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[1]
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A Highly Sensitive Model Based on Graph Neural Networks for Enzyme Key Catalytic Residue Prediction
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Journal of Chemical …,
2023 |
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[2]
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FRTpred: A novel approach for accurate prediction of protein folding rate and type
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Computers in Biology and Medicine,
2022 |
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[3]
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PERISCOPE-Opt: Machine learning-based prediction of optimal fermentation conditions and yields of recombinant periplasmic protein expressed in …
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Computational and …,
2022 |
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[4]
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Graph Signal Processing on protein residue networks helps in studying its biophysical properties
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bioRxiv,
2021 |
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[5]
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The divination of things by things
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Extended Abstracts of the 2020 CHI Conference on …,
2020 |
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[6]
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An Enhanced Protein Fold Recognition for Low Similarity Datasets Using Convolutional and Skip-Gram Features With Deep Neural Network
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2020 |
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[7]
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Recent Progresses for Computationally Identifying N 6-methyladenosine Sites in Saccharomyces cerevisiae
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2020 |
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[8]
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Enhancing Segmentation Approaches from Oaam to Fuzzy KC-Means
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2020 |
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[9]
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Using Chou's 5-steps rule to predict O-linked serine glycosylation sites by blending position relative features and statistical moment
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… ACM transactions on …,
2020 |
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[10]
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Use Chou's 5-steps rule with different word embedding types to boost performance of electron transport protein prediction model
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Quang, V Dinh-Phan… - … /ACM Transactions on …,
2020 |
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[11]
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Protein fold recognition based on auto-weighted multi-view graph embedding learning model
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IEEE/ACM Transactions on …,
2020 |
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[12]
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Recent progresses for computationally identifying N6-methyladenosine sites in Saccharomyces cerevisiae
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Journal of Applied Mathematics and Computation,
2020 |
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[13]
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Using the Chou's 5-steps rule to predict splice junctions with interpretable bidirectional long short-term memory networks
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2020 |
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[14]
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Use Chou's 5-steps rule to predict remote homology proteins by merging grey incidence analysis and domain similarity analysis
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2020 |
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[15]
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An Effective Cumulative Torsion Angles Model for Prediction of Protein Folding Rates
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2020 |
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[16]
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Noah's Ark and Internet Institutes: When and Why?
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2020 |
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[17]
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Gordon Life Science Institute and Its Impacts on Computational Biology and Drug Development
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2020 |
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[18]
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An insightful 20-year recollection since the birth of pseudo amino acid components
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2020 |
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[19]
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The Implication of “I Am the Alpha and the Omega” to Internet Institutes
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2020 |
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[20]
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The Pandemic Pestilences and Internet Institutes
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2020 |
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[21]
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Intriguing Story about the Birth of Gordon Life Science Institute and its Development and Driving Force
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2019 |
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[22]
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Protein Fold Recognition using n-Gram Strict Position Specific Scoring Matrix and Structural based Feature Extraction Technique
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International Journal of Recent Technology and Engineering,
2019 |
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[23]
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Advances in predicting subcellular localization of multi-label proteins and its implication for developing multi-target drugs
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2019 |
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[24]
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An insightful recollection for predicting protein subcellular locations in multi-label systems
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2019 |
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[25]
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An Insightful 10-year Recollection Since the Emergence of the 5-steps Rule.
