بدائل البحث:
algorithm python » algorithms within (توسيع البحث), algorithm both (توسيع البحث)
within function » fibrin function (توسيع البحث), python function (توسيع البحث), protein function (توسيع البحث)
algorithm a » algorithms a (توسيع البحث), algorithm _ (توسيع البحث), algorithm b (توسيع البحث)
algorithm python » algorithms within (توسيع البحث), algorithm both (توسيع البحث)
within function » fibrin function (توسيع البحث), python function (توسيع البحث), protein function (توسيع البحث)
algorithm a » algorithms a (توسيع البحث), algorithm _ (توسيع البحث), algorithm b (توسيع البحث)
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4761
Data Sheet 1_The role and machine learning analysis of mitochondrial autophagy-related gene expression in lung adenocarcinoma.zip
منشور في 2025"…Objective<p>Lung adenocarcinoma (LUAD) continues to be a primary cause of cancer-related mortality globally, highlighting the urgent need for novel insights finto its molecular mechanisms. …"
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4762
Data Sheet 2_The role and machine learning analysis of mitochondrial autophagy-related gene expression in lung adenocarcinoma.pdf
منشور في 2025"…Objective<p>Lung adenocarcinoma (LUAD) continues to be a primary cause of cancer-related mortality globally, highlighting the urgent need for novel insights finto its molecular mechanisms. …"
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4763
Data Sheet 3_The role and machine learning analysis of mitochondrial autophagy-related gene expression in lung adenocarcinoma.pdf
منشور في 2025"…Objective<p>Lung adenocarcinoma (LUAD) continues to be a primary cause of cancer-related mortality globally, highlighting the urgent need for novel insights finto its molecular mechanisms. …"
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4764
Table 3_Combining WGCNA and machine learning to identify mechanisms and biomarkers of hyperthyroidism and atrial fibrillation.xlsx
منشور في 2025"…Differential gene analysis was performed using the “limma” package, and overlapping genes shared by both diseases were identified through weighted gene co-expression network analysis (WGCNA), followed by functional enrichment analysis. Machine learning algorithms were also applied to identify key biomarkers. …"
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4765
Table 4_Combining WGCNA and machine learning to identify mechanisms and biomarkers of hyperthyroidism and atrial fibrillation.docx
منشور في 2025"…Differential gene analysis was performed using the “limma” package, and overlapping genes shared by both diseases were identified through weighted gene co-expression network analysis (WGCNA), followed by functional enrichment analysis. Machine learning algorithms were also applied to identify key biomarkers. …"
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4766
Table 5_Combining WGCNA and machine learning to identify mechanisms and biomarkers of hyperthyroidism and atrial fibrillation.docx
منشور في 2025"…Differential gene analysis was performed using the “limma” package, and overlapping genes shared by both diseases were identified through weighted gene co-expression network analysis (WGCNA), followed by functional enrichment analysis. Machine learning algorithms were also applied to identify key biomarkers. …"
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4767
Table 1_Combining WGCNA and machine learning to identify mechanisms and biomarkers of hyperthyroidism and atrial fibrillation.xlsx
منشور في 2025"…Differential gene analysis was performed using the “limma” package, and overlapping genes shared by both diseases were identified through weighted gene co-expression network analysis (WGCNA), followed by functional enrichment analysis. Machine learning algorithms were also applied to identify key biomarkers. …"
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4768
Data Sheet 1_Comprehensive bioinformatics analysis identifies metabolic and immune-related diagnostic biomarkers shared between diabetes and COPD using multi-omics and machine lear...
