Application of neural network to gene expression data for cancer classification

IJCNN'01. International Joint Conference on Neural Networks. Proceedings (Cat. No.01CH37222) ◽

10.1109/ijcnn.2001.939087 ◽

2002 ◽

Author(s):

A. Toure ◽

M. Basu

Keyword(s):

Neural Network ◽

Gene Expression ◽

Gene Expression Data ◽

Cancer Classification ◽

Expression Data

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Lightweight Convolutional Neural Network for Breast Cancer Classification Using RNA-Seq Gene Expression Data

IEEE Access ◽

10.1109/access.2019.2960722 ◽

2019 ◽

Vol 7 ◽

pp. 185338-185348 ◽

Author(s):

Murtada K. Elbashir ◽

Mohamed Ezz ◽

Mohanad Mohammed ◽

Said S. Saloum

Keyword(s):

Breast Cancer ◽

Neural Network ◽

Gene Expression ◽

Convolutional Neural Network ◽

Gene Expression Data ◽

Cancer Classification ◽

Expression Data ◽

Rna Seq ◽

Breast Cancer Classification

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Abstract 5104: Pan-cancer classification on gene expression data by neural network

10.1158/1538-7445.am2019-5104 ◽

2019 ◽

Author(s):

Kijin Yu ◽

Bong-Hyun Kim ◽

Peter Chang Whan Lee

Keyword(s):

Neural Network ◽

Gene Expression ◽

Gene Expression Data ◽

Cancer Classification ◽

Expression Data ◽

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Abstract 5104: Pan-cancer classification on gene expression data by neural network

10.1158/1538-7445.sabcs18-5104 ◽

2019 ◽

Author(s):

Kijin Yu ◽

Bong-Hyun Kim ◽

Peter Chang Whan Lee

Keyword(s):

Neural Network ◽

Gene Expression ◽

Gene Expression Data ◽

Cancer Classification ◽

Expression Data ◽

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Molecular cancer classification method on microarrays gene expression data using hybrid deep neural network and grey wolf algorithm

Journal of Ambient Intelligence and Humanized Computing ◽

10.1007/s12652-020-02478-x ◽

2020 ◽

Author(s):

AliReza Hajieskandar ◽

Javad Mohammadzadeh ◽

Majid Khalilian ◽

Ali Najafi

Keyword(s):

Neural Network ◽

Gene Expression ◽

Gene Expression Data ◽

Deep Neural Network ◽

Cancer Classification ◽

Classification Method ◽

Expression Data ◽

Grey Wolf ◽

Grey Wolf Algorithm

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Jaya Ant lion optimization-driven Deep recurrent neural network for cancer classification using gene expression data

Medical & Biological Engineering & Computing ◽

10.1007/s11517-021-02350-w ◽

2021 ◽

Author(s):

Ramachandro Majji ◽

G. Nalinipriya ◽

Ch. Vidyadhari ◽

R. Cristin

Keyword(s):

Neural Network ◽

Gene Expression ◽

Gene Expression Data ◽

Recurrent Neural Network ◽

Cancer Classification ◽

Expression Data ◽

Ant Lion Optimization ◽

Deep Recurrent Neural Network ◽

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Cancer Classification from Gene Expression data using Fuzzy-Rough techniques An Empirical Study

International Journal of Computer Sciences and Engineering ◽

10.26438/ijcse/v6i6.415420 ◽

2018 ◽

Vol 6 (6) ◽

pp. 415-420

Author(s):

Ansuman Kumar ◽

Anindya Halder

Keyword(s):

Gene Expression ◽

Empirical Study ◽

Gene Expression Data ◽

Cancer Classification ◽

Expression Data

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Cascade of genetic algorithm and decision tree for cancer classification on gene expression data

Expert Systems ◽

10.1111/j.1468-0394.2010.00522.x ◽

2010 ◽

Vol 27 (3) ◽

pp. 201-218 ◽

Author(s):

Jinn-Yi Yeh ◽

Tai-Hsi Wu

Keyword(s):

Gene Expression ◽

Genetic Algorithm ◽

Decision Tree ◽

Gene Expression Data ◽

Cancer Classification ◽

Expression Data

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Effective Cancer Classification based on Gene Expression Data using Multidimensional Mutual Information and ELM

2018 IEEE 7th Data Driven Control and Learning Systems Conference (DDCLS) ◽

10.1109/ddcls.2018.8515927 ◽

2018 ◽

Author(s):

Qun-Xiong Zhu ◽

Yuan Fan ◽

Yan-Lin He ◽

Yuan Xu

Keyword(s):

Gene Expression ◽

Mutual Information ◽

Gene Expression Data ◽

Cancer Classification ◽

Expression Data

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Cancer classification by sparse representation using microarray gene expression data

2008 IEEE International Conference on Bioinformatics and Biomeidcine Workshops ◽

10.1109/bibmw.2008.4686232 ◽

2008 ◽

Author(s):

Xiyi Hang

Keyword(s):

Gene Expression ◽

Sparse Representation ◽

Gene Expression Data ◽

Microarray Gene Expression Data ◽

Cancer Classification ◽

Expression Data ◽

Microarray Gene Expression ◽

Microarray Gene

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Convolutional Neural Network Approach to Predict Tumor Samples Using Gene Expression Data

Journal of Intelligent Systems: Theory and Applications ◽

10.38016/jista.946954 ◽

2021 ◽

pp. 136-141

Author(s):

Büşra Nur DARENDELİ ◽

Alper YILMAZ

Keyword(s):

Neural Network ◽

Gene Expression ◽

Convolutional Neural Network ◽

Gene Expression Data ◽

Expression Data ◽

Network Approach ◽

Neural Network Approach

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