Recent Progress in Predicting Posttranslational Modification Sites in Proteins.

No abstract is available for this paper.

• Publication year

  2015

• Venue

  Current Topics in Medicinal Chemistry

• Publication date

  2015-11-04

• Fields of study

  Biology, Medicine

• Identifiers
  DOI 10.2174/1568026615666150819110421PMID 26286211
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar, PubMed

• No claims are published for this paper.

• No concepts are published for this paper.

• repRNA: a web server for generating various feature vectors of RNA sequences

  2016cited by this paper
• iRNA-Methyl: Identifying N(6)-methyladenosine sites using pseudo nucleotide composition.

  2015cited by this paper
• iUbiq-Lys: prediction of lysine ubiquitination sites in proteins by extracting sequence evolution information via a gray system model

  2015cited by this paper
• Gram-positive and Gram-negative protein subcellular localization by incorporating evolutionary-based descriptors into Chou׳s general PseAAC.

  2015cited by this paper
• iDNA-Methyl: identifying DNA methylation sites via pseudo trinucleotide composition.

  2015cited by this paper
• iPPI-Esml: An ensemble classifier for identifying the interactions of proteins by incorporating their physicochemical properties and wavelet transforms into PseAAC.

  2015cited by this paper
• Identification of Real MicroRNA Precursors with a Pseudo Structure Status Composition Approach

  2015cited by this paper
• 3D structural conformation and functional domains of polysialyltransferase ST8Sia IV required for polysialylation of neural cell adhesion molecules.

  2015cited by this paper
• Impacts of bioinformatics to medicinal chemistry.

  2015cited by this paper
• Prediction of β-lactamase and its class by Chou's pseudo-amino acid composition and support vector machine.

  2015cited by this paper
• repDNA: a Python package to generate various modes of feature vectors for DNA sequences by incorporating user-defined physicochemical properties and sequence-order effects

  2015cited by this paper
• Pse-in-One: a web server for generating various modes of pseudo components of DNA, RNA, and protein sequences

  2015cited by this paper
• Discrimination of acidic and alkaline enzyme using Chou's pseudo amino acid composition in conjunction with probabilistic neural network model.

  2015cited by this paper
• Pseudo nucleotide composition or PseKNC: an effective formulation for analyzing genomic sequences.

  2015cited by this paper
• PseKNC-General: a cross-platform package for generating various modes of pseudo nucleotide compositions

  2015cited by this paper
• PseDNA‐Pro: DNA‐Binding Protein Identification by Combining Chou’s PseAAC and Physicochemical Distance Transformation

  2015cited by this paper
• GPS-SUMO: a tool for the prediction of sumoylation sites and SUMO-interaction motifs

  2014cited by this paper
• PECM: prediction of extracellular matrix proteins using the concept of Chou's pseudo amino acid composition.

  2014cited by this paper
• Chou's pseudo amino acid composition improves sequence-based antifreeze protein prediction.

  2014cited by this paper
• PseAAC-General: Fast Building Various Modes of General Form of Chou’s Pseudo-Amino Acid Composition for Large-Scale Protein Datasets

  2014cited by this paper
• Predicting peroxidase subcellular location by hybridizing different descriptors of Chou' pseudo amino acid patterns.

  2014cited by this paper
• PSNO: Predicting Cysteine S-Nitrosylation Sites by Incorporating Various Sequence-Derived Features into the General Form of Chou’s PseAAC

  2014cited by this paper
• iMethyl-PseAAC: Identification of Protein Methylation Sites via a Pseudo Amino Acid Composition Approach

  2014cited by this paper
• iPro54-PseKNC: a sequence-based predictor for identifying sigma-54 promoters in prokaryote with pseudo k-tuple nucleotide composition

  2014cited by this paper
• Accurate prediction of protein structural classes by incorporating predicted secondary structure information into the general form of Chou's pseudo amino acid composition.