منشور في 2025"…Multiple machine learning algorithms identified 4 shared biomarkers for COPD and diabetes, including CADPS, EDNRB, THBS4 and TMEM27. …"
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4769
Table 2_Combining WGCNA and machine learning to identify mechanisms and biomarkers of hyperthyroidism and atrial fibrillation.xlsx
منشور في 2025"…Differential gene analysis was performed using the “limma” package, and overlapping genes shared by both diseases were identified through weighted gene co-expression network analysis (WGCNA), followed by functional enrichment analysis. Machine learning algorithms were also applied to identify key biomarkers. …"
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4770
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4771
DataSheet1_Identification of potential auxin response candidate genes for soybean rapid canopy coverage through comparative evolution and expression analysis.zip
منشور في 2024"…Further development of this and similar algorithms for defining and quantifying tissue- and phenotype-specificity in gene expression may allow expansion of diversity in valuable phenotypes in important crops.…"
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4772
Data Sheet 1_Identification and validation of cellular senescence-related genes and immune cell infiltration characteristics in intervertebral disc degeneration.pdf
منشور في 2025"…SRDEGs were analyzed using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). A protein–protein interaction (PPI) network was also drawn, and the hub SRDEGs were obtained using 11 different algorithms. …"
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4773
Supplementary file 1_Socioeconomic status and lifestyle as factors of multimorbidity among older adults in China: results from the China Health and Retirement Longitudinal Survey.d...
منشور في 2025"…Socioeconomic and functional variables were dominant factors associated with multimorbidity, suggesting structural roots of health inequality. …"
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4774
Image 1_Exercise-related immune gene signature for hepatocellular carcinoma: machine learning and multi-omics analysis.pdf
منشور في 2025"…</p>Objective<p>This study aims to construct a machine learning-based prognostic signature using exercise-related immune genes (EIGs) to predict prognosis in HCC.…"
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4775
Data Sheet 1_Exercise-related immune gene signature for hepatocellular carcinoma: machine learning and multi-omics analysis.xlsx
منشور في 2025"…</p>Objective<p>This study aims to construct a machine learning-based prognostic signature using exercise-related immune genes (EIGs) to predict prognosis in HCC.…"
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4776
Data Sheet 1_Case Report: Myelodysplastic/myeloproliferative neoplasm with concurrent SF3B1, ASXL1, JAK2 and CBL mutations and <15% bone marrow ringed sideroblasts.docx
منشور في 2025"…Comprehensive genomic profiling revealed a unique quadruple mutation signature: ASXL1 p.G646Wfs*12 (9.8% VAF), JAK2 p.R683G (17.5%), and CBL p.R149Q (16.2%), with preserved karyotype. …"
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4777
Table 1_Case Report: Myelodysplastic/myeloproliferative neoplasm with concurrent SF3B1, ASXL1, JAK2 and CBL mutations and <15% bone marrow ringed sideroblasts.xlsx
منشور في 2025"…Comprehensive genomic profiling revealed a unique quadruple mutation signature: ASXL1 p.G646Wfs*12 (9.8% VAF), JAK2 p.R683G (17.5%), and CBL p.R149Q (16.2%), with preserved karyotype. …"
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4778
Data Sheet 2_Case Report: Myelodysplastic/myeloproliferative neoplasm with concurrent SF3B1, ASXL1, JAK2 and CBL mutations and <15% bone marrow ringed sideroblasts.pdf
منشور في 2025"…Comprehensive genomic profiling revealed a unique quadruple mutation signature: ASXL1 p.G646Wfs*12 (9.8% VAF), JAK2 p.R683G (17.5%), and CBL p.R149Q (16.2%), with preserved karyotype. …"
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4779
Image 4_Identification of lactylation-related biomarkers in osteoporosis from transcriptome and single-cell data.jpeg
منشور في 2025"…Subsequently, nomograms, functional enrichment analyses, immune infiltration analyses, regulatory network construction, drug prediction, and molecular docking were performed to characterize the functional and clinical significance of the biomarkers. …"
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4780
Table 4_Identification of lactylation-related biomarkers in osteoporosis from transcriptome and single-cell data.xlsx
منشور في 2025"…Subsequently, nomograms, functional enrichment analyses, immune infiltration analyses, regulatory network construction, drug prediction, and molecular docking were performed to characterize the functional and clinical significance of the biomarkers. …"