Predicting protein submitochondrial locations by incorporating the pseudo-position specific scoring matrix into the general Chou's pseudo-amino acid composition
type: Item
instance of: scholarly article
title: Predicting protein submitochondrial locations by incorporating the pseudo-position specific scoring matrix into the general Chou's pseudo-amino acid composition
zbMATH Open document ID: 1397.92228
author: Y. Aharonov
published in: Journal of Theoretical Biology
publication date: 2018-06-15T00:00:00Z
Mathematics Subject Classification ID: 92C40
Mathematics Subject Classification ID: 68T05
zbMATH DE Number: 6890064
zbMATH Keywords: submitochondrial locations
zbMATH Keywords: pseudo-amino acid composition
zbMATH Keywords: pseudo-position specific scoring matrix
zbMATH Keywords: two-dimensional wavelet denoising
zbMATH Keywords: support vector machine
zbMATH Keywords: machine learning
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describes a project that uses: GitHub
MaRDI profile type: Publication
full work available at URL: j.jtbi.2018.04.026
OpenAlex ID: W2802989292
Wikidata QID: Q52573597
cites work: Adaptive wavelet thresholding for image denoising and compression
cites work: Spatially adaptive wavelet thresholding with context modeling for image denoising
cites work: Some remarks on protein attribute prediction and pseudo amino acid composition
cites work: Fuzzy KNN for predicting membrane protein types from pseudo-amino acid composition
cites work: Q4856771
cites work: Prediction of protein submitochondria locations based on data fusion of various features of sequences
cites work: Using the augmented Chou's pseudo amino acid composition for predicting protein submitochondria locations based on auto covariance approach
cites work: Highly accurate prediction of protein self-interactions by incorporating the average block and PSSM information into the general PseAAC
cites work: Prediction of protein subcellular localization with oversampling approach and Chou's general PseAAC
DOI: 10.1016/J.JTBI.2018.04.026
description: scientific article; zbMATH DE number 6890064