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2019 |
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[26]
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Advance in Predicting Subcellular Localization of Multi-label Proteins and its Implication for Developing Multi-target Drugs
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2019 |
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[27]
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Progresses in predicting post-translational modification
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2019 |
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[28]
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A two-level computation model based on deep learning algorithm for identification of piRNA and their functions via Chou's 5-steps rule
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2019 |
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[29]
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Proposing Pseudo Amino Acid Components is an Important Milestone for Proteome and Genome Analyses
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2019 |
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[30]
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Identifying DNase I hypersensitive sites using multi-features fusion and F-score features selection via Chou's 5-steps rule
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2019 |
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[31]
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csDMA: an improved bioinformatics tool for identifying DNA 6 mA modifications via Chou's 5-step rule
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2019 |
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[32]
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Physicochemical n‐Grams Tool: A tool for protein physicochemical descriptor generation via Chou's 5‐steps rule
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2019 |
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[33]
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Prediction of lysine formylation sites using the composition of k-spaced amino acid pairs via Chou's 5-steps rule and general pseudo components
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2019 |
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[34]
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Identifying FL11 subtype by characterizing tumor immune microenvironment in prostate adenocarcinoma via Chou's 5-steps rule
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2019 |
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[35]
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Tensor Algebra-based Geometrical (3D) Biomacro-Molecular Descriptors for Protein Research: Theory, Applications and Comparison with other Methods
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2019 |
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[36]
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MsDBP: Exploring DNA-binding Proteins by Integrating Multi-scale Sequence Information via Chou's 5-steps Rule
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Journal of Proteome Research,
2019 |
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[37]
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MsDBP: Exploring DNA-Binding Proteins by Integrating Multiscale Sequence Information via Chou's Five-Step Rule
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2019 |
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[38]
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Impacts of pseudo amino acid components and 5-steps rule to proteomics and proteome analysis
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2019 |
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[39]
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Artificial intelligence (AI) tools constructed via the 5-steps rule for predicting post-translational modifications
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2019 |
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[40]
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iMethylK-PseAAC: Improving Accuracy of Lysine Methylation Sites Identification by Incorporating Statistical Moments and Position Relative Features into General …
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2019 |
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[41]
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iSulfoTyr-PseAAC: Identify Tyrosine Sulfation Sites by Incorporating Statistical Moments via Chou's 5-steps Rule and Pseudo Components
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2019 |
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[42]
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PREvaIL, an integrative approach for inferring catalytic residues using sequence, structural, and network features in a machine-learning framework
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Journal of Theoretical Biology,
2018 |
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[43]
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iProt-Sub: a comprehensive package for accurately mapping and predicting protease-specific substrates and cleavage sites
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Briefings in Bioinformatics,
2018 |
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[44]
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Pse-in-One 2.0: An Improved Package of Web Servers for Generating Various Modes of Pseudo Components of DNA, RNA, and Protein Sequences
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2017 |
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[45]
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A Novel Model-Based on FCM–LM Algorithm for Prediction of Protein Folding Rate
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Journal of bioinformatics and computational biology,
2017 |
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[46]
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An unprecedented revolution in medicinal chemistry driven by the progress of biological science
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Current Topics in Medicinal Chemistry,
2017 |
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[47]
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Ikcr-pseens: Identify lysine crotonylation sites in histone proteins with pseudo components and ensemble classifier
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Genomics,
2017 |
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[48]
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iACP: a sequence-based tool for identifying anticancer peptides
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Oncotarget,
2016 |
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[49]
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iHyd-PseCp: Identify hydroxyproline and hydroxylysine in proteins by incorporating sequence-coupled effects into general PseAAC
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Oncotarget,
2016 |
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[50]
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iROS-gPseKNC: predicting replication origin sites in DNA by incorporating dinucleotide position-specific propensity into general pseudo nucleotide …
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Oncotarget,
2016 |
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[51]
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Network measures for protein folding state discrimination
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Scientific reports,
2016 |
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[52]
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pSuc-Lys: Predict lysine succinylation sites in proteins with PseAAC and ensemble random forest approach
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Journal of Theoretical Biology,
2016 |
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[53]
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A New Multi-label Classifier for Identifying the Functional Types of Singleplex and Multiplex Antimicrobial Peptides
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International Journal of Peptide Research and Therapeutics,
2016 |
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[54]
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Impacts of bioinformatics to medicinal chemistry
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Medicinal Chemistry,
2015 |
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[55]
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Enhanced Feature Extraction from Evolutionary Profiles for Protein Fold Recognition
