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ORI-Deep: improving the accuracy for predicting origin of replication sites by using a blend of features and long short-term memory network
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Briefings in …,
2022 |
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[2]
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Repurposing of FDA-Approved drugs to predict new inhibitors against key regulatory genes in Mycobacterium Tuberculosis
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Biocell,
2021 |
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[3]
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Splicing sites prediction of human genome using machine learning techniques
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2021 |
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[4]
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Evaluating machine learning methodologies for identification of cancer driver genes
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2021 |
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[5]
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A Machine Learning Approach for Drug‐Target Interaction Prediction using Wrapper Feature Selection and Class Balancing
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2020 |
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[6]
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Machine learning approaches and databases for prediction of drug–target interaction: a survey paper
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2020 |
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[7]
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Differential levels of alpha-1-inhibitor III, Immunoglobulin heavy chain variable region, and Hypertrophied skeletal muscle protein GTF3 in rat mammary tumorigenesis
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2020 |
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[8]
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Insight into multicopper oxidase laccase from Myrothecium verrucaria ITCC-8447: a case study using in silico and experimental analysis
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2020 |
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[9]
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Quantitative Structure-activity Relationship of Acetylcholinesterase Inhibitors based on mRMR Combined with Support Vector Regression
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2019 |
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[10]
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Docking analysis of hexanoic acid and quercetin with seven domains of polyketide synthase A provided insight into quercetin-mediated aflatoxin biosynthesis …
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2019 |
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[11]
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Bioimage-based Prediction of Protein Subcellular Location in Human Tissue with Ensemble Features and Deep Networks
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2019 |
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[12]
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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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[13]
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iCrotoK-PseAAC: Identify lysine crotonylation sites by blending position relative statistical features according to the Chou's 5-step rule
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2019 |
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[14]
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Using Chou's general PseAAC to analyze the evolutionary relationship of receptor associated proteins (RAP) with various folding patterns of protein domains
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Journal of Theoretical Biology,
2018 |
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[15]
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Recent studies of mitochondrial slc25: Integration of experimental and computational approaches
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Current Protein and Peptide Science,
2018 |
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[16]
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iPhosT-PseAAC: Identify phosphothreonine sites by incorporating sequence statistical moments into PseAAC
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Analytical Biochemistry,
2018 |
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[17]
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Solitons: A Cutting-Edge Scientific Proposal Explaining the Mechanisms of Acupuntural Action
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2018 |
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[18]
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pLoc_bal-mGpos: Predict subcellular localization of Gram-positive bacterial proteins by quasi-balancing training dataset and PseAAC
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Genomics,
2018 |
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[19]
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iPromoter-FSEn: Identification of bacterial σ70 promoter sequences using feature subspace based ensemble classifier
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Genomics,
2018 |
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[20]
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Analysis and prediction of ion channel inhibitors by using feature selection and Chou's general pseudo amino acid composition
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Journal of Theoretical Biology,
2018 |
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[21]
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The Relationship Between DNA Methylation in Key Region and the Differential Expressions of Genes in Human Breast Tumor Tissue
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2018 |
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[22]
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Characterization of proteins in different subcellular localizations for Escherichia coli K12
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Genomics,
2018 |
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[23]
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Identification of Bacterial Sigma 70 Promoter Sequences Using Feature Subspace Based Ensemble Classifier
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2018 |
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[24]
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Identification of DNA-Binding Proteins via a Voting Strategy
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Current Proteomics,
2018 |
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[25]
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Identifying 5-methylcytosine sites in RNA sequence using composite encoding feature into Chou's PseKNC
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Journal of Theoretical Biology,
2018 |
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[26]
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Computational prediction of sigma-54 promoters in bacterial genomes by integrating motif finding and machine learning strategies
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2018 |
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[27]
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Detecting Succinylation sites from protein sequences using ensemble support vector machine
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2018 |
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[28]
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A Novel Hybrid Sequence-Based Model for Identifying Anticancer Peptides
