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Using optimized evidence-theoretic K-nearest neighbor classifier and pseudo-amino acid composition to predict membrane protein types
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Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1002/(sici)1097-0134(19990101)34:1<137::aid-prot11>3.0.co;2-oopenalex-snapshot
Prediction of membrane protein types and subcellular locations
inferredcites →https://doi.org/10.1002/1097-0282(20010415)58:5<491::aid-bip1024>3.0.co;2-iopenalex-snapshot
Prediction of the subcellular location of prokaryotic proteins based on a new representation of the amino acid composition
inferredcites →https://doi.org/10.1002/jcb.10719openalex-snapshot
Prediction and classification of protein subcellular location—sequence‐order effect and pseudo amino acid composition
inferredcites →https://doi.org/10.1002/prot.10251openalex-snapshot
Subcellular location prediction of apoptosis proteins
inferredcites →https://doi.org/10.1002/prot.1035openalex-snapshot
Prediction of protein cellular attributes using pseudo‐amino acid composition
inferredcites →https://doi.org/10.1002/prot.10500openalex-snapshot
Predicting protein quaternary structure by pseudo amino acid composition
inferredcites →https://doi.org/10.1002/prot.1071openalex-snapshot
Some insights into protein structural class prediction
inferredcites →https://doi.org/10.1002/prot.340210406openalex-snapshot
A novel approach to predicting protein structural classes in a (20–1)‐D amino acid composition space
inferredcites →https://doi.org/10.1006/jmbi.1996.0804openalex-snapshot
Relation between amino acid composition and cellular location of proteins 1 1Edited by F. E. Cohen
inferredcites →https://doi.org/10.1006/jtbi.1993.1053openalex-snapshot
A Joint Prediction of the Folding Types of 1490 Human Proteins from their Genetic Codons
inferredcites →https://doi.org/10.1007/978-1-4613-1571-1openalex-snapshot
Prediction of Protein Structure and the Principles of Protein Conformation
inferredcites →https://doi.org/10.1007/978-3-540-44792-4_29openalex-snapshot
A k-Nearest Neighbor Classification Rule Based on Dempster-Shafer Theory
inferredcites →https://doi.org/10.1007/s00726-004-0148-7openalex-snapshot
Using complexity measure factor to predict protein subcellular location
inferredcites →https://doi.org/10.1007/s00726-004-0154-9openalex-snapshot
Using cellular automata to generate image representation for biological sequences
inferredcites →https://doi.org/10.1016/0968-0004(93)90025-iopenalex-snapshot
Molecular biology of the cell
inferredcites →https://doi.org/10.1016/j.bbrc.2004.07.059openalex-snapshot
Predicting protein structural class by functional domain composition
inferredcites →https://doi.org/10.1016/j.bbrc.2004.12.069openalex-snapshot
Using GO-PseAA predictor to identify membrane proteins and their types
inferredcites →https://doi.org/10.1016/j.jtbi.2003.08.015openalex-snapshot
Application of SVM to predict membrane protein types
inferredcites →https://doi.org/10.1016/j.jtbi.2004.07.023openalex-snapshot
SLLE for predicting membrane protein types
inferredcites →https://doi.org/10.1016/s0006-3495(03)70050-2openalex-snapshot
Support Vector Machines for Predicting Membrane Protein Types by Using Functional Domain Composition
inferredcites →https://doi.org/10.1016/s0021-9258(17)31748-9openalex-snapshot
Predicting protein folding types by distance functions that make allowances for amino acid interactions.
inferredcites →https://doi.org/10.1016/s0065-3233(00)54009-1openalex-snapshot
Protein sorting signals and prediction of subcellular localization
inferredcites →https://doi.org/10.1016/s0968-0004(98)01336-xopenalex-snapshot
PSORT: a program for detecting sorting signals in proteins and predicting their subcellular localization
inferredcites →https://doi.org/10.1021/ci049686vopenalex-snapshot
Prediction of Membrane Protein Types by Incorporating Amphipathic Effects
inferredcites →https://doi.org/10.1021/pr025527kopenalex-snapshot
Bioinformatical Analysis of G-Protein-Coupled Receptors
inferredcites →https://doi.org/10.1021/pr0255710openalex-snapshot
Prediction of Enzyme Family Classes
inferredcites →https://doi.org/10.1023/a:1007091128394openalex-snapshot
Prediction of Membrane Protein Types Based on the Hydrophobic Index of Amino Acids
inferredcites →https://doi.org/10.1023/a:1020713915365openalex-snapshot
An Intriguing Controversy over Protein Structural Class Prediction
inferredcites →https://doi.org/10.1023/a:1025350409648openalex-snapshot
Application of Pseudo Amino Acid Composition for Predicting Protein Subcellular Location: Stochastic Signal Processing Approach
inferredcites →https://doi.org/10.1074/jbc.m204161200openalex-snapshot