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2015 |
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[56]
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Predicting the Protein Folding Rate Based on Sequence Feature Screening and Support Vector Regression
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Acta Physico-Chimica Sinica,
2014 |
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[57]
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基于序列特征筛选与支持向量回归预测蛋白质折叠速率
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2014 |
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[58]
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Proposing a highly accurate protein structural class predictor using segmentation-based features
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BMC genomics,
2014 |
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[59]
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A Tri-Gram Based Feature Extraction Technique Using Linear Probabilities of Position Specific Scoring Matrix for Protein Fold Recognition
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NanoBioscience, IEEE Transactions on,
2014 |
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[60]
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Towards more accurate prediction of protein folding rates: a review of the existing web-based bioinformatics approaches
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Briefings in bioinformatics,
2014 |
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[61]
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Graphic Mapping of Protein-Coding DNA Sequence in Four-Dimensional Space and its Application
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Journal of Computational and Theoretical Nanoscience,
2014 |
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[62]
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Unfolded protein ensembles, folding trajectories, and refolding rate prediction
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The Journal of chemical physics,
2013 |
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[63]
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Surface Acidic Amino Acid of Pseudomonas/Halomonas Chimeric Nucleoside Diphosphate Kinase Leads Effective Recovery from Heat-Denaturation
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Protein and peptide letters,
2013 |
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[64]
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Expression pattern of recombinant organophosphorus hydrolase from Flavobacterium sp. ATCC 27551 in Escherichia coli
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Applied microbiology and biotechnology,
2013 |
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[65]
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A Framework for Modeling the Cellular Defending Mechanisms Against Genome Stress Under Radiotherapy
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NULL
2013 |
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[66]
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Investigation Binding Patterns of Human Carboxylesterase I (hCES I) with Broad Substrates by MD Simulations
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Current topics in medicinal chemistry,
2013 |
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[67]
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A Two-step Similarity-based Method for Prediction of Drug's Target Group
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Protein and peptide letters,
2013 |
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[68]
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Swfoldrate: Predicting protein folding rates from amino acid sequence with sliding window method
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Proteins: Structure, Function, and Bioinformatics,
2013 |
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[69]
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Theoretical and experimental biology in one
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2013 |
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[70]
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Theoretical and experimental biology in one—A symposium in honour of Professor Kuo-Chen Chou's 50th anniversary and Professor Richard Giegé's 40th …
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2013 |
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[71]
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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
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Journal of Biomedical Science and Engineering,
2013 |
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[72]
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蛋白质折叠速率决定因素与预测方法的研究进展
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生物物理学报,
2013 |
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[73]
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Incorporating Secondary Features into the General form of Chou's PseAAC for Predicting Protein Structural Class
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Protein and peptide letters,
2012 |
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[74]
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A pharmacophore model specific to active site of CYP1A2 with a novel molecular modeling explorer and CoMFA
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Medicinal Chemistry,
2012 |
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[75]
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A Computational Genome-wide Study of Protein Folding Rate
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NULL
2012 |
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[76]
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SOMPNN: an efficient non-parametric model for predicting transmembrane helices
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Amino acids,
2012 |
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[77]
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Prediction of protein subcellular multi-localization based on the general form of Chou's pseudo amino acid composition
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Protein and peptide letters,
2012 |
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[78]
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Dual-layer wavelet SVM for predicting protein structural class via the general form of Chou's pseudo amino acid composition
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Protein and peptide letters,
2012 |
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[79]
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Determination of protein folding kinetic types using sequence and predicted secondary structure and solvent accessibility
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Amino acids,
2012 |
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[80]
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Improved prediction of palmitoylation sites using PWMs and SVM
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Protein and peptide letters,
2011 |
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[81]
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Bioinformatic approaches for predicting substrates of proteases
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Journal of bioinformatics and computational biology,
2011 |
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[82]
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The dynamical contact order: Protein folding rate parameters based on quantum conformational transitions
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Science China Life Sciences,
2011 |
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[83]
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ifc2: an integrated web-server for improved prediction of protein structural class, fold type, and secondary structure content
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Amino acids,
2011 |
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[84]
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Three 3D graphical representations of DNA primary sequences based on the classifications of DNA bases and their applications
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Journal of theoretical biology,
2011 |
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[85]
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Multitask learning for protein subcellular location prediction
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IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB),
2011 |
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[86]