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Genes,
2018 |
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[29]
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iDNA6mA-PseKNC: Identifying DNA N6-methyladenosine sites by incorporating nucleotide physicochemical properties into PseKNC
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Genomics,
2018 |
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[30]
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pNitro-Tyr-PseAAC: Predict Nitrotyrosine Sites in Proteins by Incorporating Five Features into Chou's General PseAAC
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2018 |
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[31]
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Evaluation of Proteins Involved in Germination of Toxigenic Aspergillus Flavus Conidia and Studies on Phytochemicals as Anti-Aflatoxigenic Agents
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2018 |
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[32]
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A novel alignment-free vector method to cluster protein sequences
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Journal of Theoretical Biology,
2017 |
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[33]
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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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[34]
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MicroRNA precursors identification using reduced and hybrid features
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Molecular BioSystems,
2017 |
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[35]
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2L-piRNA: A Two-Layer Ensemble Classifier for Identifying Piwi-Interacting RNAs and Their Function
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Molecular Therapy - Nucleic Acids,
2017 |
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[36]
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A Two-Layer Computational Model for Discrimination of Enhancer and Their Types Using Hybrid Features Pace of Pseudo K-Tuple Nucleotide Composition
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Arabian Journal for Science and Engineering,
2017 |
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[37]
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iPGK-PseAAC: identify lysine phosphoglycerylation sites in proteins by incorporating four different tiers of amino acid pairwise coupling information into the general …
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Medicinal Chemistry,
2017 |
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[38]
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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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[39]
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iRNA-2methyl: Identify RNA 2'-O-methylation Sites by Incorporating Sequence-Coupled Effects into General PseKNC and Ensemble Classifier
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Medicinal Chemistry,
2017 |
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[40]
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pLoc-mGpos: incorporate key gene ontology information into general PseAAC for predicting subcellular localization of Gram-positive bacterial proteins
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2017 |
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[41]
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Microbial routes to (2R, 3R)-2, 3-butanediol: recent advances and future prospects
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Current Topics in Medicinal Chemistry,
2017 |
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[42]
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pLoc-mHum: predict subcellular localization of multi-location human proteins via general PseAAC to winnow out the crucial GO information
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Bioinformatics,
2017 |
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[43]
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Bi-PSSM: Position specific scoring matrix based intelligent computational model for identification of mycobacterial membrane proteins
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Journal of Theoretical Biology,
2017 |
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[44]
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Identification of microRNA precursors using reduced and hybrid features
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Molecular BioSystems,
2017 |
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[45]
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An Effective Feature Extraction Method on Protein Secondary Structure Class Prediction
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Journal of Bionanoscience,
2017 |
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[46]
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Impacts of Computational Biology to Medicinal Chemistry
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Medicinal Chemistry,
2017 |
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[47]
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Multi‐iPPseEvo: A Multi‐label Classifier for Identifying Human Phosphorylated Proteins by Incorporating Evolutionary Information into Chou′ s General PseAAC via Grey System Theory
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Molecular informatics,
2017 |
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[48]
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OOgenesis_Pred: A sequence-based method for predicting oogenesis proteins by six different modes of Chou's pseudo amino acid composition
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Journal of Theoretical Biology,
2017 |
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[49]
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Sequence-based discrimination of protein-RNA interacting residues using a probabilistic approach
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Journal of Theoretical Biology,
2017 |
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[50]
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Identification of potential CCR5 inhibitors through pharmacophore-based virtual screening, molecular dynamics simulation and binding free energy analysis
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Molecular BioSystems,
2016 |
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[51]
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Analysis and comparison of lignin peroxidases between fungi and bacteria using three different modes of Chou's general pseudo amino acid composition
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Journal of Theoretical Biology,
2016 |
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[52]
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Classify vertebrate hemoglobin proteins by incorporating the evolutionary information into the general PseAAC with the hybrid approach
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Journal of Theoretical Biology,
2016 |
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[53]
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iCar-PseCp: identify carbonylation sites in proteins by Monte Carlo sampling and incorporating sequence coupled effects into general PseAAC
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Oncotarget.,
2016 |
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[54]
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iPhos-PseEn: identifying phosphorylation sites in proteins by fusing different pseudo components into an ensemble classifier
