iPhos-PseEvo: Identifying Human Phosphorylated Proteins by Incorporating Evolutionary Information into General PseAAC via Grey System Theory (Q38794654)

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scientific article published on 12 May 2016

Language	Label	Description	Also known as
English	iPhos-PseEvo: Identifying Human Phosphorylated Proteins by Incorporating Evolutionary Information into General PseAAC via Grey System Theory	scientific article published on 12 May 2016

Statements

scholarly article

1 reference

Europe PubMed Central

6 September 2017

iPhos-PseEvo: Identifying Human Phosphorylated Proteins by Incorporating Evolutionary Information into General PseAAC via Grey System Theory (English)

1 reference

Europe PubMed Central

6 September 2017

phosphorylation

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3

object named as

Xuan Xiao

1 reference

Europe PubMed Central

6 September 2017

5

object named as

Kuo-Chen Chou

1 reference

Europe PubMed Central

6 September 2017

author name string

Wang-Ren Qiu

1

1 reference

Europe PubMed Central

6 September 2017

Bi-Qian Sun

2

1 reference

Europe PubMed Central

6 September 2017

Dong Xu

4

1 reference

Europe PubMed Central

6 September 2017

publication date

12 May 2016

1 reference

Europe PubMed Central

6 September 2017

Molecular Informatics

1 reference

Europe PubMed Central

6 September 2017

36

1 reference

Europe PubMed Central

6 September 2017

5-6

1 reference

Europe PubMed Central

6 September 2017

Peptide biosensors for the electrochemical measurement of protein kinase activity.

1 reference

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A model of the complex between cyclin-dependent kinase 5 and the activation domain of neuronal Cdk5 activator

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The protein kinase complement of the human genome

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The role of protein phosphorylation in human health and disease. The Sir Hans Krebs Medal Lecture.

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Electrochemical detection of kinase-catalyzed phosphorylation using ferrocene-conjugated ATP.

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Detection of the site of phosphorylation in a peptide using Raman spectroscopy and partial least squares discriminant analysis

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Use of antibodies for detection of phosphorylated proteins separated by two-dimensional gel electrophoresis

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Determination of specific protein kinase activities using phosphorus-33.

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Protein phosphorylation detection using dual-mode field-effect devices and nanoplasmonic sensors.

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21 January 2018

Electrochemical investigations of Tau protein phosphorylations and interactions with Pin1.

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How phosphorylation activates the protein phosphatase-1 • inhibitor-2 complex.

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Novel sensory surface for creatine kinase electrochemical detection

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Single-molecule site-specific detection of protein phosphorylation with a nanopore

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Microarray-Based Detection of Protein Binding and Functionality by Gold Nanoparticle Probes

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Some remarks on protein attribute prediction and pseudo amino acid composition

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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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iDNA-Methyl: identifying DNA methylation sites via pseudo trinucleotide composition.

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iRNA-Methyl: Identifying N(6)-methyladenosine sites using pseudo nucleotide composition.

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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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iEnhancer-2L: a two-layer predictor for identifying enhancers and their strength by pseudo k-tuple nucleotide composition

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Identification of microRNA precursor with the degenerate K-tuple or Kmer strategy

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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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pRNAm-PC: Predicting N(6)-methyladenosine sites in RNA sequences via physical-chemical properties

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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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https://api.crossref.org/works/10.1002%2FMINF.201600010

21 January 2018

Recent progress in protein subcellular location prediction

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Neural network prediction of the HIV-1 protease cleavage sites.

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Bioinformatical analysis of G-protein-coupled receptors.

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Using stacked generalization to predict membrane protein types based on pseudo-amino acid composition

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21 January 2018

iLoc-Plant: a multi-label classifier for predicting the subcellular localization of plant proteins with both single and multiple sites.