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Two-intermediate model to characterize the structure of fast-folding proteins
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Journal of theoretical biology,
2011 |
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[87]
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Predicting functions of proteins in mouse based on weighted protein-protein interaction network and protein hybrid properties
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PLoS One,
2011 |
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[88]
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Using random forest algorithm to predict β-hairpin motifs
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Protein and peptide letters,
2011 |
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[89]
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Quat-2L: a web-server for predicting protein quaternary structural attributes
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Molecular diversity,
2011 |
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[90]
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Predicting protein folding rates using the concept of Chou's pseudo amino acid composition
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Journal of computational chemistry,
2011 |
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[91]
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A Novel Method to Predict Protein-Protein Interactions Based on the Information of Protein-Protein Interaction Networks and Protein Sequence
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Protein and peptide letters,
2011 |
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[92]
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Predicting protein folding rate from amino acid sequence
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Journal of bioinformatics and computational biology,
2011 |
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[93]
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Machine learning algorithms for predicting protein folding rates and stability of mutant proteins: Comparison with statistical methods
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Current Protein and Peptide Science,
2011 |
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[94]
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Analysis of rate-limiting long-range contacts in the folding rate of three-state and two-state Proteins
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Protein and peptide letters,
2011 |
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[95]
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Analyses of Protein Sequences Using Inter-Residue Average Distance Statistics to Study Folding Processes and the Significance of Their Partial Sequences
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Protein and peptide letters,
2011 |
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[96]
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Self-similarity analysis of eubacteria genome based on weighted graph
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Journal of theoretical biology,
2011 |
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[97]
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Wenxiang: a web-server for drawing wenxiang diagrams
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Natural Science,
2011 |
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[98]
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iFC 2: an integrated web-server for improved prediction of protein structural class, fold type, and secondary structure content
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2011 |
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[99]
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-PROPAINOR: A Web-Server for Fast Prediction of Structure & Likely Functional Sites of a Protein Sequence
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The Open Bioinformatics …,
2010 |
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[100]
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Graphic rule for drug metabolism systems
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Current Drug Metabolism,
2010 |
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[101]
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Cellular responding kinetics based on a model of gene regulatory networks under radiotherapy
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Health,
2010 |
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[102]
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Virus-mPLoc: a fusion classifier for viral protein subcellular location prediction by incorporating multiple sites
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Journal of Biomolecular Structure and Dynamics,
2010 |
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[103]
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Computational prediction of properties and analysis of molecular phylogenetics of polyketide synthases in three species of Actinomycetes
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Medicinal Chemistry,
2010 |
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[104]
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Gene ontology-based protein function prediction by using sequence composition information
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Protein and peptide letters,
2010 |
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[105]
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Engineering thermostable xylanase enzyme mutant from Bacillus halodurans
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African Journal of Biotechnology,
2010 |
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[106]
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Molecular modeling of human hepatocyte PKA (cAMP-dependent protein kinase type-II) and its structure analysis
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Protein and peptide letters,
2010 |
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[107]
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Linking mutated primary structure of adrenoleukodystrophy protein with X-linked adrenoleukodystrophy
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Computer methods in biomechanics and biomedical engineering,
2010 |
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[108]
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2D-MH: A web-server for generating graphic representation of protein sequences based on the physicochemical properties of their constituent amino acids
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Journal of theoretical biology,
2010 |
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[109]
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Global and local prediction of protein folding rates based on sequence autocorrelation information
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Journal of theoretical biology,
2010 |
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[110]
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A simple method to analyze the similarity of biological sequences based on the fuzzy theory
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Journal of theoretical biology,
2010 |
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[111]
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从氨基酸序列预测蛋白质折叠速率
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Progress in Biochemistry and Biophysics,
2010 |
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[112]
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动力学接触序: 基于量子跃迁的蛋白质折叠速率参数
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中国科学: 生命科学,
2010 |
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[113]
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Prediction of disease-related genes based on hybrid features
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Current Proteomics,
2010 |
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[114]
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On the importance of the small domain in the thermostability of thermoalkalophilic lipases from L1 and T1: Insights from molecular dynamics simulation
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Protein and peptide letters,
2010 |
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[115]
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The implications of gene heterozygosity for protein folding and protein turnover
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Journal of theoretical biology,
2010 |
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[116]