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Oncotarget,
2016 |
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[55]
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iPTM-mLys: identifying multiple lysine PTM sites and their different types
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2016 |
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[56]
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“iSS-Hyb-mRMR”: Identification of splicing sites using hybrid space of pseudo trinucleotide and pseudo tetranucleotide composition
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Computer Methods and Programs in Biomedicine,
2016 |
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[57]
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pSumo-CD: Predicting sumoylation sites in proteins with covariance discriminant algorithm by incorporating sequence-coupled effects into general PseAAC
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2016 |
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[58]
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Protein fold recognition using HMM–HMM alignment and dynamic programming
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Journal of Theoretical Biology,
2016 |
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[59]
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iPhos‐PseEvo: Identifying Human Phosphorylated Proteins by Incorporating Evolutionary Information into General PseAAC via Grey System Theory
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Molecular Informatics,
2016 |
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[60]
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ProFold: Protein Fold Classification with Additional Structural Features and a Novel Ensemble Classifier
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BioMed Research International,
2016 |
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[61]
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An unusual chimeric amylosucrase generated by domain-swapping mutagenesis
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Enzyme and Microbial Technology,
2016 |
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[62]
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An estimator for local analysis of genome based on the minimal absent word
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Journal of Theoretical Biology,
2016 |
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[63]
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Identification of glucose-binding pockets in human serum albumin using support vector machine and molecular dynamics simulations
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2016 |
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[64]
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iNuc-STNC: a sequence-based predictor for identification of nucleosome positioning in genomes by extending the concept of SAAC and Chou's PseAAC
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Molecular BioSystems,
2016 |
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[65]
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Identification of DNA binding proteins using evolutionary profiles position specific scoring matrix
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Neurocomputing,
2016 |
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[66]
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Predicting lysine phosphoglycerylation with fuzzy SVM by incorporating k-spaced amino acid pairs into Chou׳ s general PseAAC
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Journal of Theoretical Biology,
2016 |
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[67]
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iACP: a sequence-based tool for identifying anticancer peptides
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Oncotarget,
2016 |
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[68]
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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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[69]
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Recent Progress in Predicting Posttranslational Modification Sites in Proteins
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Current topics in medicinal chemistry,
2016 |
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[70]
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Perspectives in Medicinal Chemistry.
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Current topics in medicinal chemistry,
2016 |
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[71]
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Modulation of cytokine network in the comorbidity of schizophrenia and tuberculosis
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Current topics in medicinal chemistry,
2016 |
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[72]
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In silico identification of putative bifunctional Plk1 inhibitors by integrative virtual screening and structural dynamics approach
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Journal of theoretical biology,
2016 |
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[73]
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ProTSAV: A protein tertiary structure analysis and validation server
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Biochimica et Biophysica Acta (BBA)-Proteins and Proteomics,
2016 |
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[74]
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Antithrombin, an Important Inhibitor in Blood Clots
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Current topics in medicinal chemistry,
2016 |
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[75]
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Association analysis between the distributions of histone modifications and gene expression in the human embryonic stem cell
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Gene,
2016 |
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[76]
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iOri-Human: identify human origin of replication by incorporating dinucleotide physicochemical properties into pseudo nucleotide composition
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Oncotarget.,
2016 |
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OP-Triplet-ELM: Identification of real and pseudo microRNA precursors using extreme learning machine with optimal features
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Journal of bioinformatics and computational biology,
2016 |
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Characteristics of Low-Frequency Molecular Phonon Modes Studied by THz Spectroscopy and Solid-State ab Initio Theory: Polymorphs I and III of Diflunisal
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The Journal of Physical Chemistry B,
2016 |
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iPPBS-Opt: a sequence-based ensemble classifier for identifying protein-protein binding sites by optimizing imbalanced training datasets
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Molecules,
2016 |
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[80]
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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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[81]
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iRNA-PseU: Identifying RNA pseudouridine sites
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Molecular Therapy - Nucleic Acids,
2016 |
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[82]
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pSumo-CD: Predicting sumoylation sites in proteins with covariance discriminant algorithm by incorporating...
