Random forest for gene selection and microarray data classification

A random forest method has been selected to perform both gene selection and classification of the microarray data. In this embedded method, the selection of smallest possible sets of genes with lowest error rates is the key factor in achieving highest classification accuracy. Hence, improved gene selection method using random forest has been proposed to obtain the smallest subset of genes as well as biggest subset of genes prior to classification. The option for biggest subset selection is done to assist researchers who intend to use the informative genes for further research. Enhanced random forest gene selection has performed better in terms of selecting the smallest subset as well as biggest subset of informative genes with lowest out of bag error rates through gene selection. Furthermore, the classification performed on the selected subset of genes using random forest has lead to lower prediction error rates compared to existing method and other similar available methods.

• Publication year

  2011

• Venue

  Knowledge Technology Week

• Publication date

  2011-07-18

• Fields of study

  Biology, Medicine, Computer Science

• Identifiers
  DOI 10.6026/97320630007142PMID 22125385PMCID 3218317
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar, PubMed

• No claims are published for this paper.

• No concepts are published for this paper.

• Computational Statistics & Data Analysis

  2009cited by this paper
• EGFR Activation and Ultraviolet Light-Induced Skin Carcinogenesis

  2006cited by this paper
• BMC Bioinformatics

  2006cited by this paper
• A Study on Gene Selection and Classification Algorithms for Classification of Microarray Gene Expression Data

  2005cited by this paper
• Application of Breiman's Random Forest to Modeling Structure-Activity Relationships of Pharmaceutical Molecules

  2004cited by this paper
• A comparative study of feature selection and multiclass classification methods for tissue classification based on gene expression

  2004cited by this paper
• An extensive comparison of recent classification tools applied to microarray data

  2004influential reference
• A molecular signature of metastasis in primary solid tumors

  2003cited by this paper
• Gene expression correlates of clinical prostate cancer behavior.

  2002cited by this paper
• Gene expression profiling predicts clinical outcome of breast cancer

  2002cited by this paper
• Prediction of central nervous system embryonal tumour outcome based on gene expression

  2002cited by this paper
• Classification and diagnostic prediction of cancers using gene expression profiling and artificial neural networks

  2001cited by this paper
• Distinct types of diffuse large B-cell lymphoma identified by gene expression profiling

  2000cited by this paper
• Therapeutic activity of agonistic monoclonal antibodies against CD40 in a chronic autoimmune inflammatory process

  2000cited by this paper
• Systematic variation in gene expression patterns in human cancer cell lines

  2000cited by this paper
• Broad patterns of gene expression revealed by clustering analysis of tumor and normal colon tissues probed by oligonucleotide arrays.

  1999cited by this paper
• Molecular classification of cancer: class discovery and class prediction by gene expression monitoring.

  1999cited by this paper
• Bagging Predictors

  1996cited by this paper
• A Study of Cross-Validation and Bootstrap for Accuracy Estimation and Model Selection

  1995cited by this paper
• THE CANCER CELL

  1924cited by this paper

• Assessing the impact of waterfront trail aesthetics on psychological restoration in urban environments: a deep learning and random forest approach

  2026cites this paper
• A Novel Palmitoylation-Related Molecular Signature for Predicting and Therapeutically Targeting Alzheimer’s Disease

  2025cites this paper
• Fungal dynamics and lignocellulose depolymerization in Pinus koraiensis: impact of longhorn beetle infestation

  2025cites this paper
• Integrative bioinformatics approaches reveal key hub genes in cyanobacteria: insights from Synechocystis sp. PCC 6803 and Geminocystis sp. NIES-3708 under abiotic stress conditions

  2025cites this paper
• Sensor-Based Rock Hardness Characterization in a Gold Mine Using Hyperspectral Imaging and Portable X-Ray Fluorescence Technologies

  2025cites this paper
• Deciphering N7-methylguanosine-driven immune dysregulation in unexplained recurrent spontaneous abortion based on transcriptome data and experimental validation

  2025cites this paper
• Artificial intelligence-driven personalized clinical decision-making and drug development in breast cancer

