Integrative gene selection for classification of microarray data

QR Code

Integrative gene selection for classification of microarray data

Microarray data classification is one of the major interests in health informatics that aims at discovering hidden patterns in gene expression profiles. The main challenge in building this classification system is the curse of dimensionality problem. Thus, there is a considerable amount of studies o...

Full description

Bibliographic Details
Main Authors:	Ong, Huey Fang, Mustapha, Norwati, Sulaiman, Md. Nasir
Format:	Article
Language:	English
Published:	Canadian Center of Science and Education 2011
Online Access:	http://psasir.upm.edu.my/id/eprint/22460/ http://psasir.upm.edu.my/id/eprint/22460/1/22460.pdf

Similar Items

An integrative gene selection with association analysis for microarray data classification
by: Ong, Huey Fang, et al.
Published: (2014)

Integrated framework with association analysis for gene selection in microarray data classification
by: Ong, Huey Fang
Published: (2011)

Associative classification framework for cancer microarray data
by: Fang, Ong Huey, et al.
Published: (2017)

Associative classification framework for cancer microarray data
by: Fang, Ong Huey, et al.
Published: (2017)

A Study On Gene Selection And Classification Algorithms For Classification Of Microarray Gene Expression Data
by: Yeo, Lee Chin, et al.
Published: (2005)

An integrative cancer classification based on gene expression data
by: Ong, H. F., et al.
Published: (2014)

Informative top-k class associative rule for cancer biomarker discovery on microarray data
by: Ong, Huey Fang, et al.
Published: (2020)

Informative top-k class associative rule for cancer biomarker discovery on microarray data
by: Ong, Huey Fang, et al.
Published: (2020)

The importance of data classification using machine learning methods in microarray data
by: Jaber, Aws Naser, et al.
Published: (2021)

Reliable multiclass cancer classification of microarray gene expression profiles using an improved wavelet neural network
by: Zainuddin, Zarita, et al.
Published: (2011)

Missing-values imputation algorithms for microarray gene expression data
by: Moorthy, Kohbalan, et al.
Published: (2019)

An enhanced feature selection and cancer classiﬁcation for microarray data using relaxed Lasso and support vector machine
by: Aina Umairah, Mazlan, et al.
Published: (2021)

Integration of rank-partition and sequential wrapper techniques for feature selection of breast cancer microarray data
by: Abdulwahhab, Ahmed Abbas
Published: (2015)

Classification Of Microarray Datasets Using Random Forest
by: Ng, Ee Ling
Published: (2009)

Selecting a smaller subset of informative genes from microarray data via a three-stage method
by: Mohamad, Mohd. Saberi, et al.
Published: (2008)

Effective gene selection techniques for classification of gene expression data
by: Yeo, Lee Chin
Published: (2005)

A model for gene selection and classification of gene expression data
by: Mohamad, Mohd Saberi, et al.
Published: (2007)

Bayesian random forests for high-dimensional classification and regression with complete and incomplete microarray data
by: Oyebayo, Olaniran Ridwan
Published: (2018)

Cancer classification from DNA microarray data using mRMR and artificial neural network
by: Akhand, M. A. H, et al.
Published: (2016)

Grayscale Morphological Analysis Of DNA Microarray For Spot Classification
by: Latha, Behara
Published: (2004)

A two-stage method for identifying a smaller subset of genes in microarray data
by: Mohamad, Mohd. Saberi, et al.
Published: (2008)

Research trends in microarray data analysis: modelling gene regulatory network by integrating transcription factors data / Farzana Kabir Ahmad and Siti Sakira Kamaruddin
by: Kabir Ahmad, Farzana, et al.
Published: (2015)

Development of IgE microarray assays for classification of allergic individuals
by: Hamed, Aljali
Published: (2016)

Cancer recognition from DNA microarray gene expression data using averaged one-dependence estimators
by: Shoon , Lei Win, et al.
Published: (2014)

Evaluation of Differential Normalization and Analysis Procedures for Illumina Gene Expression Microarray Data Involving Small Changes
by: Johnstone, D., et al.
Published: (2013)

Detection of colon cancer based on microarray dataset using machine learning as a feature selection and classification techniques
by: A. S. M, Shafi, et al.
Published: (2020)

A new classification model for a class imbalanced data set using genetic programming and support vector machines: case study for wilt disease classification
by: Mohd Pozi, Muhammad Syafiq, et al.
Published: (2015)

Utilization of Microarray Technology for Identification of Disease Response Genes in Banana (Musa Spp.)
by: Lim, Kean Jin
Published: (2006)

Identification of Differentially Expressed Genes in Human Bladder Cancer using Oligonucleotide Microarray
by: Nik Hassan, Nik Norliza
Published: (2006)

Analysis of ripening-related gene expression in papaya using an Arabidopsis-based microarray
by: Fabi, João Paulo, et al.
Published: (2012)

Performance comparison of image normalisation method for DNA microarray data
by: Baans, Omar Salem Nasser, et al.
Published: (2017)

Chondrocyte channel transcriptomics: do microarray data fit with expression and functional data?
by: Lewis, Rebecca, et al.
Published: (2013)

Selecting informative genes from leukemia gene expression data using a hybrid approach for cancer classification
by: Mohamad, Mohd. Saberi, et al.
Published: (2007)

Improving accuracy of intention-based response classification using decision tree.
by: Ali, S. A., et al.
Published: (2009)

A framework for intelligent multi agent system based neural network classification model
by: Asadi, Roya, et al.
Published: (2009)

DNA microarray gene expression analysis for diagnosis of oral dysplasia and squamous-cell carcinoma
by: Zarzar, Mouayad, et al.
Published: (2015)

Surface analysis of polymer microarrays
by: Taylor, Michael
Published: (2009)

A new classification model for online predicting users' future movements
by: Jalali, Mehrdad, et al.
Published: (2008)

Gene Selection For Cancer Classification Based On Xgboost Classifier
by: Teo, Voon Chuan
Published: (2022)

Filter-Wrapper Methods For Gene Selection In Cancer Classification
by: Alomari, Osama Ahmad Suleiman
Published: (2018)