Predicting mycobacterial proteins subcellular locations by incorporating pseudo-average chemical shift into the general form of Chou's pseudo amino acid composition

DOI10.1016/J.JTBI.2012.03.017zbMath1397.92186OpenAlexW1993791542WikidataQ44499984 ScholiaQ44499984MaRDI QIDQ1784371

Qian-Zhong Li, Guo-Liang Fan

Publication date: 26 September 2018

Published in: Journal of Theoretical Biology (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jtbi.2012.03.017

zbMATH Keywords

Mycobacterium tuberculosisaverage chemical shiftevolutionary informationjackknife validationreduced amino acids

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Learning and adaptive systems in artificial intelligence (68T05) Biochemistry, molecular biology (92C40) Cell biology (92C37)

Related Items (12)

Prediction of posttranslational modification sites from amino acid sequences with kernel methods ⋮ Detrended cross-correlation coefficient: application to predict apoptosis protein subcellular localization ⋮ Gram-positive and Gram-negative protein subcellular localization by incorporating evolutionary-based descriptors into Chou's general PseAAC ⋮ Human proteins characterization with subcellular localizations ⋮ pLoc\_bal-mGneg: predict subcellular localization of Gram-negative bacterial proteins by quasi-balancing training dataset and general PseAAC ⋮ Identify Gram-negative bacterial secreted protein types by incorporating different modes of PSSM into Chou's general PseAAC via Kullback-Leibler divergence ⋮ Protein space: a natural method for realizing the nature of protein universe ⋮ An extension of fuzzy topological approach for comparison of genetic sequences ⋮ Bi-PSSM: position specific scoring matrix based intelligent computational model for identification of mycobacterial membrane proteins ⋮ Alignment free comparison: \(k\) word voting model and its applications ⋮ Discriminating bioluminescent proteins by incorporating average chemical shift and evolutionary information into the general form of Chou's pseudo amino acid composition ⋮ R3P-Loc: a compact multi-label predictor using ridge regression and random projection for protein subcellular localization

Uses Software

• LIBSVM
• Cell-PLoc
• Memtype-2L
• Porter
• UniProt
• iLoc-Virus
• iLoc-Gpos
• iLoc-Plant
• iLoc-Hum
• iLoc-Euk
• AFP-Pred
• SecretP
• Euk-mPLoc

Cites Work

• Unnamed Item
• Use of fuzzy clustering technique and matrices to classify amino acids and its impact to Chou's pseudo amino acid composition
• Using the augmented Chou's pseudo amino acid composition for predicting protein submitochondria locations based on auto covariance approach
• Predicting membrane protein types by fusing composite protein sequence features into pseudo amino acid composition
• Some remarks on protein attribute prediction and pseudo amino acid composition
• Using the concept of Chou's pseudo amino acid composition for risk type prediction of human papillomaviruses
• SecretP: identifying bacterial secreted proteins by fusing new features into Chou's pseudo-amino acid composition
• Prediction of GABA\(_{\mathrm A}\) receptor proteins using the concept of Chou's pseudo-amino acid composition and support vector machine
• Knowledge-based virtual screening of HLA-A*0201-restricted CD8\(^+\) T-cell epitope peptides from herpes simplex virus genome
• \textbf{iLoc-Virus}: a multi-label learning classifier for identifying the subcellular localization of virus proteins with both single and multiple sites
• The modified Mahalanobis discriminant for predicting outer membrane proteins by using Chou's pseudo amino acid composition
• Identify catalytic triads of serine hydrolases by support vector machines
• Prediction of apoptosis protein subcellular location using improved hybrid approach and pseudo-amino acid composition
• Using Chou's amphiphilic pseudo-amino acid composition and support vector machine for prediction of enzyme subfamily classes
• Predicting ion channels and their types by the dipeptide mode of pseudo amino acid composition
• Prediction of protein submitochondria locations based on data fusion of various features of sequences

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