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

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21 January 2018

iDNA-Prot: identification of DNA binding proteins using random forest with grey model

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21 January 2018

Impacts of bioinformatics to medicinal chemistry

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21 January 2018

Prediction of protein cellular attributes using pseudo-amino acid composition

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21 January 2018

Using amphiphilic pseudo amino acid composition to predict enzyme subfamily classes

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21 January 2018

PseAAC-Builder: a cross-platform stand-alone program for generating various special Chou's pseudo-amino acid compositions

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propy: a tool to generate various modes of Chou's PseAAC.

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21 January 2018

Molecular science for drug development and biomedicine

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21 January 2018

Using Chou's amphiphilic pseudo-amino acid composition and support vector machine for prediction of enzyme subfamily classes

1 reference

https://api.crossref.org/works/10.1002%2FMINF.201600010

21 January 2018

Genetic programming for creating Chou's pseudo amino acid based features for submitochondria localization

1 reference

https://api.crossref.org/works/10.1002%2FMINF.201600010

21 January 2018

Use of fuzzy clustering technique and matrices to classify amino acids and its impact to Chou's pseudo amino acid composition.

1 reference

https://api.crossref.org/works/10.1002%2FMINF.201600010

21 January 2018

Using the concept of Chou's pseudo amino acid composition for risk type prediction of human papillomaviruses

1 reference

https://api.crossref.org/works/10.1002%2FMINF.201600010

21 January 2018

A novel feature representation method based on Chou's pseudo amino acid composition for protein structural class prediction

1 reference

https://api.crossref.org/works/10.1002%2FMINF.201600010

21 January 2018

Prediction of GABAA receptor proteins using the concept of Chou's pseudo-amino acid composition and support vector machine

1 reference

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21 January 2018

Prediction of metalloproteinase family based on the concept of Chou's pseudo amino acid composition using a machine learning approach

1 reference

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21 January 2018

Identifying GPCRs and their types with Chou's pseudo amino acid composition: an approach from multi-scale energy representation and position specific scoring matrix

1 reference

https://api.crossref.org/works/10.1002%2FMINF.201600010

21 January 2018

An alignment-free method to find similarity among protein sequences via the general form of Chou's pseudo amino acid composition.

1 reference

https://api.crossref.org/works/10.1002%2FMINF.201600010

21 January 2018

Prediction of allergenic proteins by means of the concept of Chou's pseudo amino acid composition and a machine learning approach

1 reference

https://api.crossref.org/works/10.1002%2FMINF.201600010

21 January 2018

Predicting anticancer peptides with Chou's pseudo amino acid composition and investigating their mutagenicity via Ames test

1 reference

https://api.crossref.org/works/10.1002%2FMINF.201600010

21 January 2018

Discriminating protein structure classes by incorporating Pseudo Average Chemical Shift to Chou's general PseAAC and Support Vector Machine.

1 reference

https://api.crossref.org/works/10.1002%2FMINF.201600010

21 January 2018

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

1 reference

https://api.crossref.org/works/10.1002%2FMINF.201600010

21 January 2018

Prediction of β-lactamase and its class by Chou's pseudo-amino acid composition and support vector machine

1 reference

https://api.crossref.org/works/10.1002%2FMINF.201600010

21 January 2018

A new signal characterization and signal-based Chou's PseAAC representation of protein sequences.

1 reference

https://api.crossref.org/works/10.1002%2FMINF.201600010

21 January 2018

PseAAC-General: fast building various modes of general form of Chou's pseudo-amino acid composition for large-scale protein datasets

1 reference

https://api.crossref.org/works/10.1002%2FMINF.201600010

21 January 2018

Pseudo nucleotide composition or PseKNC: an effective formulation for analyzing genomic sequences

1 reference

https://api.crossref.org/works/10.1002%2FMINF.201600010

21 January 2018

PseKNC: a flexible web server for generating pseudo K-tuple nucleotide composition.