Using Functional Domain Composition and Support Vector Machines for Prediction of Protein Subcellular Location
inferredcites →https://doi.org/10.1080/07391102.2001.10506692openalex-snapshot
Artificial Neural Network Model for Predicting Membrane Protein Types
inferredcites →https://doi.org/10.1093/bioinformatics/bth466openalex-snapshot
Using amphiphilic pseudo amino acid composition to predict enzyme subfamily classes
inferredcites →https://doi.org/10.1093/bioinformatics/bti104openalex-snapshot
Predicting protein localization in budding Yeast
inferredcites →https://doi.org/10.1093/nar/25.1.31openalex-snapshot
The SWISS-PROT protein sequence data bank and its supplement TrEMBL
inferredcites →https://doi.org/10.1093/oxfordjournals.jbchem.a135454openalex-snapshot
The Folding Type of a Protein Is Relevant to the Amino Acid Composition
inferredcites →https://doi.org/10.1093/protein/11.7.523openalex-snapshot
Domain structural class prediction
inferredcites →https://doi.org/10.1093/protein/12.2.107openalex-snapshot
Protein subcellular location prediction
inferredcites →https://doi.org/10.1093/protein/15.9.713openalex-snapshot
A study on the correlation of G-protein-coupled receptor types with amino acid composition
inferredcites →https://doi.org/10.1093/protein/gzh061openalex-snapshot
Weighted-support vector machines for predicting membrane protein types based on pseudo-amino acid composition
inferredcites →https://doi.org/10.1109/21.376493openalex-snapshot
A k-nearest neighbor classification rule based on Dempster-Shafer theory
inferredcites →https://doi.org/10.1109/5326.669565openalex-snapshot
An evidence-theoretic k-NN rule with parameter optimization
inferredcites →https://doi.org/10.1109/tit.1967.1053964openalex-snapshot
Nearest neighbor pattern classification
inferredcites →https://doi.org/10.1110/ps.04981104openalex-snapshot
Predicting enzyme family class in a hybridization space
inferredcites →https://doi.org/10.2174/1389203003381379openalex-snapshot
Prediction of Protein Structural Classes and Subcellular Locations
inferredcites →https://doi.org/10.2307/2530789openalex-snapshot
Encyclopedia of Statistical Sciences 2.
inferredcites →https://doi.org/10.2307/j.ctv10vm1qbopenalex-snapshot
A Mathematical Theory of Evidence
inferredcites →https://doi.org/10.3109/10409239509083488openalex-snapshot
Prediction of Protein Structural Classes
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.2139/ssrn.4681929openalex-extracted
Modelling Spatiotemporal Variability of Solar Radiation Over Ethiopia
inferred← citeshttps://doi.org/10.1002/jcb.20879openalex-snapshot
Predicting protein subcellular location by fusing multiple classifiers
inferred← citeshttps://doi.org/10.1002/jcb.21096openalex-snapshot
Large‐scale plant protein subcellular location prediction
inferred← citeshttps://doi.org/10.1002/jcc.20354openalex-snapshot
Using pseudo amino acid composition to predict protein structural classes: Approached with complexity measure factor
inferred← citeshttps://doi.org/10.1002/jcc.20369openalex-snapshot
Heuristic molecular lipophilicity potential (HMLP): Lipophilicity and hydrophilicity of amino acid side chains
inferred← citeshttps://doi.org/10.1002/jcc.20955openalex-snapshot
Using grey dynamic modeling and pseudo amino acid composition to predict protein structural classes
inferred← citeshttps://doi.org/10.1002/jcc.21053openalex-snapshot
Prediction of integral membrane protein type by collocated hydrophobic amino acid pairs
inferred← citeshttps://doi.org/10.1002/jcc.21163openalex-snapshot
GPCR‐CA: A cellular automaton image approach for predicting G‐protein–coupled receptor functional classes
inferred← citeshttps://doi.org/10.1002/pmic.200600064openalex-snapshot
GNBSL: A new integrative system to predict the subcellular location for Gram‐negative bacteria proteins
inferred← citeshttps://doi.org/10.1002/pmic.200700638openalex-snapshot
Proteomics, networks and connectivity indices
inferred← citeshttps://doi.org/10.1002/prot.20898openalex-snapshot
Predicting protease types by hybridizing gene ontology and pseudo amino acid composition
inferred← citeshttps://doi.org/10.1002/widm.1248openalex-snapshot
Machine learning for bioinformatics and neuroimaging
inferred← citeshttps://doi.org/10.1007/s00232-016-9937-7openalex-snapshot
A Treatise to Computational Approaches Towards Prediction of Membrane Protein and Its Subtypes
inferred← citeshttps://doi.org/10.1007/s00607-018-0682-xopenalex-snapshot
Identification of hormone-binding proteins using a novel ensemble classifier
inferred← citeshttps://doi.org/10.1007/s00726-006-0332-zopenalex-snapshot
Classifying G protein-coupled receptors and nuclear receptors on the basis of protein power spectrum from fast Fourier transform