  2014cited by this paper
• iCTX-Type: A Sequence-Based Predictor for Identifying the Types of Conotoxins in Targeting Ion Channels

  2014cited by this paper
• iNuc-PseKNC: a sequence-based predictor for predicting nucleosome positioning in genomes with pseudo k-tuple nucleotide composition

  2014cited by this paper
• iHyd-PseAAC: Predicting Hydroxyproline and Hydroxylysine in Proteins by Incorporating Dipeptide Position-Specific Propensity into Pseudo Amino Acid Composition

  2014cited by this paper
• Predict protein structural class for low-similarity sequences by evolutionary difference information into the general form of Chou's pseudo amino acid composition.

  2014cited by this paper
• iSS-PseDNC: Identifying Splicing Sites Using Pseudo Dinucleotide Composition

  2014cited by this paper
• 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.

  2014cited by this paper
• Prediction of bacterial protein subcellular localization by incorporating various features into Chou's PseAAC and a backward feature selection approach.

  2014cited by this paper
• iRSpot-TNCPseAAC: Identify Recombination Spots with Trinucleotide Composition and Pseudo Amino Acid Components

  2014cited by this paper
• iTIS-PseTNC: a sequence-based predictor for identifying translation initiation site in human genes using pseudo trinucleotide composition.

  2014cited by this paper
• Prediction of protein structure classes by incorporating different protein descriptors into general Chou's pseudo amino acid composition.

  2014cited by this paper
• Predicting anticancer peptides with Chou's pseudo amino acid composition and investigating their mutagenicity via Ames test.

  2014cited by this paper
• Molecular Science for Drug Development and Biomedicine

  2014cited by this paper
• iNitro-Tyr: Prediction of Nitrotyrosine Sites in Proteins with General Pseudo Amino Acid Composition

  2014cited by this paper
• Discriminating protein structure classes by incorporating Pseudo Average Chemical Shift to Chou's general PseAAC and Support Vector Machine

  2014cited by this paper
• PseKNC: a flexible web server for generating pseudo K-tuple nucleotide composition.

  2014cited by this paper
• Using radial basis function on the general form of Chou's pseudo amino acid composition and PSSM to predict subcellular locations of proteins with both single and multiple sites

  2013cited by this paper
• iAMP-2L: a two-level multi-label classifier for identifying antimicrobial peptides and their functional types.

  2013cited by this paper
• Using ensemble SVM to identify human GPCRs N-linked glycosylation sites based on the general form of Chou's PseAAC.

  2013cited by this paper
• An alignment-free method to find similarity among protein sequences via the general form of Chou’s pseudo amino acid composition

  2013cited by this paper
• Prediction of essential proteins in prokaryotes by incorporating various physico-chemical features into the general form of Chou's pseudo amino acid composition.

  2013cited by this paper
• iRSpot-PseDNC: identify recombination spots with pseudo dinucleotide composition

  2013cited by this paper
• Protein Remote Homology Detection by Combining Chou’s Pseudo Amino Acid Composition and Profile‐Based Protein Representation

  2013cited by this paper
• Signal Propagation in Protein Interaction Network during Colorectal Cancer Progression

  2013cited by this paper
• iLoc-Animal: a multi-label learning classifier for predicting subcellular localization of animal proteins.

  2013cited by this paper
• Predicting membrane protein types by incorporating protein topology, domains, signal peptides, and physicochemical properties into the general form of Chou's pseudo amino acid composition.

  2013cited by this paper
• GOASVM: a subcellular location predictor by incorporating term-frequency gene ontology into the general form of Chou's pseudo-amino acid composition.

  2013cited by this paper
• Some remarks on predicting multi-label attributes in molecular biosystems.

  2013cited by this paper
• iSNO-PseAAC: Predict Cysteine S-Nitrosylation Sites in Proteins by Incorporating Position Specific Amino Acid Propensity into Pseudo Amino Acid Composition

  2013cited by this paper
• Virus-ECC-mPLoc: a multi-label predictor for predicting the subcellular localization of virus proteins with both single and multiple sites based on a general form of Chou's pseudo amino acid composition.

