ReviewAdvances in bioinformatics2015
A Review of Feature Selection and Feature Extraction Methods Applied on Microarray Data.
Review in Advances in bioinformatics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 181 papers.
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Who cites it
181 citing papers in PubMed.
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- Review
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- Neural Latent Filtering for Gene Discovery in Breast Cancer Subtypes.Biotechnology reports (Amsterdam, Netherlands) · 2026Article
- Integrative cross-platform transcriptomic analysis coupled with machine learning identifies candidate biomarkers of abiotic stress resilience in Arabidopsis thaliana.BMC plant biology · 2026Article
- Benchmark of biomarker identification and prognostic modeling methods on diverse censored data.PloS one · 2026Article
- A machine learning integrated multi-omics framework for risk prediction and target discovery in insomnia aggravated sepsis induced acute lung injury.Frontiers in immunology · 2026Article
- Temporal stability and neural complexity in resting-state MEG predict migraine phenotypes.The journal of headache and pain · 2025Article
- Deep Temporal Clustering of Pathological Gait Recovery Patterns in Post-Stroke Patients Using Joint-Angle Trajectories: A Longitudinal Study.Bioengineering (Basel, Switzerland) · 2025Article
- Using a consensus machine learning approach to identify host biomarkers associated with treatment response in pulmonary tuberculosis.Briefings in bioinformatics · 2025Article
- Decision tree-based machine learning methods for identifying colorectal cancer-associated microRNA signatures and their regulatory networks.Scientific reports · 2025Article
- Identification of HybridBiosensors · 2025Article
- Enhancing Alzheimer's Diagnosis with Machine Learning on EEG: A Spectral Feature-Based Comparative Analysis.Diagnostics (Basel, Switzerland) · 2025Article
- Prediction of soybean yellow mottle mosaic virus in soybean using hyperspectral imaging.Plant methods · 2025Article
- GNR: Genetic-Embedded Nuclear Reaction Optimization with F-Score Filter for Gene Selection in Cancer Classification.International journal of molecular sciences · 2025Article
- Predicting EGFRPharmaceuticals (Basel, Switzerland) · 2025Article
- Deep Temporal Clustering of Pathological Gait Patterns in Post-Stroke Patients Using Joint Angle Trajectories: A Cross-Sectional Study.Bioengineering (Basel, Switzerland) · 2025Article
- Interfered feature elimination coupled with feature group selection for wound infection detection by electronic nose.PloS one · 2025Article
- Integrative analysis of miRNA expression data reveals a minimal signature for tumour cells classification.Computational and structural biotechnology journal · 2025Article
121 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
We summarise various ways of performing dimensionality reduction on high-dimensional microarray data. Many different feature selection and feature extraction methods exist and they are being widely used. All these methods aim to remove redundant and irrelevant features so that classification of new instances will be more accurate. A popular source of data is microarrays, a biological platform for gathering gene expressions. Analysing microarrays can be difficult due to the size of the data they provide. In addition the complicated relations among the different genes make analysis more difficult and removing excess features can improve the quality of the results. We present some of the most popular methods for selecting significant features and provide a comparison between them. Their advantages and disadvantages are outlined in order to provide a clearer idea of when to use each one of them for saving computational time and resources.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.