Predicting Protein Subcellular Localization: A Multiobjective PSO-based Feature Subset Selection from Amino Acid Sequence of Protein

2014 International Conference on Information Technology ◽

10.1109/icit.2014.75 ◽

2014 ◽

Author(s):

Monalisa Mandal ◽

Anirban Mukhopadhyay

Keyword(s):

Amino Acid ◽

Amino Acid Sequence ◽

Subcellular Localization ◽

Subset Selection ◽

Feature Subset Selection ◽

Feature Subset ◽

Protein Subcellular Localization

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Feature Subset Selection for Protein Subcellular Localization Prediction

Computational Intelligence and Bioinformatics - Lecture Notes in Computer Science ◽

10.1007/11816102_47 ◽

2006 ◽

pp. 433-443 ◽

Cited By ~ 1

Author(s):

Qing-Bin Gao ◽

Zheng-Zhi Wang

Keyword(s):

Subcellular Localization ◽

Subset Selection ◽

Feature Subset Selection ◽

Feature Subset ◽

Protein Subcellular Localization ◽

Subcellular Localization Prediction ◽

Selection For ◽

Protein Subcellular Localization Prediction ◽

Localization Prediction

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Prediction of protein subcellular localization by incorporating multiobjective PSO-based feature subset selection into the general form of Chou’s PseAAC

Medical & Biological Engineering & Computing ◽

10.1007/s11517-014-1238-7 ◽

2015 ◽

Vol 53 (4) ◽

pp. 331-344 ◽

Cited By ~ 45

Author(s):

Monalisa Mandal ◽

Anirban Mukhopadhyay ◽

Ujjwal Maulik

Keyword(s):

Subcellular Localization ◽

Subset Selection ◽

Feature Subset Selection ◽

Feature Subset ◽

Protein Subcellular Localization

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Human protein subcellular localization prediction based on error correcting output coding strategy while combining immunohistochemistry image and amino acid sequence

10.1109/aemcse51986.2021.00178 ◽

2021 ◽

Author(s):

Yanbing Wang ◽

Fan Yang ◽

Quanchao Ma ◽

Ziqian Wang ◽

Simeng Wang ◽

...

Keyword(s):

Amino Acid ◽

Amino Acid Sequence ◽

Subcellular Localization ◽

Human Protein ◽

Protein Subcellular Localization ◽

Subcellular Localization Prediction ◽

Coding Strategy ◽

Protein Subcellular Localization Prediction ◽

Localization Prediction ◽

Output Coding

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Empirical evaluation of feature subset selection based on a real-world data set

Engineering Applications of Artificial Intelligence ◽

10.1016/j.engappai.2004.03.005 ◽

2004 ◽

Vol 17 (3) ◽

pp. 285-288 ◽

Cited By ~ 5

Author(s):

Petra Perner ◽

Chid Apte

Keyword(s):

Real World ◽

Empirical Evaluation ◽

Subset Selection ◽

Feature Subset Selection ◽

Feature Subset ◽

Real World Data ◽

Data Set ◽

World Data

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Threshold accepting trained principal component neural network and feature subset selection: Application to bankruptcy prediction in banks

Applied Soft Computing ◽

10.1016/j.asoc.2007.12.003 ◽

2008 ◽

Vol 8 (4) ◽

pp. 1539-1548 ◽

Cited By ~ 67

Author(s):

V. Ravi ◽

C. Pramodh

Keyword(s):

Neural Network ◽

Subset Selection ◽

Principal Component ◽

Bankruptcy Prediction ◽

Feature Subset Selection ◽

Feature Subset ◽

Threshold Accepting

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Interaction between feature subset selection techniques and machine learning classifiers for detecting unsolicited emails

ACM SIGAPP Applied Computing Review ◽

10.1145/2600617.2600622 ◽

2014 ◽

Vol 14 (1) ◽

pp. 53-61 ◽

Cited By ~ 15

Author(s):

Shrawan Kumar Trivedi ◽

Shubhamoy Dey

Keyword(s):

Machine Learning ◽

Subset Selection ◽

Feature Subset Selection ◽

Feature Subset ◽

Machine Learning Classifiers ◽

Learning Classifiers

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An intelligent hybrid feature subset selection and production pattern recognition method for modeling steam cracking process

Journal of Analytical and Applied Pyrolysis ◽

10.1016/j.jaap.2021.105352 ◽

2021 ◽

pp. 105352

Author(s):

Qing Li ◽

Mengxuan Zhang ◽

Xiaogang Shi ◽

Xingying Lan ◽

Xuqiang Guo ◽

...

Keyword(s):

Pattern Recognition ◽

Subset Selection ◽

Feature Subset Selection ◽

Feature Subset ◽

Pattern Recognition Method ◽

Recognition Method ◽

Steam Cracking ◽

Production Pattern ◽

Cracking Process

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A New Approach for Feature Subset Selection using Quantum Inspired Owl Search Algorithm

2020 10th International Conference on Information Science and Technology (ICIST) ◽

10.1109/icist49303.2020.9202140 ◽

2020 ◽

Author(s):

Ashis Kumar Mandal ◽

Rikta Sen ◽

Saptarsi Goswami ◽

Amlan Chakrabarti ◽

Basabi Chakraborty

Keyword(s):

Search Algorithm ◽

Subset Selection ◽

Feature Subset Selection ◽

Feature Subset ◽

New Approach

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Amino Acid Composition Distribution: a Novel Sequence Representation for Prediction of Protein Subcellular Localization

2007 1st International Conference on Bioinformatics and Biomedical Engineering ◽

10.1109/icbbe.2007.33 ◽

2007 ◽

Cited By ~ 1

Author(s):

Jianyu Shi ◽

Shao-Wu Zhang ◽

Quan Pan ◽

Guo-Ping Zhou

Keyword(s):

Amino Acid ◽

Subcellular Localization ◽

Amino Acid Composition ◽

Acid Composition ◽

Protein Subcellular Localization ◽

Composition Distribution ◽

Sequence Representation

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Cascading GA & CFS for Feature Subset selection in Medical Data Mining

2009 IEEE International Advance Computing Conference ◽

10.1109/iadcc.2009.4809226 ◽

2009 ◽

Cited By ~ 11

Author(s):

Asha Gowda Karegowda ◽

M.A. Jayaram

Keyword(s):

Data Mining ◽

Subset Selection ◽

Medical Data ◽

Feature Subset Selection ◽

Feature Subset ◽

Medical Data Mining

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