inferred← citeshttps://doi.org/10.1007/s00726-006-0341-yopenalex-snapshot
Delaunay triangulation with partial least squares projection to latent structures: a model for G-protein coupled receptors classification and fast structure recognition
inferred← citeshttps://doi.org/10.1007/s00726-006-0465-0openalex-snapshot
Prediction of mitochondrial proteins based on genetic algorithm – partial least squares and support vector machine
inferred← citeshttps://doi.org/10.1007/s00726-006-0475-yopenalex-snapshot
Prediction of protein subcellular localization by support vector machines using multi-scale energy and pseudo amino acid composition
inferred← citeshttps://doi.org/10.1007/s00726-006-0478-8openalex-snapshot
Euk-PLoc: an ensemble classifier for large-scale eukaryotic protein subcellular location prediction
inferred← citeshttps://doi.org/10.1007/s00726-007-0010-9openalex-snapshot
Using the concept of Chou’s pseudo amino acid composition to predict protein subcellular localization: an approach by incorporating evolutionary information and von Neumann entropies
inferred← citeshttps://doi.org/10.1007/s00726-007-0016-3openalex-snapshot
Combing ontologies and dipeptide composition for predicting DNA-binding proteins
inferred← citeshttps://doi.org/10.1007/s00726-007-0496-1openalex-snapshot
Using pseudo amino acid composition and binary-tree support vector machines to predict protein structural classes
inferred← citeshttps://doi.org/10.1007/s00726-007-0550-zopenalex-snapshot
Using pseudo amino acid composition to predict transmembrane regions in protein: cellular automata and Lempel-Ziv complexity
inferred← citeshttps://doi.org/10.1007/s00726-007-0568-2openalex-snapshot
Predicting DNA-binding proteins: approached from Chou’s pseudo amino acid composition and other specific sequence features
inferred← citeshttps://doi.org/10.1007/s00726-007-0616-yopenalex-snapshot
AAIndexLoc: predicting subcellular localization of proteins based on a new representation of sequences using amino acid indices
inferred← citeshttps://doi.org/10.1007/s00726-007-0623-zopenalex-snapshot
Using pseudo amino acid composition to predict protein subcellular location: approached with amino acid composition distribution
inferred← citeshttps://doi.org/10.1007/s00726-007-0628-7openalex-snapshot
Discrimination of outer membrane proteins using a K-nearest neighbor method
inferred← citeshttps://doi.org/10.1007/s00726-008-0044-7openalex-snapshot
An ensemble of reduced alphabets with protein encoding based on grouped weight for predicting DNA-binding proteins
inferred← citeshttps://doi.org/10.1007/s00726-008-0077-yopenalex-snapshot
Protein function prediction with high-throughput data
inferred← citeshttps://doi.org/10.1007/s00726-008-0084-zopenalex-snapshot
Prediction of protein structure class by coupling improved genetic algorithm and support vector machine
inferred← citeshttps://doi.org/10.1007/s00726-008-0170-2openalex-snapshot
Prediction of protein structural classes by Chou’s pseudo amino acid composition: approached using continuous wavelet transform and principal component analysis
inferred← citeshttps://doi.org/10.1007/s00726-009-0292-1openalex-snapshot
Using K-minimum increment of diversity to predict secretory proteins of malaria parasite based on groupings of amino acids
inferred← citeshttps://doi.org/10.1007/s00726-009-0362-4openalex-snapshot
Using auto covariance method for functional discrimination of membrane proteins based on evolution information
inferred← citeshttps://doi.org/10.1007/s00726-012-1374-zopenalex-snapshot
A similarity distance of diversity measure for discriminating mesophilic and thermophilic proteins
inferred← citeshttps://doi.org/10.1007/s10930-005-7592-4openalex-snapshot
Using Fourier Spectrum Analysis and Pseudo Amino Acid Composition for Prediction of Membrane Protein Types
inferred← citeshttps://doi.org/10.1007/s10989-019-09910-7openalex-snapshot
Proposing Pseudo Amino Acid Components is an Important Milestone for Proteome and Genome Analyses
inferred← citeshttps://doi.org/10.1007/s10989-020-10087-7openalex-snapshot
Using Chou’s Five-steps Rule to Classify and Predict Glutathione S-transferases with Different Machine Learning Algorithms and Pseudo Amino Acid Composition
inferred← citeshttps://doi.org/10.1007/s10989-021-10170-7openalex-snapshot
iDRP-PseAAC: Identification of DNA Replication Proteins Using General PseAAC and Position Dependent Features
inferred← citeshttps://doi.org/10.1007/s11030-009-9134-zopenalex-snapshot
Using the nonlinear dimensionality reduction method for the prediction of subcellular localization of Gram-negative bacterial proteins
inferred← citeshttps://doi.org/10.1007/s11033-018-4391-5openalex-snapshot
