Prediction of protein subcellular localization by incorporating multiobjective PSO-based feature subset selection into the general form of Chou's PseAAC. (Q41616725)

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English	Prediction of protein subcellular localization by incorporating multiobjective PSO-based feature subset selection into the general form of Chou's PseAAC.	scientific article

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scholarly article

1 reference

Europe PubMed Central

5 October 2017

Prediction of protein subcellular localization by incorporating multiobjective PSO-based feature subset selection into the general form of Chou's PseAAC. (English)

1 reference

Europe PubMed Central

5 October 2017

3

object named as

Ujjwal Maulik

1 reference

Europe PubMed Central

5 October 2017

Anirban Mukhopadhyay

2

object named as

Anirban Mukhopadhyay

1 reference

Europe PubMed Central

5 October 2017

author name string

Monalisa Mandal

1

1 reference

Europe PubMed Central

5 October 2017

publication date

7 January 2015

1 reference

Europe PubMed Central

5 October 2017

Medical & Biological Engineering & Computing

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Europe PubMed Central

5 October 2017

53

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Europe PubMed Central

5 October 2017

4

1 reference

Europe PubMed Central

5 October 2017

331-344

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Europe PubMed Central

5 October 2017

Multi-objective optimal chemotherapy control model for cancer treatment.

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Predicting subcellular localization of proteins in a hybridization space

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

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Prediction of protein subcellular localization by weighted gene ontology terms

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Some remarks on protein attribute prediction and pseudo amino acid composition

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

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Prediction of protein cellular attributes using pseudo-amino acid composition

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Some remarks on predicting multi-label attributes in molecular biosystems

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Using Functional Domain Composition and Support Vector Machines for Prediction of Protein Subcellular Location

1 reference

https://api.crossref.org/works/10.1007%2FS11517-014-1238-7

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Protein subcellular location prediction

1 reference

https://api.crossref.org/works/10.1007%2FS11517-014-1238-7

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

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https://api.crossref.org/works/10.1007%2FS11517-014-1238-7

21 January 2018

Recent progress in protein subcellular location prediction

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21 January 2018

A fast and elitist multiobjective genetic algorithm: NSGA-II

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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/10.1007%2FS11517-014-1238-7

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

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https://api.crossref.org/works/10.1007%2FS11517-014-1238-7

21 January 2018

Support vector machine-based method for subcellular localization of human proteins using amino acid compositions, their order, and similarity search

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An effective non-parametric method for globally clustering genes from expression profiles.

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

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A knowledge base for predicting protein localization sites in eukaryotic cells

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Prediction of protein subcellular locations by support vector machines using compositions of amino acids and amino acid pairs.

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Ataxin active site determination using spectral distribution of electron ion interaction potentials of amino acids.

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Using neural networks for prediction of the subcellular location of proteins

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Hum-mPLoc: an ensemble classifier for large-scale human protein subcellular location prediction by incorporating samples with multiple sites.

1 reference

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21 January 2018

iLoc-Virus: a multi-label learning classifier for identifying the subcellular localization of virus proteins with both single and multiple sites

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Predicting subcellular localization of proteins for Gram-negative bacteria by support vector machines based on n-peptide compositions

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21 January 2018

Predicting subcellular location of apoptosis proteins with pseudo amino acid composition: approach from amino acid substitution matrix and auto covariance transformation.

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Subcellular location prediction of apoptosis proteins

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Improved prediction of subcellular location for apoptosis proteins by the dual-layer support vector machine

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Protein subcellular localization prediction based on compartment-specific features and structure conservation

1 reference

https://pubmed.ncbi.nlm.nih.gov/25564182

12 December 2020

based on heuristic

inferred from PubMed ID database lookup

mGOASVM: Multi-label protein subcellular localization based on gene ontology and support vector machines

1 reference

https://pubmed.ncbi.nlm.nih.gov/25564182

12 December 2020

based on heuristic

inferred from PubMed ID database lookup

Predicting protein subcellular locations using hierarchical ensemble of Bayesian classifiers based on Markov chains

1 reference

https://pubmed.ncbi.nlm.nih.gov/25564182

12 December 2020

based on heuristic

inferred from PubMed ID database lookup

iLoc-Euk: a multi-label classifier for predicting the subcellular localization of singleplex and multiplex eukaryotic proteins

1 reference

https://pubmed.ncbi.nlm.nih.gov/25564182

12 December 2020

based on heuristic

inferred from PubMed ID database lookup

Measuring stability of feature selection in biomedical datasets.

1 reference

https://pubmed.ncbi.nlm.nih.gov/25564182

12 December 2020

based on heuristic

inferred from PubMed ID database lookup

Identifiers

10.1007/S11517-014-1238-7

1 reference

Europe PubMed Central

5 October 2017

DBLP publication ID

journals/mbec/Mandal0M15

1 reference

DBLP Dataset 2021-01-02

28 January 2021

1 reference

Europe PubMed Central

5 October 2017

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