Journal of Biomedical Science and Engineering

Volume 2, Issue 3 (June 2009)

ISSN Print: 1937-6871   ISSN Online: 1937-688X

Google-based Impact Factor: 0.66  Citations  h5-index & Ranking

Prediction of protein folding rates from primary sequence by fusing multiple sequential features

HTML  Download Download as PDF (Size: 188KB)  PP. 136-143  
DOI: 10.4236/jbise.2009.23024    6,992 Downloads   13,150 Views  Citations

ABSTRACT

We have developed a web-server for predicting the folding rate of a protein based on its amino acid sequence information alone. The web- server is called Pred-PFR (Predicting Protein Folding Rate). Pred-PFR is featured by fusing multiple individual predictors, each of which is established based on one special feature derived from the protein sequence. The ensemble pre-dictor thus formed is superior to the individual ones, as demonstrated by achieving higher correlation coefficient and lower root mean square deviation between the predicted and observed results when examined by the jack-knife cross-validation on a benchmark dataset constructed recently. As a user-friendly web- server, Pred-PFR is freely accessible to the public at www.csbio.sjtu.edu.cn/bioinf/Folding Rate/.

Share and Cite:

Shen, H. , Song, J. and Chou, K. (2009) Prediction of protein folding rates from primary sequence by fusing multiple sequential features. Journal of Biomedical Science and Engineering, 2, 136-143. doi: 10.4236/jbise.2009.23024.