Predicting membrane proteins and their types by extracting various sequence features into Chou’s general PseAAC
inferred← citeshttps://doi.org/10.1007/s11033-019-04680-3openalex-snapshot
Employing a novel 2-gram subgroup intra pattern (2GSIP) with stacked auto encoder for membrane protein classification
inferred← citeshttps://doi.org/10.1007/s11042-024-19010-4openalex-snapshot
Triplet encoded sequence based membrane protein classification using BiLSTM
inferred← citeshttps://doi.org/10.1007/s12524-020-01154-zopenalex-snapshot
Comparison of Six Machine Learning Methods for Estimating PM2.5 Concentration Using the Himawari-8 Aerosol Optical Depth
inferred← citeshttps://doi.org/10.1007/s41870-021-00650-wopenalex-snapshot
Cardiovascular risk assessment using data mining inferencing and feature engineering techniques
inferred← citeshttps://doi.org/10.1016/j.ab.2006.07.022openalex-snapshot
Predicting protein structural class with pseudo-amino acid composition and support vector machine fusion network
inferred← citeshttps://doi.org/10.1016/j.ab.2007.10.012openalex-snapshot
PseAAC: A flexible web server for generating various kinds of protein pseudo amino acid composition
inferred← citeshttps://doi.org/10.1016/j.ab.2008.10.020openalex-snapshot
Identification of proteases and their types
inferred← citeshttps://doi.org/10.1016/j.ab.2009.01.018openalex-snapshot
Prediction of nuclear receptors with optimal pseudo amino acid composition
inferred← citeshttps://doi.org/10.1016/j.ab.2009.10.040openalex-snapshot
Improving discrimination of outer membrane proteins by fusing different forms of pseudo amino acid composition
inferred← citeshttps://doi.org/10.1016/j.ab.2012.02.007openalex-snapshot
Mem-PHybrid: Hybrid features-based prediction system for classifying membrane protein types
inferred← citeshttps://doi.org/10.1016/j.ab.2014.06.022openalex-snapshot
iTIS-PseTNC: A sequence-based predictor for identifying translation initiation site in human genes using pseudo trinucleotide composition
inferred← citeshttps://doi.org/10.1016/j.ab.2014.12.009openalex-snapshot
iDNA-Methyl: Identifying DNA methylation sites via pseudo trinucleotide composition
inferred← citeshttps://doi.org/10.1016/j.ab.2018.06.011openalex-snapshot
Classifying the molecular functions of Rab GTPases in membrane trafficking using deep convolutional neural networks
inferred← citeshttps://doi.org/10.1016/j.ab.2018.10.027openalex-snapshot
Prediction of membrane protein types by exploring local discriminative information from evolutionary profiles
inferred← citeshttps://doi.org/10.1016/j.ab.2020.113845openalex-snapshot
Classification of membrane protein using Tetra Peptide Pattern
inferred← citeshttps://doi.org/10.1016/j.aca.2009.08.022openalex-snapshot
Multi-target spectral moment: QSAR for antiviral drugs vs. different viral species
inferred← citeshttps://doi.org/10.1016/j.aquaculture.2026.744417openalex-snapshot
AquaLNCRpred: A sequence-based framework for lncRNA prediction across diverse aquaculture species
inferred← citeshttps://doi.org/10.1016/j.artmed.2019.07.005openalex-snapshot
Accurate prediction of potential druggable proteins based on genetic algorithm and Bagging-SVM ensemble classifier
inferred← citeshttps://doi.org/10.1016/j.bbrc.2005.10.046openalex-snapshot
Prediction of protein signal sequences and their cleavage sites by statistical rulers
inferred← citeshttps://doi.org/10.1016/j.bbrc.2005.10.196openalex-snapshot
Prediction of protease types in a hybridization space
inferred← citeshttps://doi.org/10.1016/j.bbrc.2006.12.004openalex-snapshot
Using amino acid and peptide composition to predict membrane protein types
inferred← citeshttps://doi.org/10.1016/j.bbrc.2007.02.040openalex-snapshot
Prediction of protein crystallization using collocation of amino acid pairs
inferred← citeshttps://doi.org/10.1016/j.bbrc.2007.03.162openalex-snapshot
Signal-CF: A subsite-coupled and window-fusing approach for predicting signal peptides
inferred← citeshttps://doi.org/10.1016/j.bbrc.2007.06.027openalex-snapshot
MemType-2L: A Web server for predicting membrane proteins and their types by incorporating evolution information through Pse-PSSM
inferred← citeshttps://doi.org/10.1016/j.bbrc.2007.08.140openalex-snapshot
Signal-3L: A 3-layer approach for predicting signal peptides
inferred← citeshttps://doi.org/10.1016/j.biochi.2013.12.021openalex-snapshot
High-accuracy prediction of protein structural classes using PseAA structural properties and secondary structural patterns
inferred← citeshttps://doi.org/10.1016/j.bmc.2008.10.004openalex-snapshot
Quantitative Proteome–Property Relationships (QPPRs). Part 1: Finding biomarkers of organic drugs with mean Markov connectivity indices of spiral networks of blood mass spectra
