Functional analysis of cancer gene subtype from co-clustering and classification

Functional analysis of cancer gene subtype from co-clustering and classification

Cancer is a heterogeneity genetic disease with huge phenotypic alterations among dissimilar cancers types or even between same cancer types. Recent expansions of genome-wide profiling technologies offer a chance to explore molecular changes variations throughout advancement of cancer. Therefore, var...

Full description

Bibliographic Details
Main Authors:	Machap, L., Abdullah, A., Shah, Z. A.
Format:	Article
Language:	English
Published:	Institute of Advanced Engineering and Science 2020
Subjects:	QA75 Electronic computers. Computer science
Online Access:	http://eprints.utm.my/93043/1/LogenthiranMachap2020_FunctionalAnalysisofCancerGeneSubtype.pdf

Similar Items

Co-clustering algorithm for the identification of cancer subtypes from gene expression data
by: Machap Z.A.b, L., et al.
Published: (2019)

Identifying cancer gene subtypes from gene expression by co-clustering algorithm and support vector machine
by: Machap, Logenthiran
Published: (2021)

Survival analysis for the identified cancer gene subtype from the co-clustering algorithm
by: Logenthiran, Machap, et al.
Published: (2022)

A review of computational methods for clustering genes with similar biological functions
by: Hui, Wen Nies, et al.
Published: (2019)

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

Biological-based semi-supervised clustering algorithm to improve gene function prediction
by: Kasim, Shahreen, et al.
Published: (2011)

A multi-objective approach to selects genes for cancer classification
by: Mohamad, Mohd. Saberi, et al.
Published: (2008)

Three-stage method for selecting informative genes for cancer classification
by: Mohamad, Mohd Saberi, et al.
Published: (2009)

Clustering functional modules from protein interaction network
by: Abdullah, Afnizanfaizal, et al.
Published: (2008)

An improved parallelized mRMR for gene subset selection in cancer classification
by: Kusairi, R. M., et al.
Published: (2017)

An interative GA-Based approach : gene selection and classification of lung cancer data
by: Mohamad, Mohd. Saberi, et al.
Published: (2008)

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

A review on recent progress in machine learning and deep learning methods for cancer classification on gene expression data
by: Mazlan, A. U., et al.
Published: (2021)

Gene selection and classification in autism gene expression data
by: Al-Jaf, Shilan Sameen Hameed
Published: (2017)

Selecting informative genes from microarray data by using hybrid methods for cancer classification
by: Mohamad, Mohd Saberi, et al.
Published: (2009)

A soft hierarchical algorithm for the clustering of multiple bioactive chemical compounds
by: Salim, Naomie, et al.
Published: (2007)

Fuzzy c-means clustering by incorporating biological knowledge and multi-stage filtering to improve gene function prediction
by: Kasim, Shahreen
Published: (2011)

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

An Enhanced Topologically Significant Directed Random Walk in Cancer Classification using Gene Expression Datasets
by: Choon, Sen Seah, et al.
Published: (2017)

An improved binary particle swarm optimization algorithm for genes selection and classification of colon cancer data
by: Mohamad, Mohd. Saberi, et al.
Published: (2008)

Significant directed walk framework to increase the accuracy of cancer classification using gene expression data
by: Seah, C. S., et al.
Published: (2021)

Validation of hierarchical gene clusters using repeated measurements
by: Mohamad, Mohd. Saberi, et al.
Published: (2013)

A Review of Computational Approaches to Predict Gene Functions
by: Loh, Swee Kuan, et al.
Published: (2018)

Semi-supervised SVM-based feature selection for cancer classification using microarray gene expression data
by: Ang, Jun Chin, et al.
Published: (2015)

The performance review of mrmr for gene selection and selection and classification of dna microarrays
by: Yusup, N., et al.
Published: (2019)

Hybrid of hierarchical and partitional clustering algorithm for gene expression data
by: Raja Kumaran, Shamini, et al.
Published: (2020)

Automatic clustering and classification of coffee leaf diseases based on an extended Kernel Density Estimation approach
by: Hasan, Reem Ibrahim, et al.
Published: (2023)

Random forest for gene selection and microarray data classification
by: Moorthy, Kohbalan, et al.
Published: (2012)

Clustering High Dimensional Data Using Subspace And Projected Clustering Algorithms
by: Sembiring, Rahmat Widia, et al.
Published: (2010)

A Comparative Agglomerative Hierarchical Clustering Method to Cluster Implemented Course
by: Sembiring, Rahmat Widia, et al.
Published: (2010)

Student profiling on university co-curricular activities using cluster analysis
by: Rajenthran, Hemabegai, et al.
Published: (2017)

Fuzzy clustering algorithms and their applications to chemical datasets
by: Shah, Jehan Zeb, et al.
Published: (2005)

Hybrid approach of EEG stress level classification using K-means clustering and support vector machine
by: Tee, Yi Wen, et al.
Published: (2022)

Filter-Based Gene Selection Method for Tissues Classification on Large Scale Gene Expression Data
by: Kabir Ahmad, Farzana, et al.
Published: (2018)

Comparative analysis of deep learning algorithm for cancer classification using multi-omics feature selection
by: Azmi, Nur Sabrina, et al.
Published: (2022)

A new binary particle swarm optimizer to select a smaller subset of genes for leukaemia cancer classification
by: Mohamad, Mohd. Saberi, et al.
Published: (2008)

Hybrid radial basis function network for classification problems
by: Shamsuddin, Siti Mariyam, et al.
Published: (2009)

An iterative GASVM-based method: gene selection and classification of microarray data
by: Mohamad, Mohd. Saberi, et al.
Published: (2009)

ABC: android botnet classification using feature selection and classification algorithms
by: Abdullah, Zubaile, et al.
Published: (2017)

Gene subset selection for lung cancer classification using a multi-objective strategy
by: Mohamad, Mohd. Saberi, et al.
Published: (2008)