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2016 |
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[83]
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Perspectives in medicinal chemistry
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2016 |
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[84]
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iPPI-Esml
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2015 |
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[85]
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Current progress in structural bioinformatics of protein-biomolecule interactions
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2015 |
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[86]
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Association of EGF rs4444903 and XPD rs13181 polymorphisms with cutaneous melanoma in Caucasians
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Medicinal Chemistry,
2015 |
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[87]
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MOWGLI: prediction of protein-MannOse interacting residues With ensemble classifiers usinG evoLutionary Information
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Journal of Biomolecular Structure and Dynamics,
2015 |
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[88]
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Recent Development of Peptide Drugs and Advance on Theory and Methodology of Peptide Inhibitor Design
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Medicinal Chemistry,
2015 |
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[89]
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Editorial: current progress in structural bioinformatics of protein-biomolecule interactions.
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Medicinal chemistry (Shāriqah (United Arab Emirates)),
2015 |
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[90]
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iSuc-PseOpt: Identifying lysine succinylation sites in proteins by incorporating sequence-coupling effects into pseudo components and optimizing imbalanced training dataset
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Analytical Biochemistry,
2015 |
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[91]
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Prediction of Nucleotide Binding Peptides Using Star Graph Topological Indices
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Molecular Informatics,
2015 |
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[92]
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iLM-2L: A two-level predictor for identifying protein lysine methylation sites and their methylation degrees by incorporating K-gap amino acid pairs into Chou׳ s general PseAAC
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Journal of Theoretical Biology,
2015 |
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[93]
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Impact of I30T and I30M substitution in MPZ gene associated with Dejerine–Sottas syndrome type B (DSSB): A molecular modeling and dynamics
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Journal of theoretical biology,
2015 |
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[94]
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Some Remarks on Prediction of Protein-Protein Interaction with Machine Learning
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Medicinal Chemistry,
2015 |
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[95]
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Modelling the molecular mechanism of protein–protein interactions and their inhibition: CypD–p53 case study
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Molecular diversity,
2015 |
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[96]
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Pseudo nucleotide composition or PseKNC: an effective formulation for analyzing genomic sequences
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Molecular BioSystems,
2015 |
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[97]
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repRNA: a web server for generating various feature vectors of RNA sequences
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Molecular Genetics and Genomics,
2015 |
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[98]
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Impacts of bioinformatics to medicinal chemistry
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Medicinal Chemistry,
2015 |
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[99]
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Identification of protein-protein binding sites by incorporating the physicochemical properties and stationary wavelet transforms into pseudo amino acid composition
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Journal of Biomolecular Structure and Dynamics,
2015 |
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[100]
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QSAR prediction of HIV-1 protease inhibitory activities using docking derived molecular descriptors
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Journal of theoretical biology,
2015 |
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[101]
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Accurate prediction of protein structural classes by incorporating PSSS and PSSM into Chou's general PseAAC
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Chemometrics and Intelligent Laboratory Systems,
2015 |
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[102]
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current progress in structural bioinformatics of protein-biomolecule interactions.