inferred← citeshttps://doi.org/10.1016/j.bmc.2010.01.068openalex-snapshot
Multi-target spectral moment QSAR versus ANN for antiparasitic drugs against different parasite species
inferred← citeshttps://doi.org/10.1016/j.bpc.2007.03.006openalex-snapshot
Novel two-stage hybrid neural discriminant model for predicting proteins structural classes
inferred← citeshttps://doi.org/10.1016/j.chemolab.2011.06.007openalex-snapshot
A two-stage method for O-glycosylation site prediction
inferred← citeshttps://doi.org/10.1016/j.chemolab.2019.103919openalex-snapshot
RBPro-RF: Use Chou’s 5-steps rule to predict RNA-binding proteins via random forest with elastic net
inferred← citeshttps://doi.org/10.1016/j.chemolab.2022.104623openalex-snapshot
PredAoDP: Accurate identification of antioxidant proteins by fusing different descriptors based on evolutionary information with support vector machine
inferred← citeshttps://doi.org/10.1016/j.ejmech.2009.04.040openalex-snapshot
Multi-target spectral moment: QSAR for antifungal drugs vs. different fungi species
inferred← citeshttps://doi.org/10.1016/j.genrep.2018.07.012openalex-snapshot
Enhanced Artificial Neural Network for Protein Fold Recognition and Structural Class Prediction
inferred← citeshttps://doi.org/10.1016/j.ijar.2019.07.009openalex-snapshot
A new evidential K-nearest neighbor rule based on contextual discounting with partially supervised learning
inferred← citeshttps://doi.org/10.1016/j.jprot.2012.09.006openalex-snapshot
Identification of mycobacterial membrane proteins and their types using over-represented tripeptide compositions
inferred← citeshttps://doi.org/10.1016/j.jtbi.2006.05.006openalex-snapshot
Using stacked generalization to predict membrane protein types based on pseudo-amino acid composition
inferred← citeshttps://doi.org/10.1016/j.jtbi.2006.06.025openalex-snapshot
Using pseudo-amino acid composition and support vector machine to predict protein structural class
inferred← citeshttps://doi.org/10.1016/j.jtbi.2007.05.017openalex-snapshot
Novel scales based on hydrophobicity indices for secondary protein structure
inferred← citeshttps://doi.org/10.1016/j.jtbi.2007.06.001openalex-snapshot
Using Chou's amphiphilic pseudo-amino acid composition and support vector machine for prediction of enzyme subfamily classes
inferred← citeshttps://doi.org/10.1016/j.jtbi.2007.09.006openalex-snapshot
Adaptation of model proteins from cold to hot environments involves continuous and small adjustments of average parameters related to amino acid composition
inferred← citeshttps://doi.org/10.1016/j.jtbi.2007.09.014openalex-snapshot
Prediction protein structural classes with pseudo-amino acid composition: Approximate entropy and hydrophobicity pattern
inferred← citeshttps://doi.org/10.1016/j.jtbi.2008.03.009openalex-snapshot
Predicting protein structural class based on multi-features fusion
inferred← citeshttps://doi.org/10.1016/j.jtbi.2008.07.012openalex-snapshot
Prediction of membrane protein types by means of wavelet analysis and cascaded neural networks
inferred← citeshttps://doi.org/10.1016/j.jtbi.2008.11.003openalex-snapshot
Use of fuzzy clustering technique and matrices to classify amino acids and its impact to Chou's pseudo amino acid composition
inferred← citeshttps://doi.org/10.1016/j.jtbi.2009.08.004openalex-snapshot
SubChlo: Predicting protein subchloroplast locations with pseudo-amino acid composition and the evidence-theoretic K-nearest neighbor (ET-KNN) algorithm
inferred← citeshttps://doi.org/10.1016/j.jtbi.2010.08.010openalex-snapshot
A study of entropy/clarity of genetic sequences using metric spaces and fuzzy sets
inferred← citeshttps://doi.org/10.1016/j.jtbi.2010.12.024openalex-snapshot
Some remarks on protein attribute prediction and pseudo amino acid composition
inferred← citeshttps://doi.org/10.1016/j.jtbi.2013.11.017openalex-snapshot
A two-stage SVM method to predict membrane protein types by incorporating amino acid classifications and physicochemical properties into a general form of Chou's PseAAC
inferred← citeshttps://doi.org/10.1016/j.jtbi.2013.12.015openalex-snapshot
Prediction of protein structure classes using hybrid space of multi-profile Bayes and bi-gram probability feature spaces
inferred← citeshttps://doi.org/10.1016/j.jtbi.2014.09.032openalex-snapshot
A two-layer classification framework for protein fold recognition
inferred← citeshttps://doi.org/10.1016/j.jtbi.2016.05.011openalex-snapshot
Machine learning approaches for discrimination of Extracellular Matrix proteins using hybrid feature space
inferred← citeshttps://doi.org/10.1016/j.jtbi.2016.12.004openalex-snapshot