Cited by

[1] FRTpred: A novel approach for accurate prediction of protein folding rate and type
Computers in Biology and Medicine, 2022
[2] PERISCOPE-Opt: Machine learning-based prediction of optimal fermentation conditions and yields of recombinant periplasmic protein expressed in …
Computational and …, 2022
[3] Graph Signal Processing on protein residue networks helps in studying its biophysical properties
bioRxiv, 2021
[4] An Enhanced Protein Fold Recognition for Low Similarity Datasets Using Convolutional and Skip-Gram Features With Deep Neural Network
2020
[5] Recent Progresses for Computationally Identifying N 6-methyladenosine Sites in Saccharomyces cerevisiae
2020
[6] Enhancing Segmentation Approaches from Oaam to Fuzzy KC-Means
2020
[7] Using Chou's 5-steps rule to predict O-linked serine glycosylation sites by blending position relative features and statistical moment
… ACM transactions on …, 2020
[8] Use Chou's 5-steps rule with different word embedding types to boost performance of electron transport protein prediction model
Quang, V Dinh-Phan… - … /ACM Transactions on …, 2020
[9] Protein fold recognition based on auto-weighted multi-view graph embedding learning model
IEEE/ACM Transactions on …, 2020
[10] Using the Chou's 5-steps rule to predict splice junctions with interpretable bidirectional long short-term memory networks
2020
[11] Use Chou's 5-steps rule to predict remote homology proteins by merging grey incidence analysis and domain similarity analysis
2020
[12] An Effective Cumulative Torsion Angles Model for Prediction of Protein Folding Rates
2020
[13] Noah's Ark and Internet Institutes: When and Why?
2020
[14] Gordon Life Science Institute and Its Impacts on Computational Biology and Drug Development
2020
[15] An insightful 20-year recollection since the birth of pseudo amino acid components
2020
[16] The Implication of “I Am the Alpha and the Omega” to Internet Institutes
2020
[17] The Pandemic Pestilences and Internet Institutes
2020
[18] Intriguing Story about the Birth of Gordon Life Science Institute and its Development and Driving Force
2019
[19] 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
[20] Advances in predicting subcellular localization of multi-label proteins and its implication for developing multi-target drugs
2019
[21] An insightful recollection for predicting protein subcellular locations in multi-label systems
2019
[22] An Insightful 10-year Recollection Since the Emergence of the 5-steps Rule.
2019
[23] Advance in Predicting Subcellular Localization of Multi-label Proteins and its Implication for Developing Multi-target Drugs
2019
[24] Progresses in predicting post-translational modification
2019
[25] A two-level computation model based on deep learning algorithm for identification of piRNA and their functions via Chou's 5-steps rule
2019
[26] Proposing Pseudo Amino Acid Components is an Important Milestone for Proteome and Genome Analyses
2019
[27] Identifying DNase I hypersensitive sites using multi-features fusion and F-score features selection via Chou's 5-steps rule
2019
[28] csDMA: an improved bioinformatics tool for identifying DNA 6 mA modifications via Chou's 5-step rule
2019
[29] Physicochemical n‐Grams Tool: A tool for protein physicochemical descriptor generation via Chou's 5‐steps rule
2019
[30] 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
[31] Identifying FL11 subtype by characterizing tumor immune microenvironment in prostate adenocarcinoma via Chou's 5-steps rule
2019
[32] Tensor Algebra-based Geometrical (3D) Biomacro-Molecular Descriptors for Protein Research: Theory, Applications and Comparison with other Methods
2019
[33] MsDBP: Exploring DNA-binding Proteins by Integrating Multi-scale Sequence Information via Chou's 5-steps Rule
Journal of Proteome Research, 2019
[34] MsDBP: Exploring DNA-Binding Proteins by Integrating Multiscale Sequence Information via Chou's Five-Step Rule
2019
[35] Impacts of pseudo amino acid components and 5-steps rule to proteomics and proteome analysis
2019
[36] Artificial intelligence (AI) tools constructed via the 5-steps rule for predicting post-translational modifications
2019
[37] iMethylK-PseAAC: Improving Accuracy of Lysine Methylation Sites Identification by Incorporating Statistical Moments and Position Relative Features into General …
2019
[38] iSulfoTyr-PseAAC: Identify Tyrosine Sulfation Sites by Incorporating Statistical Moments via Chou's 5-steps Rule and Pseudo Components
2019
[39] PREvaIL, an integrative approach for inferring catalytic residues using sequence, structural, and network features in a machine-learning framework
Journal of Theoretical Biology, 2018
[40] iProt-Sub: a comprehensive package for accurately mapping and predicting protease-specific substrates and cleavage sites
Briefings in Bioinformatics, 2018
[41] 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
[42] A Novel Model-Based on FCM–LM Algorithm for Prediction of Protein Folding Rate
Journal of bioinformatics and computational biology, 2017
[43] An unprecedented revolution in medicinal chemistry driven by the progress of biological science
Current Topics in Medicinal Chemistry, 2017
[44] Ikcr-pseens: Identify lysine crotonylation sites in histone proteins with pseudo components and ensemble classifier
Genomics, 2017
[45] iACP: a sequence-based tool for identifying anticancer peptides
Oncotarget, 2016
[46] iHyd-PseCp: Identify hydroxyproline and hydroxylysine in proteins by incorporating sequence-coupled effects into general PseAAC
Oncotarget, 2016
[47] iROS-gPseKNC: predicting replication origin sites in DNA by incorporating dinucleotide position-specific propensity into general pseudo nucleotide …
Oncotarget, 2016
[48] Network measures for protein folding state discrimination
Scientific reports, 2016