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Medicinal chemistry (Shariqah (United Arab Emirates)),
2015 |
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[103]
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Discrimination of acidic and alkaline enzyme using Chou's pseudo amino acid composition in conjunction with probabilistic neural network model
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Journal of theoretical biology,Elsevier,
2015 |
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[104]
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A two-layer classification framework for protein fold recognition
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Journal of theoretical biology,Elsevier,
2015 |
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[105]
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Gram-positive and Gram-negative protein subcellular localization by incorporating evolutionary-based descriptors into Chou? s general PseAAC
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Journal of theoretical biology,
2015 |
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[106]
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Using temperature effects to predict the interactions between two RNAs
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Journal of theoretical biology,
2015 |
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[107]
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Analysis of the multi-copied genes and the impact of the redundant protein coding sequences on gene annotation in prokaryotic genomes
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Journal of theoretical biology,
2015 |
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[108]
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Novel 3D bio-macromolecular bilinear descriptors for protein science: Predicting protein structural classes
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Journal of theoretical biology,
2015 |
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[109]
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iPPI-Esml: An ensemble classifier for identifying the interactions of proteins by incorporating their physicochemical properties and wavelet transforms into PseAAC
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Journal of theoretical biology,
2015 |
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[110]
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Thermostable chitinase II from Thermomyces lanuginosus SSBP: Cloning, structure prediction and molecular dynamics simulations
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Journal of theoretical biology,
2015 |
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[111]
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Laplacian Dynamics with Synthesis and Degradation
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Bulletin of mathematical biology,
2015 |
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[112]
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A high performance prediction of HPV genotypes by Chaos game representation and singular value decomposition
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BMC bioinformatics,
2015 |
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[113]
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Editorial (Thematic Issue: Current Progress in Structural Bioinformatics of Protein-Biomolecule Interactions)
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Medicinal Chemistry,
2015 |
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[114]
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iDNA-Methyl: Identifying DNA methylation sites via pseudo trinucleotide composition
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Analytical biochemistry,
2015 |
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[115]
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Identification of real microRNA precursors with a pseudo structure status composition approach
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PloS one,
2015 |
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[116]
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iMiRNA-PseDPC: microRNA precursor identification with a pseudo distance-pair composition approach
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Journal of Biomolecular Structure and Dynamics,
2015 |
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[117]
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基于深度学习的蛋白质二级结构预测
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计算机仿真,
2015 |
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[118]
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Comparative genomics study of Salmonella Typhimurium LT2 for the identification of putative therapeutic candidates
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Journal of theoretical biology,
2015 |
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[119]
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A comparative study of structural and conformational properties of casein kinase-1 isoforms: Insights from molecular dynamics and principal component analysis
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Journal of theoretical biology,
2015 |
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[120]
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Protein remote homology detection by combining Chou's distance-pair pseudo amino acid composition and principal component analysis
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Molecular Genetics and Genomics,
2015 |
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[121]
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Using Chou's Pseudo Amino Acid Composition and Machine Learning Method to Predict the Antiviral Peptides
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Open Bioinformatics Journal,
2015 |
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[122]
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Enhancement Predicting Accuracy for Elastin-Like Polypeptides Temperature Transition by Back Propagation Neural Network
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Protein and peptide letters,
2014 |
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[123]
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Terahertz spectroscopy and solid-state density functional theory calculation of anthracene: Effect of dispersion force on the vibrational modes
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The Journal of chemical physics,
2014 |
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[124]
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Harnessing catalysis to enhance scanning probe nanolithography
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Nanoscale,
2014 |
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[125]
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Time series clustering by a robust autoregressive metric with application to air pollution
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Chemometrics and Intelligent Laboratory Systems,
2014 |
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[126]
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Constructing a linear QSAR for some metabolizable drugs by human or pig flavin-containing monooxygenases using some molecular features selected by a genetic algorithm trained SVM
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Journal of theoretical biology,
2014 |
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[127]
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Multi-Label Learning With Fuzzy Hypergraph Regularizition for Protein Subcellular Location Prediction
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NanoBioscience, IEEE Transactions on (Volume:13,Issue: 4) ,
2014 |
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[128]
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Apolipoprotein E Gene Variants of Alzheimer's Disease and Vascular Dementia Patients in a Community Population of Nanking
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Medicinal Chemistry,
