Journal of Biomedical Science and Engineering

Journal of Biomedical Science and Engineering

ISSN Print: 1937-6871
ISSN Online: 1937-688X
www.scirp.org/journal/jbise
E-mail: jbise@scirp.org
"Prediction of protein folding rates from primary sequence by fusing multiple sequential features"
written by Hong-Bin Shen, Jiang-Ning Song, Kuo-Chen Chou,
published by Journal of Biomedical Science and Engineering, Vol.2 No.3, 2009
has been cited by the following article(s):
  • Google Scholar
  • CrossRef
[1] Using the Chou's 5-steps rule to predict splice junctions with interpretable bidirectional long short-term memory networks
2020
[2] Use Chou's 5-steps rule to predict remote homology proteins by merging grey incidence analysis and domain similarity analysis
2020
[3] An Effective Cumulative Torsion Angles Model for Prediction of Protein Folding Rates
2020
[4] Noah's Ark and Internet Institutes: When and Why?
2020
[5] Gordon Life Science Institute and Its Impacts on Computational Biology and Drug Development
2020
[6] An insightful 20-year recollection since the birth of pseudo amino acid components
2020
[7] The Implication of “I Am the Alpha and the Omega” to Internet Institutes
2020
[8] The Pandemic Pestilences and Internet Institutes
2020
[9] An Enhanced Protein Fold Recognition for Low Similarity Datasets Using Convolutional and Skip-Gram Features With Deep Neural Network
2020
[10] Recent Progresses for Computationally Identifying N 6-methyladenosine Sites in Saccharomyces cerevisiae
2020
[11] Enhancing Segmentation Approaches from Oaam to Fuzzy KC-Means
2020
[12] Advances in predicting subcellular localization of multi-label proteins and its implication for developing multi-target drugs
2019
[13] An insightful recollection for predicting protein subcellular locations in multi-label systems
2019
[14] An Insightful 10-year Recollection Since the Emergence of the 5-steps Rule.
2019
[15] Intriguing Story about the Birth of Gordon Life Science Institute and its Development and Driving Force
2019
[16] Protein Fold Recognition using n-Gram Strict Position Specific Scoring Matrix and Structural based Feature Extraction Technique
International Journal of Recent Technology and Engineering, 2019
[17] JOURNAL OF MATHEMATICS, STATISTICS AND COMPUTING
2019
[18] Advance in Predicting Subcellular Localization of Multi-label Proteins and its Implication for Developing Multi-target Drugs
2019
[19] Progresses in predicting post-translational modification
2019
[20] A two-level computation model based on deep learning algorithm for identification of piRNA and their functions via Chou's 5-steps rule
2019
[21] Proposing Pseudo Amino Acid Components is an Important Milestone for Proteome and Genome Analyses
2019
[22] Identifying DNase I hypersensitive sites using multi-features fusion and F-score features selection via Chou's 5-steps rule
2019
[23] csDMA: an improved bioinformatics tool for identifying DNA 6 mA modifications via Chou's 5-step rule
2019
[24] Physicochemical n‐Grams Tool: A tool for protein physicochemical descriptor generation via Chou's 5‐steps rule
2019
[25] Prediction of lysine formylation sites using the composition of k-spaced amino acid pairs via Chou's 5-steps rule and general pseudo components
2019
[26] Identifying FL11 subtype by characterizing tumor immune microenvironment in prostate adenocarcinoma via Chou's 5-steps rule
2019
[27] Tensor Algebra-based Geometrical (3D) Biomacro-Molecular Descriptors for Protein Research: Theory, Applications and Comparison with other Methods
2019
[28] MsDBP: Exploring DNA-binding Proteins by Integrating Multi-scale Sequence Information via Chou's 5-steps Rule
Journal of Proteome Research, 2019
[29] MsDBP: Exploring DNA-Binding Proteins by Integrating Multiscale Sequence Information via Chou's Five-Step Rule
2019
[30] Impacts of pseudo amino acid components and 5-steps rule to proteomics and proteome analysis
2019
[31] Artificial intelligence (AI) tools constructed via the 5-steps rule for predicting post-translational modifications
2019
[32] iMethylK-PseAAC: Improving Accuracy of Lysine Methylation Sites Identification by Incorporating Statistical Moments and Position Relative Features into General …
2019
[33] iSulfoTyr-PseAAC: Identify Tyrosine Sulfation Sites by Incorporating Statistical Moments via Chou's 5-steps Rule and Pseudo Components
2019
[34] PREvaIL, an integrative approach for inferring catalytic residues using sequence, structural, and network features in a machine-learning framework
Journal of Theoretical Biology, 2018
