May 1, 2022 · A new gene selection method for cancer biomarker identification has been developed. The method combines feature selection, SVM, and ABCD algorithm.
It can be concluded that the proposed method is effective in gene selection for the identification of cancer biomarkers from RNA-seq data. ResearchGate Logo.
Nov 20, 2014 · We demonstrate a computational model for producing highly sensitive and specific cancer biomarker signatures from RNA-Seq data.
Jun 11, 2024 · We propose DOT, a multi-objective optimization framework for transferring cellular features across these data modalities, thus integrating their complementary ...
Missing: biomarkers | Show results with:biomarkers
Oct 10, 2024 · We introduce three- and four-objective optimization strategies based on genetic algorithms to identify clinically actionable biomarkers in omics ...
An efficient search algorithm for biomarker selection from RNA-seq ...
dl.acm.org › doi › JIFS-171297
After statistical noise removing from the original large-scale dataset, a multi-objective optimization process is proposed to select the best non-dominated ...
Sep 18, 2022 · We propose two improved NSGA2 algorithms for finding subsets of biomarkers exhibiting different trade-offs between accuracy and feature number.
Dec 21, 2022 · This framework identified a robust, interpretable COVID-19 signature and is broadly applicable in other disease contexts.
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In this paper, we take the module containing the significant disease-related genes and their interactions from biological networks as a module biomarker, and ...
Oct 10, 2024 · We introduce a novel hybrid gene selection approach that combines the Harris Hawk Optimization (HHO) and Whale Optimization (WO) algorithms with ...