[49] pSuc-Lys: Predict lysine succinylation sites in proteins with PseAAC and ensemble random forest approach
Journal of Theoretical Biology, 2016
[50] A New Multi-label Classifier for Identifying the Functional Types of Singleplex and Multiplex Antimicrobial Peptides
International Journal of Peptide Research and Therapeutics, 2016
[51] Impacts of bioinformatics to medicinal chemistry
Medicinal Chemistry, 2015
[52] Enhanced Feature Extraction from Evolutionary Profiles for Protein Fold Recognition
2015
[53] Predicting the Protein Folding Rate Based on Sequence Feature Screening and Support Vector Regression
Acta Physico-Chimica Sinica, 2014
[54] 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
[55] Proposing a highly accurate protein structural class predictor using segmentation-based features
BMC genomics, 2014
[56] A Tri-Gram Based Feature Extraction Technique Using Linear Probabilities of Position Specific Scoring Matrix for Protein Fold Recognition
NanoBioscience, IEEE Transactions on, 2014
[57] Towards more accurate prediction of protein folding rates: a review of the existing web-based bioinformatics approaches
Briefings in bioinformatics, 2014
[58] Graphic Mapping of Protein-Coding DNA Sequence in Four-Dimensional Space and its Application
Journal of Computational and Theoretical Nanoscience, 2014
[59] Unfolded protein ensembles, folding trajectories, and refolding rate prediction
The Journal of chemical physics, 2013
[60] Surface Acidic Amino Acid of Pseudomonas/Halomonas Chimeric Nucleoside Diphosphate Kinase Leads Effective Recovery from Heat-Denaturation
Protein and peptide letters, 2013
[61] Expression pattern of recombinant organophosphorus hydrolase from Flavobacterium sp. ATCC 27551 in Escherichia coli
Applied microbiology and biotechnology, 2013
[62] A Framework for Modeling the Cellular Defending Mechanisms Against Genome Stress Under Radiotherapy
2013
[63] Investigation Binding Patterns of Human Carboxylesterase I (hCES I) with Broad Substrates by MD Simulations
Current topics in medicinal chemistry, 2013
[64] A Two-step Similarity-based Method for Prediction of Drug's Target Group
Protein and peptide letters, 2013
[65] Swfoldrate: Predicting protein folding rates from amino acid sequence with sliding window method
Proteins: Structure, Function, and Bioinformatics, 2013
[66] Theoretical and experimental biology in one
2013
[67] 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
[68] 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
[69] 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
[70] Incorporating Secondary Features into the General form of Chou's PseAAC for Predicting Protein Structural Class
Protein and peptide letters, 2012
[71] A pharmacophore model specific to active site of CYP1A2 with a novel molecular modeling explorer and CoMFA
Medicinal Chemistry, 2012
[72] A Computational Genome-wide Study of Protein Folding Rate
2012
[73] SOMPNN: an efficient non-parametric model for predicting transmembrane helices
Amino acids, 2012
[74] Prediction of protein subcellular multi-localization based on the general form of Chou's pseudo amino acid composition
Protein and peptide letters, 2012
[75] 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
[76] Determination of protein folding kinetic types using sequence and predicted secondary structure and solvent accessibility
Amino acids, 2012
[77] Improved prediction of palmitoylation sites using PWMs and SVM
Protein and peptide letters, 2011
[78] Bioinformatic approaches for predicting substrates of proteases
Journal of bioinformatics and computational biology, 2011
[79] The dynamical contact order: Protein folding rate parameters based on quantum conformational transitions
Science China Life Sciences, 2011
[80] ifc2: an integrated web-server for improved prediction of protein structural class, fold type, and secondary structure content
Amino acids, 2011
[81] Three 3D graphical representations of DNA primary sequences based on the classifications of DNA bases and their applications
Journal of theoretical biology, 2011
[82] Multitask learning for protein subcellular location prediction
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB), 2011
[83] Two-intermediate model to characterize the structure of fast-folding proteins
Journal of theoretical biology, 2011
[84] Predicting functions of proteins in mouse based on weighted protein-protein interaction network and protein hybrid properties
PLoS One, 2011
[85] Using random forest algorithm to predict β-hairpin motifs
Protein and peptide letters, 2011
[86] Quat-2L: a web-server for predicting protein quaternary structural attributes
Molecular diversity, 2011
[87] Predicting protein folding rates using the concept of Chou's pseudo amino acid composition
Journal of computational chemistry, 2011
[88] 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
[89] Predicting protein folding rate from amino acid sequence
Journal of bioinformatics and computational biology, 2011
[90] Machine learning algorithms for predicting protein folding rates and stability of mutant proteins: Comparison with statistical methods
Current Protein and Peptide Science, 2011
[91] Analysis of rate-limiting long-range contacts in the folding rate of three-state and two-state Proteins
Protein and peptide letters, 2011
[92] 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
[93] Self-similarity analysis of eubacteria genome based on weighted graph
Journal of theoretical biology, 2011
[94] Wenxiang: a web-server for drawing wenxiang diagrams
Natural Science, 2011
[95] iFC 2: an integrated web-server for improved prediction of protein structural class, fold type, and secondary structure content
2011
[96] -PROPAINOR: A Web-Server for Fast Prediction of Structure & Likely Functional Sites of a Protein Sequence
The Open Bioinformatics …, 2010
[97] Graphic rule for drug metabolism systems