[35] iProt-Sub: a comprehensive package for accurately mapping and predicting protease-specific substrates and cleavage sites
Briefings in Bioinformatics, 2018
[36] Pse-in-One 2.0: An Improved Package of Web Servers for Generating Various Modes of Pseudo Components of DNA, RNA, and Protein Sequences
2017
[37] A Novel Model-Based on FCM–LM Algorithm for Prediction of Protein Folding Rate
Journal of bioinformatics and computational biology, 2017
[38] An unprecedented revolution in medicinal chemistry driven by the progress of biological science
Current Topics in Medicinal Chemistry, 2017
[39] Ikcr-pseens: Identify lysine crotonylation sites in histone proteins with pseudo components and ensemble classifier
Genomics, 2017
[40] iACP: a sequence-based tool for identifying anticancer peptides
Oncotarget, 2016
[41] iHyd-PseCp: Identify hydroxyproline and hydroxylysine in proteins by incorporating sequence-coupled effects into general PseAAC
Oncotarget, 2016
[42] iROS-gPseKNC: predicting replication origin sites in DNA by incorporating dinucleotide position-specific propensity into general pseudo nucleotide …
Oncotarget, 2016
[43] Network measures for protein folding state discrimination
Scientific reports, 2016
[44] pSuc-Lys: Predict lysine succinylation sites in proteins with PseAAC and ensemble random forest approach
Journal of Theoretical Biology, 2016
[45] A New Multi-label Classifier for Identifying the Functional Types of Singleplex and Multiplex Antimicrobial Peptides
International Journal of Peptide Research and Therapeutics, 2016
[46] Impacts of bioinformatics to medicinal chemistry
Medicinal Chemistry, 2015
[47] Enhanced Feature Extraction from Evolutionary Profiles for Protein Fold Recognition
2015
[48] Predicting the Protein Folding Rate Based on Sequence Feature Screening and Support Vector Regression
Acta Physico-Chimica Sinica, 2014
[49] 基于序列特征筛选与支持向量回归预测蛋白质折叠速率
2014
[50] Proposing a highly accurate protein structural class predictor using segmentation-based features
BMC genomics, 2014
[51] A Tri-Gram Based Feature Extraction Technique Using Linear Probabilities of Position Specific Scoring Matrix for Protein Fold Recognition
NanoBioscience, IEEE Transactions on, 2014
[52] Towards more accurate prediction of protein folding rates: a review of the existing web-based bioinformatics approaches
Briefings in bioinformatics, 2014
[53] Graphic Mapping of Protein-Coding DNA Sequence in Four-Dimensional Space and its Application
Journal of Computational and Theoretical Nanoscience, 2014
[54] Unfolded protein ensembles, folding trajectories, and refolding rate prediction
The Journal of chemical physics, 2013
[55] Surface Acidic Amino Acid of Pseudomonas/Halomonas Chimeric Nucleoside Diphosphate Kinase Leads Effective Recovery from Heat-Denaturation
Protein and peptide letters, 2013
[56] Expression pattern of recombinant organophosphorus hydrolase from Flavobacterium sp. ATCC 27551 in Escherichia coli
Applied microbiology and biotechnology, 2013
[57] A Framework for Modeling the Cellular Defending Mechanisms Against Genome Stress Under Radiotherapy
2013
[58] Investigation Binding Patterns of Human Carboxylesterase I (hCES I) with Broad Substrates by MD Simulations
Current topics in medicinal chemistry, 2013
[59] A Two-step Similarity-based Method for Prediction of Drug's Target Group
Protein and peptide letters, 2013
[60] Swfoldrate: Predicting protein folding rates from amino acid sequence with sliding window method
Proteins: Structure, Function, and Bioinformatics, 2013
[61] Theoretical and experimental biology in one
2013
[62] Theoretical and experimental biology in one—A symposium in honour of Professor Kuo-Chen Chou's 50th anniversary and Professor Richard Giegé's 40th …
2013
[63] Theoretical and experimental biology in one—A symposium in honour of Professor Kuo-Chen Chou’s 50th anniversary and Professor Richard Giegé’s 40th anniversary of their scientific careers
Journal of Biomedical Science and Engineering, 2013
[64] 蛋白质折叠速率决定因素与预测方法的研究进展
生物物理学报, 2013
[65] Incorporating Secondary Features into the General form of Chou's PseAAC for Predicting Protein Structural Class
Protein and peptide letters, 2012
[66] A pharmacophore model specific to active site of CYP1A2 with a novel molecular modeling explorer and CoMFA
Medicinal Chemistry, 2012
[67] A Computational Genome-wide Study of Protein Folding Rate
2012
[68] SOMPNN: an efficient non-parametric model for predicting transmembrane helices
Amino acids, 2012
[69] Prediction of protein subcellular multi-localization based on the general form of Chou's pseudo amino acid composition
Protein and peptide letters, 2012
