Search alternatives:
process optimization » model optimization (Expand Search)
design optimization » bayesian optimization (Expand Search)
based process » based processes (Expand Search), based probes (Expand Search), based proteins (Expand Search)
binary task » binary mask (Expand Search)
task design » based design (Expand Search)
degs based » diets based (Expand Search), lens based (Expand Search), wgs based (Expand Search)
process optimization » model optimization (Expand Search)
design optimization » bayesian optimization (Expand Search)
based process » based processes (Expand Search), based probes (Expand Search), based proteins (Expand Search)
binary task » binary mask (Expand Search)
task design » based design (Expand Search)
degs based » diets based (Expand Search), lens based (Expand Search), wgs based (Expand Search)
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41
Models and Dataset
Published 2025“…The algorithm does not rely on predefined control parameters like crossover or mutation rates, which makes it lightweight and easy to implement for various feature selection and optimization tasks.…”
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42
DataSheet_1_Integrated analysis of potential gene crosstalk between non-alcoholic fatty liver disease and diabetic nephropathy.docx
Published 2022“…Ten optimal crosstalk genes were selected by LASSO regression and Boruta algorithm, including CD36, WIPI1, CBX7, FCN1, SLC35D2, CP, ZDHHC3, PTPN3, LPL, and SPP1. …”
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43
Data Sheet 1_Immunogenic cell death-related genes as prognostic biomarkers and therapeutic insights in uterine corpus endometrial carcinoma: an integrative bioinformatics analysis....
Published 2025“…Differentially expressed genes (DEGs) were identified from transcriptomic data processed with the "DESeq2" R package. …”
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44
Table2_Comprehensive analysis of key m5C modification-related genes in type 2 diabetes.XLSX
Published 2022“…</p><p>Methods: The merged gene expression profiles from two Gene Expression Omnibus (GEO) datasets were used to identify m5C-related genes and T2D-related differentially expressed genes (DEGs). Least-absolute shrinkage and selection operator (LASSO) regression analysis was performed to identify optimal predictors of T2D. …”
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45
Table1_Comprehensive analysis of key m5C modification-related genes in type 2 diabetes.XLSX
Published 2022“…</p><p>Methods: The merged gene expression profiles from two Gene Expression Omnibus (GEO) datasets were used to identify m5C-related genes and T2D-related differentially expressed genes (DEGs). Least-absolute shrinkage and selection operator (LASSO) regression analysis was performed to identify optimal predictors of T2D. …”
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46
Presentation1_Comprehensive analysis of key m5C modification-related genes in type 2 diabetes.PDF
Published 2022“…</p><p>Methods: The merged gene expression profiles from two Gene Expression Omnibus (GEO) datasets were used to identify m5C-related genes and T2D-related differentially expressed genes (DEGs). Least-absolute shrinkage and selection operator (LASSO) regression analysis was performed to identify optimal predictors of T2D. …”
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47
Image1_Comprehensive analysis of key m5C modification-related genes in type 2 diabetes.PDF
Published 2022“…</p><p>Methods: The merged gene expression profiles from two Gene Expression Omnibus (GEO) datasets were used to identify m5C-related genes and T2D-related differentially expressed genes (DEGs). Least-absolute shrinkage and selection operator (LASSO) regression analysis was performed to identify optimal predictors of T2D. …”
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48
<b>A Single-cell Transcriptomic Sequencing Dataset of Early Female and Male Chicken (</b><b><i>Gallus gallus</i></b><b>) Embryos</b>
Published 2025“…The UMAP algorithm was optimized with a neighborhood size of 20 to achieve optimal cell clustering and clear visual representation of the cell populations.…”