Unb-DPC: Identify mycobacterial membrane protein types by incorporating un-biased dipeptide composition into Chou's general PseAAC
inferred← citeshttps://doi.org/10.1016/j.jtbi.2017.09.013openalex-snapshot
Bi-PSSM: Position specific scoring matrix based intelligent computational model for identification of mycobacterial membrane proteins
inferred← citeshttps://doi.org/10.1016/j.jtbi.2017.09.018openalex-snapshot
Predicting membrane protein types using various decision tree classifiers based on various modes of general PseAAC for imbalanced datasets
inferred← citeshttps://doi.org/10.1016/j.jtbi.2018.07.032openalex-snapshot
Predicting membrane protein types by incorporating a novel feature set into Chou's general PseAAC
inferred← citeshttps://doi.org/10.1016/j.jtbi.2019.04.019openalex-snapshot
Prediction of antioxidant proteins by incorporating statistical moments based features into Chou's PseAAC
inferred← citeshttps://doi.org/10.1016/j.knosys.2015.08.007openalex-snapshot
EK-NNclus: A clustering procedure based on the evidential K-nearest neighbor rule
inferred← citeshttps://doi.org/10.1016/j.neucom.2012.11.058openalex-snapshot
Predicting pupylation sites in prokaryotic proteins using pseudo-amino acid composition and extreme learning machine
inferred← citeshttps://doi.org/10.1016/j.talanta.2006.09.015openalex-snapshot
Prediction of protein secondary structure content using support vector machine
inferred← citeshttps://doi.org/10.1016/j.ymeth.2024.05.014openalex-snapshot
APLpred: A machine learning-based tool for accurate prediction and characterization of asparagine peptide lyases using sequence-derived optimal features
inferred← citeshttps://doi.org/10.1021/pr050331gopenalex-snapshot
Predicting Protein−Protein Interactions from Sequences in a Hybridization Space
inferred← citeshttps://doi.org/10.1021/pr060404bopenalex-snapshot
Large-Scale Predictions of Gram-Negative Bacterial Protein Subcellular Locations
inferred← citeshttps://doi.org/10.1039/c5mb00155bopenalex-snapshot
Pseudo nucleotide composition or PseKNC: an effective formulation for analyzing genomic sequences
inferred← citeshttps://doi.org/10.1039/c8ra06311gopenalex-snapshot
Screening of cytochrome P450 3A4 inhibitors via in silico and in vitro approaches
inferred← citeshttps://doi.org/10.1080/03081079.2010.544870openalex-snapshot
Prediction of membrane protein types using maximum variance projection
inferred← citeshttps://doi.org/10.1080/07391102.2006.10507088openalex-snapshot
Amino Acid Principal Component Analysis (AAPCA) and its Applications in Protein Structural Class Prediction
inferred← citeshttps://doi.org/10.1080/07391102.2010.10507351openalex-snapshot
Virus-mPLoc: A Fusion Classifier for Viral Protein Subcellular Location Prediction by Incorporating Multiple Sites
inferred← citeshttps://doi.org/10.1080/07391102.2014.968624openalex-snapshot
Identification of DNA-binding proteins by incorporating evolutionary information into pseudo amino acid composition via the top-n-gram approach
inferred← citeshttps://doi.org/10.1093/bib/bbw021openalex-snapshot
Prediction and identification of the effectors of heterotrimeric G proteins in rice (Oryza sativaL.)
inferred← citeshttps://doi.org/10.1093/bib/bbx164openalex-snapshot
Systematic analysis and prediction of type IV secreted effector proteins by machine learning approaches
inferred← citeshttps://doi.org/10.1093/bioinformatics/btl170openalex-snapshot
Ensemble classifier for protein fold pattern recognition
inferred← citeshttps://doi.org/10.1093/protein/gzl053openalex-snapshot
Gpos-PLoc: an ensemble classifier for predicting subcellular localization of Gram-positive bacterial proteins
inferred← citeshttps://doi.org/10.1093/protein/gzp057openalex-snapshot
GPCR-GIA: a web-server for identifying G-protein coupled receptors and their families with grey incidence analysis
inferred← citeshttps://doi.org/10.1109/bmei.2008.86openalex-snapshot
Prediction of Membrane Protein Types by an Ensemble Classifier Based on Pseudo Amino Acid Composition and Approximate Entropy
inferred← citeshttps://doi.org/10.1109/bmei.2009.5305127openalex-snapshot
Prediction of Membrane Protein Types by Using Support Vector Machine Based on Composite Vector
inferred← citeshttps://doi.org/10.1109/bmei.2010.5639329openalex-snapshot
Application of protein Hasse matrix image to predict protein structural classes
inferred← citeshttps://doi.org/10.1109/cisp-bmei.2017.8302278openalex-snapshot
An ensemble classifier based on stacked generalization for predicting membrane protein types
inferred← citeshttps://doi.org/10.1109/fbit.2007.21openalex-snapshot
Classification of Cell Membrane Proteins
inferred← citeshttps://doi.org/10.1109/iccis54243.2021.9676407openalex-snapshot
Discriminating plasma membrane, internal membrane, and organelle membrane proteins by SVM