[70] Dual-layer wavelet SVM for predicting protein structural class via the general form of Chou's pseudo amino acid composition
Protein and peptide letters, 2012
[71] Determination of protein folding kinetic types using sequence and predicted secondary structure and solvent accessibility
Amino acids, 2012
[72] Improved prediction of palmitoylation sites using PWMs and SVM
Protein and peptide letters, 2011
[73] Bioinformatic approaches for predicting substrates of proteases
Journal of bioinformatics and computational biology, 2011
[74] The dynamical contact order: Protein folding rate parameters based on quantum conformational transitions
Science China Life Sciences, 2011
[75] ifc2: an integrated web-server for improved prediction of protein structural class, fold type, and secondary structure content
Amino acids, 2011
[76] Three 3D graphical representations of DNA primary sequences based on the classifications of DNA bases and their applications
Journal of theoretical biology, 2011
[77] Multitask learning for protein subcellular location prediction
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB), 2011
[78] Two-intermediate model to characterize the structure of fast-folding proteins
Journal of theoretical biology, 2011
[79] Predicting functions of proteins in mouse based on weighted protein-protein interaction network and protein hybrid properties
PLoS One, 2011
[80] Using random forest algorithm to predict β-hairpin motifs
Protein and peptide letters, 2011
[81] Quat-2L: a web-server for predicting protein quaternary structural attributes
Molecular diversity, 2011
[82] Predicting protein folding rates using the concept of Chou's pseudo amino acid composition
Journal of computational chemistry, 2011
[83] A Novel Method to Predict Protein-Protein Interactions Based on the Information of Protein-Protein Interaction Networks and Protein Sequence
Protein and peptide letters, 2011
[84] Predicting protein folding rate from amino acid sequence
Journal of bioinformatics and computational biology, 2011
[85] Machine learning algorithms for predicting protein folding rates and stability of mutant proteins: Comparison with statistical methods
Current Protein and Peptide Science, 2011
[86] Analysis of rate-limiting long-range contacts in the folding rate of three-state and two-state Proteins
Protein and peptide letters, 2011
[87] Analyses of Protein Sequences Using Inter-Residue Average Distance Statistics to Study Folding Processes and the Significance of Their Partial Sequences
Protein and peptide letters, 2011
[88] Self-similarity analysis of eubacteria genome based on weighted graph
Journal of theoretical biology, 2011
[89] Wenxiang: a web-server for drawing wenxiang diagrams
Natural Science, 2011
[90] iFC 2: an integrated web-server for improved prediction of protein structural class, fold type, and secondary structure content
2011
[91] Graphic rule for drug metabolism systems
Current Drug Metabolism, 2010
[92] Cellular responding kinetics based on a model of gene regulatory networks under radiotherapy
Health, 2010
[93] Virus-mPLoc: a fusion classifier for viral protein subcellular location prediction by incorporating multiple sites
Journal of Biomolecular Structure and Dynamics, 2010
[94] Computational prediction of properties and analysis of molecular phylogenetics of polyketide synthases in three species of Actinomycetes
Medicinal Chemistry, 2010
[95] Gene ontology-based protein function prediction by using sequence composition information
Protein and peptide letters, 2010
[96] Engineering thermostable xylanase enzyme mutant from Bacillus halodurans
African Journal of Biotechnology, 2010
[97] Molecular modeling of human hepatocyte PKA (cAMP-dependent protein kinase type-II) and its structure analysis
Protein and peptide letters, 2010
[98] Linking mutated primary structure of adrenoleukodystrophy protein with X-linked adrenoleukodystrophy
Computer methods in biomechanics and biomedical engineering, 2010
[99] 2D-MH: A web-server for generating graphic representation of protein sequences based on the physicochemical properties of their constituent amino acids
Journal of theoretical biology, 2010
[100] Global and local prediction of protein folding rates based on sequence autocorrelation information
Journal of theoretical biology, 2010
[101] A simple method to analyze the similarity of biological sequences based on the fuzzy theory
Journal of theoretical biology, 2010
[102] 从氨基酸序列预测蛋白质折叠速率
Progress in Biochemistry and Biophysics, 2010
[103] 动力学接触序: 基于量子跃迁的蛋白质折叠速率参数
中国科学: 生命科学, 2010
[104] Prediction of disease-related genes based on hybrid features