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https://api.crossref.org/works/10.1002%2FMINF.201600010

21 January 2018

PseKNC-General: a cross-platform package for generating various modes of pseudo nucleotide compositions

1 reference

https://api.crossref.org/works/10.1002%2FMINF.201600010

21 January 2018

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

1 reference

https://api.crossref.org/works/10.1002%2FMINF.201600010

21 January 2018

Pse-in-One: a web server for generating various modes of pseudo components of DNA, RNA, and protein sequences

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21 January 2018

The convergence-divergence duality in lectin domains of selectin family and its implications

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21 January 2018

MemType-2L: a web server for predicting membrane proteins and their types by incorporating evolution information through Pse-PSSM.

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Structural bioinformatics and its impact to biomedical science

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21 January 2018

Improving the accuracy of PSI-BLAST protein database searches with composition-based statistics and other refinements

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21 January 2018

iLoc-Hum: using the accumulation-label scale to predict subcellular locations of human proteins with both single and multiple sites.

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21 January 2018

Predicting secretory proteins of malaria parasite by incorporating sequence evolution information into pseudo amino acid composition via grey system model

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https://api.crossref.org/works/10.1002%2FMINF.201600010

21 January 2018

iLoc-Animal: a multi-label learning classifier for predicting subcellular localization of animal proteins.

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iGPCR-drug: a web server for predicting interaction between GPCRs and drugs in cellular networking

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21 January 2018

AFP-Pred: A random forest approach for predicting antifreeze proteins from sequence-derived properties.

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21 January 2018

RSARF: prediction of residue solvent accessibility from protein sequence using random forest method

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21 January 2018

Identification of protein-protein binding sites by incorporating the physicochemical properties and stationary wavelet transforms into pseudo amino acid composition

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21 January 2018

Identifying Important Risk Factors for Survival in Kidney Graft Failure Patients Using Random Survival Forests

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Ensemble classifier for protein fold pattern recognition.

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An antibody directed against PDGF receptor beta enhances the antitumor and the anti-angiogenic activities of an anti-VEGF receptor 2 antibody

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Signal-3L: A 3-layer approach for predicting signal peptides

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Cell-PLoc: a package of Web servers for predicting subcellular localization of proteins in various organisms

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Virus-PLoc: a fusion classifier for predicting the subcellular localization of viral proteins within host and virus-infected cells

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Euk-mPLoc: a fusion classifier for large-scale eukaryotic protein subcellular location prediction by incorporating multiple sites

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Predicting eukaryotic protein subcellular location by fusing optimized evidence-theoretic K-Nearest Neighbor classifiers

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QuatIdent: a web server for identifying protein quaternary structural attribute by fusing functional domain and sequential evolution information

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ProtIdent: a web server for identifying proteases and their types by fusing functional domain and sequential evolution information

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21 January 2018

Identification of proteases and their types

1 reference

https://api.crossref.org/works/10.1002%2FMINF.201600010

21 January 2018

pSuc-Lys: Predict lysine succinylation sites in proteins with PseAAC and ensemble random forest approach.

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https://api.crossref.org/works/10.1002%2FMINF.201600010

21 January 2018

Hum-PLoc: a novel ensemble classifier for predicting human protein subcellular localization

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21 January 2018

Prediction of linear B-cell epitopes using amino acid pair antigenicity scale.

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Prediction of protein signal sequences and their cleavage sites.

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21 January 2018

iSNO-PseAAC: predict cysteine S-nitrosylation sites in proteins by incorporating position specific amino acid propensity into pseudo amino acid composition

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iRSpot-PseDNC: identify recombination spots with pseudo dinucleotide composition

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

1 reference

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Euk-PLoc: an ensemble classifier for large-scale eukaryotic protein subcellular location prediction

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Chou's pseudo amino acid composition improves sequence-based antifreeze protein prediction

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DSPMP: Discriminating secretory proteins of malaria parasite by hybridizing different descriptors of Chou's pseudo amino acid patterns

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Virus-mPLoc: a fusion classifier for viral protein subcellular location prediction by incorporating multiple sites

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ATM is activated by mitotic stress and suppresses centrosome amplification in primary but not in tumor cells

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Identifiers

10.1002/MINF.201600010

1 reference

Europe PubMed Central

6 September 2017

1 reference

Europe PubMed Central

6 September 2017

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