WERFE: A Gene Selection Algorithm Based on Recursive Feature Elimination and Ensemble Strategy
Gene selection algorithm in micro-array data classification problem finds a small set of genes which are most informative and distinctive. A well-performed gene selection algorithm should pick a set of genes that achieve high performance and the size of ...
Qi Chen +5 more
doaj +3 more sources
A Multi-Task Ensemble Strategy for Gene Selection and Cancer Classification [PDF]
Gene expression-based tumor classification aims to distinguish tumor types based on gene expression profiles. This task is difficult due to the high dimensionality of gene expression data and limited sample sizes.
Suli Lin +3 more
doaj +2 more sources
Ensemble Algorithm Based on Gene Selection, Data Augmentation, and Boosting Approaches for Ovarian Cancer Classification [PDF]
Background: Ovarian cancer is a difficult and lethal illness that requires early detection and precise classification for effective therapy. Microarray technology has permitted the simultaneous assessment of hundreds of genes’ expression levels, yielding
Zne-Jung Lee +3 more
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Hybrid Gene Selection Algorithm for Cancer Classification Using Nuclear Reaction Optimization (NRO) [PDF]
Microarray gene expression data are characterized by high dimensionality and small sample sizes, which complicates cancer classification tasks. To address these challenges, this study proposes a hybrid gene selection approach that integrates a filter ...
Shahad Alkamli, Hala Alshamlan
doaj +2 more sources
Evaluating the Nuclear Reaction Optimization (NRO) Algorithm for Gene Selection in Cancer Classification [PDF]
Background/Objectives: Cancer classification using microarray datasets presents a significant challenge due to their extremely high dimensionality. This complexity necessitates advanced optimization methods for effective gene selection.
Shahad Alkamli, Hala Alshamlan
doaj +2 more sources
A Hybrid Ensemble Equilibrium Optimizer Gene Selection Algorithm for Microarray Data [PDF]
As modern medical technology advances, the utilization of gene expression data has proliferated across diverse domains, particularly in cancer diagnosis and prognosis monitoring. However, gene expression data is often characterized by high dimensionality
Peng Su +4 more
doaj +2 more sources
DGDRP: drug-specific gene selection for drug response prediction via re-ranking through propagating and learning biological network [PDF]
Introduction: Drug response prediction, especially in terms of cell viability prediction, is a well-studied research problem with significant implications for personalized medicine.
Minwoo Pak +7 more
doaj +2 more sources
A Modified Memetic Algorithm with an Application to Gene Selection in a Sheep Body Weight Study
Selecting the minimal best subset out of a huge number of factors for influencing the response is a fundamental and very challenging NP-hard problem because the presence of many redundant genes results in over-fitting easily while missing an important ...
Maoxuan Miao +3 more
doaj +1 more source
Enhancing Feature Selection Optimization for COVID-19 Microarray Data
The utilization of gene selection techniques is crucial when dealing with extensive datasets containing limited cases and numerous genes, as they enhance the learning processes and improve overall outcomes.
Gayani Krishanthi +4 more
doaj +1 more source
Selective gene amplification [PDF]
We describe a system for directed evolution based on in vitro compartmentalisation in which amplification of a gene is coupled to the formation of product by the enzyme it encodes. This approach mimics the process of natural selection; 'fitter' genes--encoding more efficient enzymes--have more 'offspring'.
Bernard T, Kelly, Andrew D, Griffiths
openaire +2 more sources