2014 |
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[129]
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A QSPR-like model for multilocus genotype networks of Fasciola hepatica in Northwest Spain
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Journal of theoretical biology,
2014 |
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[130]
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Research/Review: Insights into the Mutation-Induced Dysfunction of Arachidonic Acid Metabolism from Modeling of Human CYP2J2
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Current drug metabolism,
2014 |
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[131]
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Prediction of Vanillin and Glutamate Productions in Yeast Using a Hybrid of Continuous Bees Algorithm and Flux Balance Analysis (CBAFBA)
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Current Bioinformatics,
2014 |
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[132]
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An effective haplotype assembly algorithm based on hypergraph partitioning
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Journal of Theoretical Biology,Elsevier,
2014 |
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[133]
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Protein fold recognition by alignment of amino acid residues using kernelized dynamic time warping
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Journal of theoretical biology,
2014 |
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[134]
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iCTX-Type: A Sequence-Based Predictor for Identifying the Types of Conotoxins in Targeting Ion Channels
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BioMed Research International,
2014 |
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[135]
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Sequence-specific flexibility organization of splicing flanking sequence and prediction of splice sites in the human genome
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Chromosome Research,Springer,
2014 |
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[136]
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Molecular modeling, simulation and virtual screening of ribosomal phosphoprotein P1 from Plasmodium falciparum
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Journal of theoretical biology,
2014 |
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[137]
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Research/Review: Structure and Linkage Disequilibrium Analysis of Adamantane Resistant Mutations in Influenza Virus M2 Proton Channel
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Current drug metabolism,
2014 |
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[138]
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iDrug-Target: Predicting the interactions between drug compounds and target proteins in cellular networking via benchmark dataset optimization approach
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Journal of Biomolecular Structure and Dynamics,just-accepted,
2014 |
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[139]
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iUbiq-Lys: prediction of lysine ubiquitination sites in proteins by extracting sequence evolution information via a gray system model
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Journal of Biomolecular Structure and Dynamics,ahead-of-print,
2014 |
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[140]
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Chou? s pseudo amino acid composition improves sequence-based antifreeze protein prediction
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Journal of theoretical biology,Elsevier,
2014 |
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[141]
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A set of descriptors for identifying the protein–drug interaction in cellular networking
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Journal of theoretical biology,Elsevier,
2014 |
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[142]
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Prediction of protein structure classes by incorporating different protein descriptors into general Chou's pseudo amino acid composition
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|
Journal of theoretical biology,Elsevier,
2014 |
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[143]
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Identification of DNA-binding proteins by incorporating evolutionary information into pseudo amino acid composition via the top-n-gram approach
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Journal of Biomolecular Structure and Dynamics,ahead-of-print,
2014 |
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[144]
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Molecular Science for Drug Development and Biomedicine
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International journal of molecular sciences,
2014 |
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[145]
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SAHA-based novel HDAC inhibitor design by core hopping method
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Journal of Molecular Graphics and Modelling,
2014 |
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[146]
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Transmission of intra-cellular genetic information: A system proposal
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Journal of theoretical biology,Elsevier,
2014 |
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[147]
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Screening drug target proteins based on sequence information
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Journal of biomedical informatics,Elsevier,
2014 |
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[148]
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Communities in the iron superoxide dismutase amino acid network
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Journal of theoretical biology,Elsevier,
2014 |
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[149]
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A Multi-label Classifier for Prediction Membrane Protein Functional Types in Animal
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The Journal of membrane biology,Springer,
2014 |
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[150]
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Protein submitochondria localization from integrated sequence repesentation and SVM-based backward feature extraction
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Mol. BioSyst.,
2014 |
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[151]
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Human proteins characterization with subcellular localizations
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Journal of theoretical biology,Elsevier,
2014 |
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[152]
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iMethyl-PseAAC: Identification of Protein Methylation Sites via a Pseudo Amino Acid Composition Approach
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BioMed Research International,Hindawi Publishing Corporation,
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A protein structural classes prediction method based on PSI-BLAST profile
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Analytical Equilibrium Solutions of Biochemical Systems with Synthesis and Degradation
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arXiv preprint arXiv:1404.6477,
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Predict protein structural class for low-similarity sequences by evolutionary difference information into the general form of Chou? s pseudo amino acid composition
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Journal of theoretical biology,Elsevier,
2014 |