  2025cites this paper
• Dysregulation of ferroptosis-related genes in granulosa cells associates with impaired oocyte quality in polycystic ovary syndrome

  2024cites this paper
• Feature Selection of Gene Expression Data Using a Modified Artificial Fish Swarm Algorithm With Population Variation

  2024cites this paper
• A novel machine learning prediction model for metastasis in breast cancer

  2024cites this paper
• Exploring the potential link between MitoEVs and the immune microenvironment of periodontitis based on machine learning and bioinformatics methods

  2024cites this paper
• Research on SAR image quality evaluation method based on improved harris hawk optimization algorithm and XGBoost

  2024cites this paper
• Leveraging Explainability with K-Fold Feature Selection

  2023cites this paper
• Identification MNS1, FRZB, OGN, LUM, SERP1NA3 and FCN3 as the potential immune-related key genes involved in ischaemic cardiomyopathy by random forest and nomogram

  2023cites this paper
• Electrophilicity-based charge transfer for developing aquatic-quantitative structure toxicity relationships (Aqua-QSTR)

  2023cites this paper
• A survey on computational learning methods for analysis of gene expression data in genomics

  2022cites this paper
• A new digital soil mapping method with temporal-spatial-spectral information derived from multi-source satellite images

  2022cites this paper
• A Prediction Model for Lung Cancer Levels Based on Machine Learning

  2022cites this paper
• CMAR_A_346871 909..923

  2022cites this paper
• Development and Validation of a New Multiparametric Random Survival Forest Predictive Model for Breast Cancer Recurrence with a Potential Benefit to Individual Outcomes

  2022cites this paper
• A comprehensive survey on computational learning methods for analysis of gene expression data

  2022cites this paper
• Environmental hazard assessment and monitoring for air pollution using machine learning and remote sensing

  2022cites this paper
• Feature Extraction and Classification of Colon Cancer Using a Hybrid Approach of Supervised and Unsupervised Learning

  2021cites this paper
• Multi-category multi-state information ensemble-based classification method for precise diagnosis of three cancers

  2021cites this paper
• Side effect prediction based on drug-induced gene expression profiles and random forest with iterative feature selection

  2021cites this paper
• Optimal Feature Set Size in Random Forest Regression

  2021cites this paper
• Improving random forest predictions in small datasets from two-phase sampling designs

  2021cites this paper
• Exploration of 2-neuron memory units in spiking neural networks

  2020cites this paper
• Dynamic clustering method for imbalanced learning based on AdaBoost

  2020cites this paper
• Discrete Wavelet Transform (DWT) and Random Forest for Cancer Detection Based on Microarray Data Classification

  2020cites this paper
• Vis-SWIR spectral prediction model for soil organic matter with different grouping strategies

  2020cites this paper
• Drug REpurposing using AI/ML tools - for Rare Diseases (DREAM-RD): A case study with Fragile X Syndrome (FXS)

  2020cites this paper
• Predicting prognosis of endometrioid endometrial adenocarcinoma on the basis of gene expression and clinical features using Random Forest

  2019cites this paper
• Using Forward / Backword Decision Trees on GSM441161 and GSE32863 Microarray Data

  2019cites this paper
• Knowledge and biomarkers extraction system by integrating heterogeneous information sources

  2019cites this paper
• Application of Hyperspectral Imaging Technology in Classification of Tobacco Leaves and Impurities

  2019cites this paper
• Whale optimized mixed kernel function of support vector machine for colorectal cancer diagnosis

  2019cites this paper
• KLASIFIKASI DATA KANKER BERDASARKAN MIKRO ARRAY GEN MENGGUNAKAN JARINGAN SYARAF TIRUAN

  2019cites this paper
• Cancer Classification Using Microarray Data By DPCAForest

  2019influential citation
• Feature Ranking using Robust Fuzzy Score Function for Gene Expression Data

  2019cites this paper
• A Clustering Approach for Feature Selection in Microarray Data Classification Using Random Forest

  2018cites this paper
• Combination of CRP and NLR: a better predictor of postoperative survival in patients with gastric cancer