  2013cited by this paper
• EuLoc: a web-server for accurately predict protein subcellular localization in eukaryotes by incorporating various features of sequence segments into the general form of Chou’s PseAAC

  2013cited by this paper
• A Multilabel Model Based on Chou’s Pseudo–Amino Acid Composition for Identifying Membrane Proteins with Both Single and Multiple Functional Types

  2013cited by this paper
• iSNO-AAPair: incorporating amino acid pairwise coupling into PseAAC for predicting cysteine S-nitrosylation sites in proteins

  2013cited by this paper
• Discriminating bioluminescent proteins by incorporating average chemical shift and evolutionary information into the general form of Chou's pseudo amino acid composition.

  2013cited by this paper
• propy: a tool to generate various modes of Chou's PseAAC

  2013cited by this paper
• Prediction of protein subcellular multi-localization based on the general form of Chou's pseudo amino acid composition.

  2012cited by this paper
• Prediction of allergenic proteins by means of the concept of Chou's pseudo amino acid composition and a machine learning approach.

  2012cited by this paper
• iLoc-Hum: using the accumulation-label scale to predict subcellular locations of human proteins with both single and multiple sites.

  2012cited by this paper
• Predicting protein solubility by the general form of Chou's pseudo amino acid composition: approached from chaos game representation and fractal dimension.

  2012cited by this paper
• Incorporating secondary features into the general form of Chou's PseAAC for predicting protein structural class.

  2012cited by this paper
• Identify DNA-binding proteins with optimal Chou's amino acid composition.

  2012cited by this paper
• Predicting antibacterial peptides by the concept of Chou's pseudo-amino acid composition and machine learning methods.

  2012cited by this paper
• Predicting protein structural class by incorporating patterns of over-represented k-mers into the general form of Chou's PseAAC.

  2012cited by this paper
• Predict mycobacterial proteins subcellular locations by incorporating pseudo-average chemical shift into the general form of Chou's pseudo amino acid composition.

  2012cited by this paper
• Identifying Bacterial Virulent Proteins by Fusing a Set of Classifiers Based on Variants of Chou's Pseudo Amino Acid Composition and on Evolutionary Information

  2012cited by this paper
• Dual-layer wavelet SVM for predicting protein structural class via the general form of Chou's pseudo amino acid composition.

  2012cited by this paper
• iNuc-PhysChem: A Sequence-Based Predictor for Identifying Nucleosomes via Physicochemical Properties

  2012cited by this paper
• Discriminating outer membrane proteins with Fuzzy K-nearest Neighbor algorithms based on the general form of Chou's PseAAC.

  2012cited by this paper
• Multi-kernel transfer learning based on Chou's PseAAC formulation for protein submitochondria localization.

  2012cited by this paper
• Predicting protein-protein interactions by combing various sequence- derived features into the general form of Chou's Pseudo amino acid composition.

  2012cited by this paper
• PseAAC-Builder: a cross-platform stand-alone program for generating various special Chou's pseudo-amino acid compositions.

  2012cited by this paper
• Predicting protein fold types by the general form of Chou's pseudo amino acid composition: approached from optimal feature extractions.

  2012cited by this paper
• Identifying protein quaternary structural attributes by incorporating physicochemical properties into the general form of Chou's PseAAC via discrete wavelet transform.

  2012cited by this paper
• Predicting the classification of transcription factors by incorporating their binding site properties into a novel mode of Chou's pseudo amino acid composition.

  2012cited by this paper
• Predicting plant protein subcellular multi-localization by Chou's PseAAC formulation based multi-label homolog knowledge transfer learning.

  2012cited by this paper
• Hepatitis C Virus Network Based Classification of Hepatocellular Cirrhosis and Carcinoma

  2012cited by this paper
• Predicting viral protein subcellular localization with Chou's pseudo amino acid composition and imbalance-weighted multi-label K-nearest neighbor algorithm.