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e-PROPAINOR: A Web-Server for Fast Prediction of C Structure & Likely Functional Sites of a Protein Sequence
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Open Bioinformatics Journal,
2010 |
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[117]
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Prediction of enzyme subfamily class via pseudo amino acid composition by incorporating the conjoint triad feature
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Protein and peptide letters,
2010 |
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[118]
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Plant-mPLoc: a top-down strategy to augment the power for predicting plant protein subcellular localization
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PloS one,
2010 |
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[119]
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Using the concept of Chou's pseudo amino acid composition for risk type prediction of human papillomaviruses
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Journal of theoretical biology,
2010 |
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[120]
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Analysis and prediction of the metabolic stability of proteins based on their sequential features, subcellular locations and interaction networks
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PloS one,
2010 |
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[121]
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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
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Protein and peptide letters,
2010 |
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[122]
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Molecular modeling of cytochrome P450 and drug metabolism
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Current drug metabolism,
2010 |
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[123]
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Prediction of mitochondrial proteins of malaria parasite using split amino acid composition and PSSM profile
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Amino acids,
2010 |
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[124]
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Sequence-based prediction of enzyme thermostability through bioinformatics algorithms
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Current Bioinformatics,
2010 |
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[125]
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Protein subcellular multi-localization prediction using a min-max modular support vector machine
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International journal of neural systems,
2010 |
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[126]
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Characteristic peptides of protein secondary structural motifs
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Protein and peptide letters,
2010 |
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[127]
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A summary of computational resources for protein phosphorylation
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Current Protein and Peptide Science,
2010 |
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[128]
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Classification of transcription factors using protein primary structure
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Protein and peptide letters,
2010 |
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[129]
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Accurate prediction of protein folding rates from sequence and sequence‐derived residue flexibility and solvent accessibility
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Proteins: Structure, Function, and Bioinformatics,
2010 |
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[130]
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Predicting enzyme subclasses by using support vector machine with composite vectors
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Protein and peptide letters,
2010 |
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[131]
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Identifying the hub proteins from complicated membrane protein network systems
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Medicinal Chemistry,
2010 |
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[132]
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Prediction of the parallel/antiparallel orientation of beta-strands using amino acid pairing preferences and support vector machines
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Journal of theoretical biology,
2010 |
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[133]
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Composition-based effective chain length for prediction of protein folding rates
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Physical Review E,
2010 |
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[134]
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Development of tools and database for analysis of metal binding sites in protein
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Protein and peptide letters,
2010 |
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[135]
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Protein classification using texture descriptors extracted from the protein backbone image
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Journal of Theoretical Biology,
2010 |
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[136]
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The Burrows–Wheeler similarity distribution between biological sequences based on Burrows–Wheeler transform
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Journal of theoretical biology,
2010 |
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[137]
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Predicting caspase substrate cleavage sites based on a hybrid SVMPSSM method
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Protein and Peptide Letters,
2010 |
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[138]
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GPCR-GIA: a web-server for identifying G-protein coupled receptors and their families with grey incidence analysis
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Protein Engineering Design and Selection,
2009 |
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[139]
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A network-QSAR model for prediction of genetic-component biomarkers in human colorectal cancer
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Journal of theoretical biology,
2009 |
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[140]
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Generalized lattice graphs for 2D-visualization of biological information
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Journal of theoretical biology,
2009 |
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[141]
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Estimation of relative binding free energy based on a free energy variational principle for quantitative structure activity relationship analyses
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Chemical Physics,
2009 |
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[142]
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Recent advances in developing web-servers for predicting protein attributes
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2009 |
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[143]
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Gpos-mPLoc: A top-down approach to improve the quality of predicting subcellular localization of Gram-positive bacterial proteins
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Protein and peptide letters,
2009 |
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[144]
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Review: recent advances in developing web-servers for predicting protein attributes
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Natural Science,
2009 |
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[145]
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A top-down approach to enhance the power of predicting human protein subcellular localization: Hum-mPLoc 2.0
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Analytical biochemistry,
2009 |
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