class prediction

pLoc\_bal-mGneg: predict subcellular localization of Gram-negative bacterial proteins by quasi-balancing training dataset and general PseAAC (cites work)
cites work: Gneg-mPLoc: a top-down strategy to enhance the quality of predicting subcellular localization of Gram-negative bacterial proteins

pLoc\_bal-mGneg: predict subcellular localization of Gram-negative bacterial proteins by quasi-balancing training dataset and general PseAAC (cites work)
cites work: GOASVM: a subcellular location predictor by incorporating term-frequency gene ontology into the general form of Chou's pseudo-amino acid composition

pLoc\_bal-mGneg: predict subcellular localization of Gram-negative bacterial proteins by quasi-balancing training dataset and general PseAAC (cites work)
cites work: Predicting protein structural classes with pseudo amino acid composition: an approach using geometric moments of cellular automaton image

pLoc\_bal-mGneg: predict subcellular localization of Gram-negative bacterial proteins by quasi-balancing training dataset and general PseAAC (cites work)
cites work: Prediction of protein subcellular localization with oversampling approach and Chou's general PseAAC

pLoc\_bal-mGneg: predict subcellular localization of Gram-negative bacterial proteins by quasi-balancing training dataset and general PseAAC (cites work)
cites work: Using Chou's amphiphilic pseudo-amino acid composition and support vector machine for prediction of enzyme subfamily classes

pLoc\_bal-mGneg: predict subcellular localization of Gram-negative bacterial proteins by quasi-balancing training dataset and general PseAAC (DOI)
DOI: 10.1016/J.JTBI.2018.09.005

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