  2012cited by this paper
• Identification of Colorectal Cancer Related Genes with mRMR and Shortest Path in Protein-Protein Interaction Network

  2012cited by this paper
• Predicting protein folding rates using the concept of Chou's pseudo amino acid composition

  2011cited by this paper
• Wavelet images and Chou’s pseudo amino acid composition for protein classification

  2011cited by this paper
• A Multi-Label Classifier for Predicting the Subcellular Localization of Gram-Negative Bacterial Proteins with Both Single and Multiple Sites

  2011cited by this paper
• Prediction of GABAA receptor proteins using the concept of Chou's pseudo-amino acid composition and support vector machine.

  2011cited by this paper
• NR-2L: A Two-Level Predictor for Identifying Nuclear Receptor Subfamilies Based on Sequence-Derived Features

  2011cited by this paper
• OligoPred: a web-server for predicting homo-oligomeric proteins by incorporating discrete wavelet transform into Chou's pseudo amino acid composition.

  2011cited by this paper
• AFP-Pred: A random forest approach for predicting antifreeze proteins from sequence-derived properties.

  2011cited by this paper
• GPCR-2L: predicting G protein-coupled receptors and their types by hybridizing two different modes of pseudo amino acid compositions.

  2011cited by this paper
• GPS-YNO2: computational prediction of tyrosine nitration sites in proteins.

  2011cited by this paper
• Supersecondary structure prediction using Chou's pseudo amino acid composition

  2011cited by this paper
• Using a novel AdaBoost algorithm and Chou's Pseudo amino acid composition for predicting protein subcellular localization.

  2011cited by this paper
• Decoding signalling networks by mass spectrometry-based proteomics

  2010cited by this paper
• Some remarks on protein attribute prediction and pseudo amino acid composition

  2010cited by this paper
• 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.

  2010cited by this paper
• Using the concept of Chou's pseudo amino acid composition for risk type prediction of human papillomaviruses.

  2010cited by this paper
• Prediction of G-protein-coupled receptor classes in low homology using Chou's pseudo amino acid composition with approximate entropy and hydrophobicity patterns.

  2010cited by this paper
• Machine learning approach to predict protein phosphorylation sites by incorporating evolutionary information

  2010cited by this paper
• Musite, a Tool for Global Prediction of General and Kinase-specific Phosphorylation Sites*

  2010cited by this paper

• Progress of Deep Learning Prediction of CD8+ T‐Cell Epitopes

  2025cites this paper
• CCL18 and EGF May Serve as Potential Prognostic Biomarkers and Therapeutic Targets for Human Breast Cancer

  2025cites this paper
• IDH1/MDH1 deacetylation promotes acute liver failure by regulating NETosis

  2024cites this paper
• Modulating Phosphorylation by Proximity-Inducing Modalities for Cancer Therapy.

  2024cites this paper
• O-GlcNAcylated RALY Contributes to Hepatocellular Carcinoma Cells Proliferation by Regulating USP22 mRNA Nuclear Export

  2024cites this paper
• Dissecting the Immune System through Gene Regulation.

  2024cites this paper
• Genetic association in CYP3A4 and CYP3A5 genes elevate the risk of prostate cancer

  2023cites this paper
• Regulation of Prenylated Rat Sarcoma Proteins via Sequential Azidation-Selenylation and a Click Reaction

  2023cites this paper
• A novel cell-permeable peptide prevents protein sumoylation and supports the mislocalization and aggregation of TDP-43.

  2023cites this paper
• Investigating the Precise Identification of Citrullination Sites with High-Performance Score Metrics using a Powerful Computation Predicting Tool.

  2023cites this paper
• Current advances in biopharmaceutical informatics: guidelines, impact and challenges in the computational developability assessment of antibody therapeutics

  2022cites this paper
• Post-translational modifications: emerging regulators manipulating jasmonate biosynthesis and signaling

  2022cites this paper
• Post-translational modification of protein and disease onset- recent advances

  2022cites this paper
• Deciphering combinatorial post-translational modifications by top-down mass spectrometry.