Current Drug Metabolism, 2010
[98] Cellular responding kinetics based on a model of gene regulatory networks under radiotherapy
Health, 2010
[99] Virus-mPLoc: a fusion classifier for viral protein subcellular location prediction by incorporating multiple sites
Journal of Biomolecular Structure and Dynamics, 2010
[100] Computational prediction of properties and analysis of molecular phylogenetics of polyketide synthases in three species of Actinomycetes
Medicinal Chemistry, 2010
[101] Gene ontology-based protein function prediction by using sequence composition information
Protein and peptide letters, 2010
[102] Engineering thermostable xylanase enzyme mutant from Bacillus halodurans
African Journal of Biotechnology, 2010
[103] Molecular modeling of human hepatocyte PKA (cAMP-dependent protein kinase type-II) and its structure analysis
Protein and peptide letters, 2010
[104] Linking mutated primary structure of adrenoleukodystrophy protein with X-linked adrenoleukodystrophy
Computer methods in biomechanics and biomedical engineering, 2010
[105] 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
[106] Global and local prediction of protein folding rates based on sequence autocorrelation information
Journal of theoretical biology, 2010
[107] A simple method to analyze the similarity of biological sequences based on the fuzzy theory
Journal of theoretical biology, 2010
[108] 从氨基酸序列预测蛋白质折叠速率
Progress in Biochemistry and Biophysics, 2010
[109] 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
[110] Prediction of disease-related genes based on hybrid features
Current Proteomics, 2010
[111] 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
[112] The implications of gene heterozygosity for protein folding and protein turnover
Journal of theoretical biology, 2010
[113] e-PROPAINOR: A Web-Server for Fast Prediction of C Structure & Likely Functional Sites of a Protein Sequence
Open Bioinformatics Journal, 2010
[114] Prediction of enzyme subfamily class via pseudo amino acid composition by incorporating the conjoint triad feature
Protein and peptide letters, 2010
[115] Plant-mPLoc: a top-down strategy to augment the power for predicting plant protein subcellular localization
PloS one, 2010
[116] Using the concept of Chou's pseudo amino acid composition for risk type prediction of human papillomaviruses
Journal of theoretical biology, 2010
[117] Analysis and prediction of the metabolic stability of proteins based on their sequential features, subcellular locations and interaction networks
PloS one, 2010
[118] 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
[119] Molecular modeling of cytochrome P450 and drug metabolism
Current drug metabolism, 2010
[120] Prediction of mitochondrial proteins of malaria parasite using split amino acid composition and PSSM profile
Amino acids, 2010
[121] Sequence-based prediction of enzyme thermostability through bioinformatics algorithms
Current Bioinformatics, 2010
[122] Protein subcellular multi-localization prediction using a min-max modular support vector machine
International journal of neural systems, 2010
[123] Characteristic peptides of protein secondary structural motifs
Protein and peptide letters, 2010
[124] A summary of computational resources for protein phosphorylation
Current Protein and Peptide Science, 2010
[125] Classification of transcription factors using protein primary structure
Protein and peptide letters, 2010
[126] Accurate prediction of protein folding rates from sequence and sequence‐derived residue flexibility and solvent accessibility
Proteins: Structure, Function, and Bioinformatics, 2010
[127] Predicting enzyme subclasses by using support vector machine with composite vectors
Protein and peptide letters, 2010
[128] Identifying the hub proteins from complicated membrane protein network systems
Medicinal Chemistry, 2010
[129] Prediction of the parallel/antiparallel orientation of beta-strands using amino acid pairing preferences and support vector machines
Journal of theoretical biology, 2010
[130] Composition-based effective chain length for prediction of protein folding rates
Physical Review E, 2010
[131] Development of tools and database for analysis of metal binding sites in protein
Protein and peptide letters, 2010
[132] Protein classification using texture descriptors extracted from the protein backbone image
Journal of Theoretical Biology, 2010
[133] The Burrows–Wheeler similarity distribution between biological sequences based on Burrows–Wheeler transform
Journal of theoretical biology, 2010
[134] Predicting caspase substrate cleavage sites based on a hybrid SVMPSSM method
Protein and Peptide Letters, 2010
[135] GPCR-GIA: a web-server for identifying G-protein coupled receptors and their families with grey incidence analysis
Protein Engineering Design and Selection, 2009
[136] A network-QSAR model for prediction of genetic-component biomarkers in human colorectal cancer
Journal of theoretical biology, 2009
[137] Generalized lattice graphs for 2D-visualization of biological information
Journal of theoretical biology, 2009
[138] Estimation of relative binding free energy based on a free energy variational principle for quantitative structure activity relationship analyses
Chemical Physics, 2009
[139] Recent advances in developing web-servers for predicting protein attributes
2009
[140] Gpos-mPLoc: A top-down approach to improve the quality of predicting subcellular localization of Gram-positive bacterial proteins
Protein and peptide letters, 2009
[141] Review: recent advances in developing web-servers for predicting protein attributes
Natural Science, 2009
[142] A top-down approach to enhance the power of predicting human protein subcellular localization: Hum-mPLoc 2.0
Analytical biochemistry, 2009

Copyright © 2024 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.