  2018cites this paper
• A data mining framework based on boundary-points for gene selection from DNA-microarrays: Pancreatic Ductal Adenocarcinoma as a case study

  2018cites this paper
• Feature Importance for Human Epithelial (HEp-2) Cell Image Classification

  2018cites this paper
• Automatic Product Name Recognition from Short Product Descriptions

  2018cites this paper
• An Online Method Based on Random Forest for Air Pollutant Concentration Forecasting

  2018cites this paper
• On the classification techniques in data mining for microarray data classification

  2018cites this paper
• Review of Gene Subset Selection using Modified K-Nearest Neighbor Clustering Algorithm

  2018cites this paper
• Random Forest-Based Feature Importance for HEp-2 Cell Image Classification

  2017cites this paper
• Improved Support Vector Machine Using Multiple SVM-RFE for Cancer Classification

  2017influential citation
• Feature Extraction and Classification on Esophageal X-Ray Images of Xinjiang Kazak Nationality

  2017cites this paper
• Classification of Colorectal Cancer Using Clustering and Feature Selection Approaches

  2017cites this paper
• Application of unsupervised analysis techniques to lung cancer patient data

  2017cites this paper
• K-Means Clustering with Infinite Feature Selection for Classification Tasks in Gene Expression Data

  2017cites this paper
• Predictive modeling based on random forests

  2017cites this paper
• Gene Selection from Microarray Data for Alzheimer's Disease Using Random Forest

  2017cites this paper
• DETECT I & DETECT II: a study protocol for a prospective multicentre observational study to validate the UroMark assay for the detection of bladder cancer from urinary cells

  2017cites this paper
• An Agent-Based Clustering Approach for Gene Selection in Gene Expression Microarray

  2017cites this paper
• Identifying Drug–Drug Interactions by Data Mining: A Pilot Study of Warfarin-Associated Drug Interactions

  2016cites this paper
• Hybrid One-Class Ensemble for High-Dimensional Data Classification

  2016cites this paper
• Function Prediction of Disease-Related Long Intergenic Non-Coding RNA Using Random Forest

  2016cites this paper
• Finding a disease-related gene from microarray data using random forest

  2016cites this paper
• Gene selection and classification approach for microarray data based on Random Forest Ranking and BBHA

  2016influential citation
• Early Transcriptome Signatures from Immunized Mouse Dendritic Cells Predict Late Vaccine-Induced T-Cell Responses

  2016cites this paper
• Genetic and Epigenetic Variations in Asthma and Wheeze Illnesses

  2015cites this paper
• New approach for imbalanced biological dataset classification

  2015cites this paper
• Accelerating wrapper-based feature selection with K-nearest-neighbor

  2015cites this paper
• Improving PLS-RFE based gene selection for microarray data classification

  2015cites this paper
• Selecting target concept in one-class classification for handling class imbalance problem

  2015cites this paper
• Handling Label Noise in Microarray Classification with One-Class Classifier Ensemble

  2014cites this paper
• Random Forest and Gene Ontology for functional analysis of microarray data

  2014cites this paper
• RAFT - Real And False TFBSs

  2014cites this paper
• A hybrid classifier committee for analysing asymmetry features in breast thermograms

  2014cites this paper
• A Comparative Result Analysis of Human Cancer Diagnosis using Ensemble Classification Methods

  2013cites this paper
• A balanced iterative random forest for gene selection from microarray data

  2013cites this paper
• Combining one-class support vector machines for microarray classification

  2013cites this paper
• Improving the resolution of interaction maps : a middleground between high-resolution complexes and genome-wide interactomes

  2013cites this paper
• Multiple Gene Sets for Cancer Classification Using Gene Range Selection Based on Random Forest

  2013cites this paper
• Multiclass Prediction for Cancer Microarray Data Using Various Variables Range Selection Based on Random Forest

  2013cites this paper
• Predicting protective bacterial antigens using random forest classifiers

  2012cites this paper
• Aberrant expression of microRNA in gliomas: Molecular mechanisms, functional consequences and clinical significance

  2012cites this paper
• Characterization of ammonia-oxidizing archaea by Raman microspectroscopy

  2012cites this paper