  2022cites this paper
• Multi-Omics Approach Reveals Dysregulation of Protein Phosphorylation Correlated with Lipid Metabolism in Mouse Non-Alcoholic Fatty Liver

  2022cites this paper
• predML-Site: Predicting Multiple Lysine PTM Sites With Optimal Feature Representation and Data Imbalance Minimization

  2021cites this paper
• Current Status of the Use of Multifunctional Enzymes as Anti-Cancer Drug Targets

  2021cites this paper
• Post-translational modifications in proteins: resources, tools and prediction methods

  2021cites this paper
• Computational identification of multiple lysine PTM sites by analyzing the instance hardness and feature importance

  2021cites this paper
• predPhogly-Site: Predicting phosphoglycerylation sites by incorporating probabilistic sequence-coupling information into PseAAC and addressing data imbalance

  2021cites this paper
• RETRACTED ARTICLE: An insightful 20-year recollection since the birth of pseudo amino acid components

  2020cites this paper
• The pLoc_bal-mHum is a Powerful Web-Serve for Predicting the Subcellular Localization of Human Proteins Purely Based on Their Sequence Information

  2020cites this paper
• Natural Science, 2017

  2020cites this paper
• The Significant and Profound Impacts of Gordon Life Science Institute

  2020cites this paper
• Optimization of Serine Phosphorylation Prediction in Proteins by Comparing Human Engineered Features and Deep Representations.

  2020cites this paper
• iPhosS(Deep)-PseAAC: Identification of Phosphoserine Sites in Proteins Using Deep Learning on General Pseudo Amino Acid Compositions

  2020cites this paper
• Prediction of human phosphorylated proteins by extracting multi-perspective discriminative features from the evolutionary profile and physicochemical properties through LFDA

  2020cites this paper
• The Pandemic Pestilences and Internet Institutes

  2020influential citation
• pLoc_Deep-mHum: Predict Subcellular Localization of Human Proteins by Deep Learning

  2020cites this paper
• The End of Our Earth Is Certainly to Come: “When”? and “Why”?

  2020cites this paper
• Sumoylation as an Emerging Target in Therapeutics against Cancer.

  2020cites this paper
• Showcase to Illustrate How the Webserver ploc_Bal-Meuk Is Working

  2020cites this paper
• Identification of Human Secretome and Membrane Proteome-Based Cancer Biomarkers Utilizing Bioinformatics

  2020cites this paper
• The pLoc_bal-mGneg Predictor is a Powerful Web-Server for Identifying the Subcellular Localization of Gram-Negative Bacterial Proteins based on their Sequences Information Alone

  2020cites this paper
• Accurate Identification of Human Phosphorylated Proteins by Ensembling Supervised Kernel Self‐organizing Maps

  2020cites this paper
• Application of Machine Learning Approaches for the Design and Study of Anticancer Drugs.

  2019cites this paper
• Proteomic analysis and prediction of amino acid variations that influence protein posttranslational modifications

  2019cites this paper
• pDHS-DSET: Prediction of DNase I hypersensitive sites in plant genome using DS evidence theory.

  2019cites this paper
• Relationship Between DNA Methylation in Key Region and the Differential Expressions of Genes in Human Breast Tumor Tissue

  2019cites this paper
• Fu-SulfPred: Identification of Protein S-sulfenylation Sites by Fusing Forests via Chou's General PseAAC.

  2019cites this paper
• The Multiple Applications and Possible Mechanisms of the Hyperbaric Oxygenation Therapy.

  2019cites this paper
• SPalmitoylC-PseAAC: A sequence-based model developed via Chou's 5-steps rule and general PseAAC for identifying S-palmitoylation sites in proteins.

  2019cites this paper
• iRNA-PseKNC(2methyl): Identify RNA 2'-O-methylation sites by convolution neural network and Chou's pseudo components.

