Results 11 to 20 of about 11,201,470 (335)
Gene Selection in Cancer Classification Using Sparse Logistic Regression with L1/2 Regularization
Applied Sciences, 2018 In recent years, gene selection for cancer classification based on the expression of a small number of gene biomarkers has been the subject of much research in genetics and molecular biology.
Shengbing Wu +3 more
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Deep gene selection method to select genes from microarray datasets for cancer classification [PDF]
BMC Bioinformatics, 2019 Microarray datasets consist of complex and high-dimensional samples and genes, and generally the number of samples is much smaller than the number of genes.
Russul Alanni +3 more
semanticscholar +4 more sources
DGDRP: drug-specific gene selection for drug response prediction via re-ranking through propagating and learning biological network [PDF]
Frontiers in GeneticsIntroduction: 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
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Hybrid gene selection approach using XGBoost and multi-objective genetic algorithm for cancer classification [PDF]
Medical and Biological Engineering and Computing, 2021 Microarray gene expression data are often accompanied by a large number of genes and a small number of samples. However, only a few of these genes are relevant to cancer, resulting in significant gene selection challenges.
Xiongshi Deng +3 more
semanticscholar +1 more source
A Modified Memetic Algorithm with an Application to Gene Selection in a Sheep Body Weight Study
Animals, 2022 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
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Enhancing Feature Selection Optimization for COVID-19 Microarray Data
COVID, 2023 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
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Selective gene amplification [PDF]
Protein Engineering Design and Selection, 2007 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
Frontiers in Genetics, 2021 To tackle the challenges in genomic data analysis caused by their tens of thousands of dimensions while having a small number of examples and unbalanced examples between classes, the technique of unsupervised feature selection based on standard deviation
Juanying Xie +5 more
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SLNL: A novel method for gene selection and phenotype classification
International Journal of Intelligent Systems, 2022 One of the central tasks of genome research is to predict phenotypes and discover some important gene biomarkers. However, there are three main problems in analyzing genomics data to predict phenotypes and gene marker selection. Such as large p and small
Hai-Hui Huang +4 more
semanticscholar +1 more source
Frontiers in Genetics, 2021 Cancer subtype identification is important to facilitate cancer diagnosis and select effective treatments. Clustering of cancer patients based on high-dimensional RNA-sequencing data can be used to detect novel subtypes, but only a subset of the features
David Källberg +4 more
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