inferred← citeshttps://doi.org/10.1109/icife.2010.5609266openalex-snapshot
Predicting protein structural classes with pseudo amino acid composition: A new approach using geometric moments of distance matrix image
inferred← citeshttps://doi.org/10.1109/ihmsc.2010.127openalex-snapshot
Supervised Dimensionality Reduction Method for Predicting Membrane Proteins Types
inferred← citeshttps://doi.org/10.1109/tcbbio.2025.3540588openalex-snapshot
TP-ML: A Machine-Learning-Based Tool to Identify Threonine Proteases Using Sequence-Derived Optimal Features
inferred← citeshttps://doi.org/10.1109/tkde.2022.3157346openalex-snapshot
A Sparse Reconstructive Evidential -Nearest Neighbor Classifier for High-dimensional Data
inferred← citeshttps://doi.org/10.1109/tsm.2014.2374339openalex-snapshot
Fault Detection Using Random Projections and k-Nearest Neighbor Rule for Semiconductor Manufacturing Processes
inferred← citeshttps://doi.org/10.1109/tsmcb.2006.877795openalex-snapshot
Classification Using Belief Functions: Relationship Between Case-Based and Model-Based Approaches
inferred← citeshttps://doi.org/10.1110/ps.037762.108openalex-snapshot
Amino acid composition and protein dimension
inferred← citeshttps://doi.org/10.1155/2014/286419openalex-snapshot
iCTX-Type: A Sequence-Based Predictor for Identifying the Types of Conotoxins in Targeting Ion Channels
inferred← citeshttps://doi.org/10.1155/2016/1654623openalex-snapshot
Identification of Bacterial Cell Wall Lyases via Pseudo Amino Acid Composition
inferred← citeshttps://doi.org/10.1155/2016/8370132openalex-snapshot
A Prediction Model for Membrane Proteins Using Moments Based Features
inferred← citeshttps://doi.org/10.1186/1471-2105-7-518openalex-snapshot
Prediction of protein submitochondria locations by hybridizing pseudo-amino acid composition with various physicochemical features of segmented sequence
inferred← citeshttps://doi.org/10.1371/journal.pone.0011335openalex-snapshot
Plant-mPLoc: A Top-Down Strategy to Augment the Power for Predicting Plant Protein Subcellular Localization
inferred← citeshttps://doi.org/10.14569/ijacsa.2016.070768openalex-snapshot
Computational Modeling of Proteins based on Cellular Automata
inferred← citeshttps://doi.org/10.1586/14789450.4.4.453openalex-snapshot
Methodology development for predicting subcellular localization and other attributes of proteins
inferred← citeshttps://doi.org/10.18483/ijsci.2247openalex-snapshot
Showcase to Illustrate How the Web-Server iKcr-PseEns is Working
inferred← citeshttps://doi.org/10.18632/oncotarget.7815openalex-snapshot
iACP: a sequence-based tool for identifying anticancer peptides
inferred← citeshttps://doi.org/10.21203/rs.3.rs-1873422/v1openalex-snapshot
Employing a Novel Tri-code Embedding vector with LSTM and SoftMax layer for Membrane Protein Classification
inferred← citeshttps://doi.org/10.2174/092986609787848045openalex-snapshot
Prediction of Cell Wall Lytic Enzymes Using Chous Amphiphilic Pseudo Amino Acid Composition
inferred← citeshttps://doi.org/10.2174/092986609788923374openalex-snapshot
Prediction of Small Molecules Metabolic Pathways Based on Functional Group Composition
inferred← citeshttps://doi.org/10.2174/092986611795446085openalex-snapshot
Prediction of Thermophilic Protein with Pseudo Amino Acid Composition: An Approach from Combined Feature Selection and Reduction
inferred← citeshttps://doi.org/10.2174/0929867326666190506111629openalex-snapshot
Advances in Electrochemistry for Monitoring Cellular Chemical Flux
inferred← citeshttps://doi.org/10.2174/0929867326666190507082559openalex-snapshot
Advances in Predicting Subcellular Localization of Multi-label Proteins and its Implication for Developing Multi-target Drugs
inferred← citeshttps://doi.org/10.2174/1381612825666191129164042openalex-snapshot
An Insightful 10-year Recollection Since the Emergence of the 5-steps Rule
inferred← citeshttps://doi.org/10.2174/156802607780906771openalex-snapshot
Medicinal Chemistry and Bioinformatics - Current Trends in Drugs Discovery with Networks Topological Indices
inferred← citeshttps://doi.org/10.2174/1568026619666191018100141openalex-snapshot
Impacts of Pseudo Amino Acid Components and 5-steps Rule to Proteomics and Proteome Analysis
inferred← citeshttps://doi.org/10.2174/1570163817666200806165934openalex-snapshot
Insights into Machine Learning-based Approaches for Virtual Screening in Drug Discovery: Existing Strategies and Streamlining Through FP-CADD
inferred← citeshttps://doi.org/10.2174/157016409789973707openalex-snapshot
Pseudo Amino Acid Composition and its Applications in Bioinformatics, Proteomics and System Biology
inferred← citeshttps://doi.org/10.2174/1570164617666191025101914openalex-snapshot