  2019cites this paper
• GlyStruct: glycation prediction using structural properties of amino acid residues

  2019cites this paper
• iNR-2L: A two-level sequence-based predictor developed via Chou's 5-steps rule and general PseAAC for identifying nuclear receptors and their families.

  2019cites this paper
• Metabolism of Oxalate in Humans: A Potential Role Kynurenine Aminotransferase/Glutamine Transaminase/Cysteine Conjugate Beta-lyase Plays in Hyperoxaluria.

  2019cites this paper
• Lysine Malonylation Identification in E. coli with Multiple Features

  2019cites this paper
• Mechanistic Insights of Chemicals and Drugs as Risk Factors for Systemic Lupus Erythematosus.

  2019cites this paper
• Prediction of Nitrosocysteine Sites Using Position and Composition Variant Features

  2019cites this paper
• Advances in Electrochemistry for Monitoring Cellular Chemical Flux.

  2019cites this paper
• Prediction of lysine formylation sites using the composition of k-spaced amino acid pairs via Chou's 5-steps rule and general pseudo components.

  2019cites this paper
• Progresses in Predicting Post-translational Modification

  2019cites this paper
• Proposing Pseudo Amino Acid Components is an Important Milestone for Proteome and Genome Analyses

  2019cites this paper
• iN6-Methyl (5-step): Identifying RNA N6-methyladenosine sites using deep learning mode via Chou's 5-step rules and Chou's general PseKNC

  2019cites this paper
• iMethylK_pseAAC: Improving Accuracy of Lysine Methylation Sites Identification by Incorporating Statistical Moments and Position Relative Features into General PseAAC via Chou’s 5-steps Rule

  2019cites this paper
• iSulfoTyr-PseAAC: Identify Tyrosine Sulfation Sites by Incorporating Statistical Moments via Chou’s 5-steps Rule and Pseudo Components

  2019cites this paper
• A Possible Modulation Mechanism of Intramolecular and Intermolecular Interactions for NCAM Polysialylation and Cell Migration.

  2019cites this paper
• Impacts of pseudo amino acid components and 5-steps rule to proteomics and proteome analysis.

  2019cites this paper
• iProtease-PseAAC(2L): A two-layer predictor for identifying proteases and their types using Chou's 5-step-rule and general PseAAC.

  2019cites this paper
• An insightful 10-year recollection since the emergence of the 5-steps rule.

  2019cites this paper
• RAACBook: a web server of reduced amino acid alphabet for sequence-dependent inference by using Chou’s five-step rule

  2019cites this paper
• The pLoc_bal-mPlant is a powerful artificial intelligence tool for predicting the subcellular localization of plant proteins purely based on their sequence information

  2019cites this paper
• Sequence and structure‐based characterization of ubiquitination sites in human and yeast proteins using Chou's sample formulation

  2019cites this paper
• A Novel Hybrid Sequence-Based Model for Identifying Anticancer Peptides

  2018cites this paper
• iDNA6mA-PseKNC: Identifying DNA N6-methyladenosine sites by incorporating nucleotide physicochemical properties into PseKNC.

  2018cites this paper
• Predicting lysine lipoylation sites using bi-profile bayes feature extraction and fuzzy support vector machine algorithm.

  2018cites this paper
• Mutli-Features Prediction of Protein Translational Modification Sites

  2018cites this paper
• Detecting Succinylation sites from protein sequences using ensemble support vector machine

  2018cites this paper
• Improving succinylation prediction accuracy by incorporating the secondary structure via helix, strand and coil, and evolutionary information from profile bigrams

  2018cites this paper
• Success: evolutionary and structural properties of amino acids prove effective for succinylation site prediction

  2018cites this paper
• Prediction of DNase I hypersensitive sites in plant genome using multiple modes of pseudo components.

  2018cites this paper
• iPhosY-PseAAC: identify phosphotyrosine sites by incorporating sequence statistical moments into PseAAC

  2018cites this paper
• New Achievements in Bioinformatics Prediction of Post Translational Modification of Proteins.

