Erratum to: Classification and Clustering on Microarray Data for Gene Functional Prediction Using R.

Classification and Clustering on Microarray Data for Gene Functional Prediction Using R.

Improving PLS-RFE based gene selection for microarray data classification.

Gene expression microarray classification using PCA-BEL.

Parallel classification and feature selection in microarray data using SPRINT.

Clustering by fast search and merge of local density peaks for gene expression microarray data.

Bioc package to generate and analyse gene networks derived from functional enrichment and clustering.

Gene masking - a technique to improve accuracy for cancer classification with high dimensionality in microarray data.

Classification of Microarray Data Using Kernel Fuzzy Inference System.

Impact of missing data imputation methods on gene expression clustering and classification.

Hyperspectral image classification using functional data analysis.

Novel R pipeline for analyzing Biolog Phenotypic MicroArray data.

Hierarchical gene selection and genetic fuzzy system for cancer microarray data classification.

CAFE: an R package for the detection of gross chromosomal abnormalities from gene expression microarray data.

mRMR-ABC: A Hybrid Gene Selection Algorithm for Cancer Classification Using Microarray Gene Expression Profiling.

Multicategory classification of 11 neuromuscular diseases based on microarray data using support vector machine.

Classification of serous ovarian tumors based on microarray data using multicategory support vector machines.

Genetic programming based ensemble system for microarray data classification.

A novel strategy for gene selection of microarray data based on gene-to-class sensitivity information.

Cloud-scale genomic signals processing classification analysis for gene expression microarray data.

Assisted clustering of gene expression data using ANCut.

Erratum: New GOLD classification: longitudinal data on group assignment.

CORM: An R Package Implementing the Clustering of Regression Models Method for Gene Clustering.

Fragment peptide library for classification and functional prediction of proteins.

spliceR: an R package for classification of alternative splicing and prediction of coding potential from RNA-seq data.

Suggest Documents

Classification and Clustering on Microarray Data for Gene Functional Prediction Using R.

Improving PLS-RFE based gene selection for microarray data classification.

Gene expression microarray classification using PCA-BEL.

Parallel classification and feature selection in microarray data using SPRINT.

Clustering by fast search and merge of local density peaks for gene expression microarray data.

Bioc package to generate and analyse gene networks derived from functional enrichment and clustering.

Gene masking - a technique to improve accuracy for cancer classification with high dimensionality in microarray data.

Classification of Microarray Data Using Kernel Fuzzy Inference System.

Impact of missing data imputation methods on gene expression clustering and classification.

Hyperspectral image classification using functional data analysis.

Novel R pipeline for analyzing Biolog Phenotypic MicroArray data.

Hierarchical gene selection and genetic fuzzy system for cancer microarray data classification.

CAFE: an R package for the detection of gross chromosomal abnormalities from gene expression microarray data.

mRMR-ABC: A Hybrid Gene Selection Algorithm for Cancer Classification Using Microarray Gene Expression Profiling.

Multicategory classification of 11 neuromuscular diseases based on microarray data using support vector machine.

Classification of serous ovarian tumors based on microarray data using multicategory support vector machines.

Genetic programming based ensemble system for microarray data classification.

A novel strategy for gene selection of microarray data based on gene-to-class sensitivity information.

Cloud-scale genomic signals processing classification analysis for gene expression microarray data.

Assisted clustering of gene expression data using ANCut.

Erratum: New GOLD classification: longitudinal data on group assignment.

CORM: An R Package Implementing the Clustering of Regression Models Method for Gene Clustering.

Fragment peptide library for classification and functional prediction of proteins.

spliceR: an R package for classification of alternative splicing and prediction of coding potential from RNA-seq data.

Erratum to: Classification and Clustering on Microarray Data for Gene Functional Prediction Using R.

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