Distorted Key Theory and its Implication for Drug Development
inferred← citeshttps://doi.org/10.2174/1570193x13666151218191932openalex-snapshot
Recent Advances on Prediction of Protein Subcellular Localization
inferred← citeshttps://doi.org/10.2174/1573406411666141229162834openalex-snapshot
Impacts of Bioinformatics to Medicinal Chemistry
inferred← citeshttps://doi.org/10.2174/1574893614666181217145156openalex-snapshot
Advances in the Prediction of Protein Subcellular Locations with Machine Learning
inferred← citeshttps://doi.org/10.2174/1574893614666190204154038openalex-snapshot
Relevance of Machine Learning Techniques and Various Protein Features in Protein Fold Classification: A Review
inferred← citeshttps://doi.org/10.2174/1574893618666230224143726openalex-snapshot
Identification of Membrane Protein Types Based Using Hypergraph Neural Network
inferred← citeshttps://doi.org/10.2174/1574893618666230905102407openalex-snapshot
RDR100: A Robust Computational Method for Identification of Krüppel-like Factors
inferred← citeshttps://doi.org/10.2174/1875036201307010041openalex-snapshot
A Short Survey on Genetic Sequences, Chou’s Pseudo Amino Acid Composition and its Combination with Fuzzy Set Theory
inferred← citeshttps://doi.org/10.2174/978160805379711201010003openalex-snapshot
QSAR, Complex Networks, Principal Components and Partial Order Analysis of Drug Cardiotoxicity with Proteome Mass- Spectra Topological Indices
inferred← citeshttps://doi.org/10.26717/bjstr.2019.23.003978openalex-snapshot
The Cradle of Gordon Life Science Institute and its Development and Driving Force
inferred← citeshttps://doi.org/10.31038/jmg.2020322openalex-snapshot
https://researchopenworld.com/showcase-to-illustrate-how-the-web-server-irnamethyl-is-working/#
inferred← citeshttps://doi.org/10.3168/jds.2018-16048openalex-snapshot
Using molecular descriptors for assisted screening of heterologous competitive antigens to improve the sensitivity of ELISA for detection of enrofloxacin in raw milk
inferred← citeshttps://doi.org/10.31829/2692-4242/biogen2019-2(1)-102openalex-snapshot
The Cradle of Gordon Life Science Institute and Its Development and Driving Force
inferred← citeshttps://doi.org/10.3233/ifs-151701openalex-snapshot
An extension of fuzzy topological approach for comparison of genetic sequences
inferred← citeshttps://doi.org/10.3389/feart.2021.596860openalex-snapshot
Solar Radiation Prediction Using Different Machine Learning Algorithms and Implications for Extreme Climate Events
inferred← citeshttps://doi.org/10.3390/app132212511openalex-snapshot
RPREC: A Radar Plot Recognition Algorithm Based on Adaptive Evidence Classification
inferred← citeshttps://doi.org/10.3390/brainsci10100726openalex-snapshot
Prediction of Human Inhibition Brain Function with Inter-Subject and Intra-Subject Variability
inferred← citeshttps://doi.org/10.3390/catal14120894openalex-snapshot
GPpred: A Novel Sequence-Based Tool for Predicting Glutamic Proteases Using Optimized Hybrid Encodings
inferred← citeshttps://doi.org/10.3390/ecsoc-11-01371openalex-snapshot
Predicting Proteome-Early Drug Induced Cardiac Toxicity Relationships (Pro-EDICToRs) with Node Overlapping Parameters (NOPs) of a new class of Blood Mass-Spectra graphs
inferred← citeshttps://doi.org/10.3390/ijms15021746openalex-snapshot
iRSpot-TNCPseAAC: Identify Recombination Spots with Trinucleotide Composition and Pseudo Amino Acid Components
inferred← citeshttps://doi.org/10.3390/ijms15034915openalex-snapshot
iNR-Drug: Predicting the Interaction of Drugs with Nuclear Receptors in Cellular Networking
inferred← citeshttps://doi.org/10.4236/ns.2009.12011openalex-snapshot
REVIEW : Recent advances in developing web-servers for predicting protein attributes
inferred← citeshttps://doi.org/10.4236/ns.2017.94007openalex-snapshot
Pse-in-One 2.0: An Improved Package of Web Servers for Generating Various Modes of Pseudo Components of DNA, RNA, and Protein Sequences
inferred← citeshttps://doi.org/10.4236/ns.2020.123013openalex-snapshot
Gordon Life Science Institute and Its Impacts on Computational Biology and Drug Development
inferred← citeshttps://doi.org/10.4236/ns.2020.127036openalex-snapshot
An Insightful Recollection for Predicting Protein Subcellular Locations in Multi-Label Systems
inferred← citeshttps://doi.org/10.47363/jeast/2021(3)126openalex-snapshot
Proposal of Pseudo Amino Acid Composition and Its Impacts and Profound Influence
inferred← citeshttps://doi.org/10.5681/bi.2011.011openalex-snapshot
A Glance at DNA Microarray Technology and Applications
inferred← citeshttps://doi.org/10.5772/intechopen.100180openalex-snapshot
In Silico Vaccine Design Tools
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