  2017cites this paper
• Multi‐iPPseEvo: A Multi‐label Classifier for Identifying Human Phosphorylated Proteins by Incorporating Evolutionary Information into Chou′s General PseAAC via Grey System Theory

  2017cites this paper
• Enzymatic and non‐enzymatic detoxification of 4‐hydroxynonenal: Methodological aspects and biological consequences

  2017cites this paper
• S-SulfPred: A sensitive predictor to capture S-sulfenylation sites based on a resampling one-sided selection undersampling-synthetic minority oversampling technique.

  2017cites this paper
• iKcr-PseEns: Identify lysine crotonylation sites in histone proteins with pseudo components and ensemble classifier.

  2017cites this paper
• Applying Knowledge of Enzyme Biochemistry to the Prediction of Functional Sites for Aiding Drug Discovery.

  2017cites this paper
• Role of Dopamine Signaling in Drug Addiction.

  2017cites this paper
• iPreny-PseAAC: Identify C-terminal Cysteine Prenylation Sites in Proteins by Incorporating Two Tiers of Sequence Couplings into PseAAC.

  2017cites this paper
• iPGK-PseAAC: Identify Lysine Phosphoglycerylation Sites in Proteins by Incorporating Four Different Tiers of Amino Acid Pairwise Coupling Information into the General PseAAC.

  2017cites this paper
• An Unprecedented Revolution in Medicinal Chemistry Driven by the Progress of Biological Science.

  2017cites this paper
• SucStruct: Prediction of succinylated lysine residues by using structural properties of amino acids.

  2017cites this paper
• Docking Studies, Synthesis and Biological Evaluation of β-aryl-β-hydroxy Propanoic Acids for Anti-inflammatory Activity.

  2017cites this paper
• iRNA-2methyl: Identify RNA 2'-O-methylation Sites by Incorporating Sequence-Coupled Effects into General PseKNC and Ensemble Classifier.

  2017cites this paper
• Chlorella vulgaris Induces Apoptosis of Human Non-Small Cell Lung Carcinoma (NSCLC) Cells.

  2017cites this paper
• Genome-Wide Prediction of DNA Methylation Using DNA Composition and Sequence Complexity in Human

  2017cites this paper
• PSSM-Suc: Accurately predicting succinylation using position specific scoring matrix into bigram for feature extraction.

  2017cites this paper
• Pse-Analysis: a python package for DNA/RNA and protein/peptide sequence analysis based on pseudo components and kernel methods

  2017cites this paper
• iRNA-PseColl: Identifying the Occurrence Sites of Different RNA Modifications by Incorporating Collective Effects of Nucleotides into PseKNC

  2017cites this paper
• Pse-in-One 2.0: An Improved Package of Web Servers for Generating Various Modes of Pseudo Components of DNA, RNA, and Protein Sequences

  2017cites this paper
• Prediction of protein N-formylation using the composition of k-spaced amino acid pairs.

  2017cites this paper
• 2L-piRNA: A Two-Layer Ensemble Classifier for Identifying Piwi-Interacting RNAs and Their Function

  2017cites this paper
• Performance measures in evaluating machine learning based bioinformatics predictors for classifications

  2016cites this paper
• AGIA Tag System Based on a High Affinity Rabbit Monoclonal Antibody against Human Dopamine Receptor D1 for Protein Analysis

  2016cites this paper
• Understanding the Structural Basis of ALDH-2 Inhibition by Molecular Docking.

  2016cites this paper
• iPTM-mLys: identifying multiple lysine PTM sites and their different types

  2016cites this paper
• Predicting lysine phosphoglycerylation with fuzzy SVM by incorporating k-spaced amino acid pairs into Chou׳s general PseAAC.

  2016cites this paper
• An estimator for local analysis of genome based on the minimal absent word.

  2016cites this paper
• Potential drug-drug interactions in paediatric outpatient prescriptions in Nigeria and implications for the future

  2016cites this paper