Current Proteomics, 2010
[105] On the importance of the small domain in the thermostability of thermoalkalophilic lipases from L1 and T1: Insights from molecular dynamics simulation
Protein and peptide letters, 2010
[106] The implications of gene heterozygosity for protein folding and protein turnover
Journal of theoretical biology, 2010
[107] e-PROPAINOR: A Web-Server for Fast Prediction of C Structure & Likely Functional Sites of a Protein Sequence
Open Bioinformatics Journal, 2010
[108] Prediction of enzyme subfamily class via pseudo amino acid composition by incorporating the conjoint triad feature
Protein and peptide letters, 2010
[109] Plant-mPLoc: a top-down strategy to augment the power for predicting plant protein subcellular localization
PloS one, 2010
[110] Using the concept of Chou's pseudo amino acid composition for risk type prediction of human papillomaviruses
Journal of theoretical biology, 2010
[111] Analysis and prediction of the metabolic stability of proteins based on their sequential features, subcellular locations and interaction networks
PloS one, 2010
[112] Using the concept of Chou's pseudo amino acid composition to predict enzyme family classes: an approach with support vector machine based on discrete wavelet transform
Protein and peptide letters, 2010
[113] Molecular modeling of cytochrome P450 and drug metabolism
Current drug metabolism, 2010
[114] Prediction of mitochondrial proteins of malaria parasite using split amino acid composition and PSSM profile
Amino acids, 2010
[115] Sequence-based prediction of enzyme thermostability through bioinformatics algorithms
Current Bioinformatics, 2010
[116] Protein subcellular multi-localization prediction using a min-max modular support vector machine
International journal of neural systems, 2010
[117] Characteristic peptides of protein secondary structural motifs
Protein and peptide letters, 2010
[118] A summary of computational resources for protein phosphorylation
Current Protein and Peptide Science, 2010
[119] Classification of transcription factors using protein primary structure
Protein and peptide letters, 2010
[120] Accurate prediction of protein folding rates from sequence and sequence‐derived residue flexibility and solvent accessibility
Proteins: Structure, Function, and Bioinformatics, 2010
[121] Predicting enzyme subclasses by using support vector machine with composite vectors
Protein and peptide letters, 2010
[122] Identifying the hub proteins from complicated membrane protein network systems
Medicinal Chemistry, 2010
[123] Prediction of the parallel/antiparallel orientation of beta-strands using amino acid pairing preferences and support vector machines
Journal of theoretical biology, 2010
[124] Composition-based effective chain length for prediction of protein folding rates
Physical Review E, 2010
[125] Development of tools and database for analysis of metal binding sites in protein
Protein and peptide letters, 2010
[126] Protein classification using texture descriptors extracted from the protein backbone image
Journal of Theoretical Biology, 2010
[127] The Burrows–Wheeler similarity distribution between biological sequences based on Burrows–Wheeler transform
Journal of theoretical biology, 2010
[128] Predicting caspase substrate cleavage sites based on a hybrid SVMPSSM method
Protein and Peptide Letters, 2010
[129] GPCR-GIA: a web-server for identifying G-protein coupled receptors and their families with grey incidence analysis
Protein Engineering Design and Selection, 2009
[130] A network-QSAR model for prediction of genetic-component biomarkers in human colorectal cancer
Journal of theoretical biology, 2009
[131] Generalized lattice graphs for 2D-visualization of biological information
Journal of theoretical biology, 2009
[132] Estimation of relative binding free energy based on a free energy variational principle for quantitative structure activity relationship analyses
Chemical Physics, 2009
[133] Recent advances in developing web-servers for predicting protein attributes
2009
[134] Gpos-mPLoc: A top-down approach to improve the quality of predicting subcellular localization of Gram-positive bacterial proteins
Protein and peptide letters, 2009
[135] Review: recent advances in developing web-servers for predicting protein attributes
Natural Science, 2009
[136] A top-down approach to enhance the power of predicting human protein subcellular localization: Hum-mPLoc 2.0
Analytical biochemistry, 2009
Free SCIRP Newsletters
Copyright © 2006-2022 Scientific Research Publishing Inc. All Rights Reserved.
Top