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Neural network and SVM classifiers accurately predict lipid binding proteins, irrespective of sequence homology
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Journal of theoretical biology,Elsevier,
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iTIS-PseTNC: a sequence-based predictor for identifying translation initiation site in human genes using pseudo trinucleotide composition
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International journal of molecular sciences,
2014 |
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iRSpot-TNCPseAAC: Identify recombination spots with trinucleotide composition and pseudo amino acid components
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International journal of molecular sciences,
2014 |
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Combining evolutionary information extracted from frequency profiles with sequence-based kernels for protein remote homology detection
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Bioinformatics,
2014 |
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iNitro-Tyr: Prediction of nitrotyrosine sites in proteins with general pseudo amino acid composition
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PloS one,
2014 |
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iNuc-PseKNC: a sequence-based predictor for predicting nucleosome positioning in genomes with pseudo k-tuple nucleotide composition
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Bioinformatics,
2014 |
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iDNA-Prot| dis: Identifying DNA-binding proteins by incorporating amino acid distance-pairs and reduced alphabet profile into the general pseudo amino acid composition
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PloS one,
2014 |
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Prediction of protein S-nitrosylation sites based on adapted normal distribution bi-profile Bayes and Chou's pseudo amino acid composition
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International journal of molecular sciences,
2014 |
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iNR-Drug: predicting the interaction of drugs with nuclear receptors in cellular networking
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International journal of molecular sciences,
2014 |
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Prediction of bacterial protein subcellular localization by incorporating various features into Chou's PseAAC and a backward feature selection approach
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Biochimie,Elsevier,
2014 |
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Discriminating protein structure classes by incorporating Pseudo Average Chemical Shift to Chou's general PseAAC and Support Vector Machine
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Computer methods and programs in biomedicine,
2014 |
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iPro54-PseKNC: a sequence-based predictor for identifying sigma-54 promoters in prokaryote with pseudo k-tuple nucleotide composition
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Nucleic acids research,
2014 |
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PseKNC: A flexible web server for generating pseudo K-tuple nucleotide composition
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Analytical biochemistry,Elsevier,
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iHyd-PseAAC: predicting hydroxyproline and hydroxylysine in proteins by incorporating dipeptide position-specific propensity into pseudo amino acid composition
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International journal of molecular sciences,
2014 |
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k-Partite cliques of protein interactions: A novel subgraph topology for functional coherence analysis on PPI networks
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Journal of theoretical biology,Elsevier,
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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
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Journal of theoretical biology,
2014 |
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Accurate prediction of protein structural classes by incorporating predicted secondary structure information into the general form of Chou's pseudo amino acid composition
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Journal of theoretical biology,
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Computer-Aided Perspective for the Design of Flexible HIV Non- Nucleoside Reverse Transcriptase Inhibitors (NNRTIs): de-novo Drug Design, Virtual Screening and Molecular Dynamics Simulations
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Letters in Drug Design & Discovery,
2014 |
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2014 |
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k-Partite cliques of protein interactions: A novel subgraph topology for functional coherence analysis on PPI networks
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Journal of Theoretical Biology,
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iNitro-Tyr: Prediction of Nitrotyrosine Sites in Proteins with General Pseudo Amino Acid
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iDNA-Prot| dis: Identifying DNA-Binding Proteins by Incorporating Amino Acid Distance-Pairs and Reduced
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iSS-PseDNC: Identifying Splicing Sites Using Pseudo Dinucleotide Composition
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BioMed Research International,Hindawi Publishing Corporation,
2014 |
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Grappling the high altitude for safe edible bamboo shoots with rich nutritional attributes and escaping cyanogenic toxicity
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BioMed research international,
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Recent advances in predicting protein classification and their applications to drug development
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Current topics in medicinal chemistry,
2013 |
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iGPCR-Drug: A web server for predicting interaction between GPCRs and drugs in cellular networking
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PloS one,
2013 |
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Predict drug-protein interaction in cellular networking
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Current topics in medicinal chemistry,
2013 |
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iSNO-AAPair: incorporating amino acid pairwise coupling into PseAAC for predicting cysteine S-nitrosylation sites in proteins
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PeerJ,
2013 |
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iCDI-PseFpt: identify the channel–drug interaction in cellular networking with PseAAC and molecular fingerprints
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Journal of theoretical biology,Elsevier,
2013 |
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iEzy-Drug: A web server for identifying the interaction between enzymes and drugs in cellular networking
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BioMed research international,Hindawi Publishing Corporation,
2013 |
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A hybrid computational model for the effects of maspin on cancer cell dynamics
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Journal of theoretical biology,Elsevier,
2013 |
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PFP-RFSM: Protein fold prediction by using random forests and sequence motifs
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Journal of Biomedical Science and Engineering,
2013 |
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Functional Roles of Benzothiazole Motif in Antiepileptic Drug Research
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Mini reviews in medicinal chemistry,
2013 |
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