Image 1_SUMOylation-related genes define prognostic subtypes in stomach adenocarcinoma: integrating single-cell analysis and machine learning analyses.tif by Kaiping Luo (14494751)

“…The random survival forest (RSF)-based SRS model (AUC: 0.97) stratified patients into high-/low-risk groups, where high-risk patients exhibited advanced tumor stages, immune suppression, and elevated TIDE scores (p < 0.001). Functional enrichment linked low-risk groups to genome stability pathways (DNA repair, cell cycle control). …”

Image 2_SUMOylation-related genes define prognostic subtypes in stomach adenocarcinoma: integrating single-cell analysis and machine learning analyses.tif by Kaiping Luo (14494751)

“…The random survival forest (RSF)-based SRS model (AUC: 0.97) stratified patients into high-/low-risk groups, where high-risk patients exhibited advanced tumor stages, immune suppression, and elevated TIDE scores (p < 0.001). Functional enrichment linked low-risk groups to genome stability pathways (DNA repair, cell cycle control). …”

Image 4_SUMOylation-related genes define prognostic subtypes in stomach adenocarcinoma: integrating single-cell analysis and machine learning analyses.tif by Kaiping Luo (14494751)

“…The random survival forest (RSF)-based SRS model (AUC: 0.97) stratified patients into high-/low-risk groups, where high-risk patients exhibited advanced tumor stages, immune suppression, and elevated TIDE scores (p < 0.001). Functional enrichment linked low-risk groups to genome stability pathways (DNA repair, cell cycle control). …”

Data Sheet 1_Novel diagnostic biomarkers associated with macrophage-microglia in spinal cord injury.pdf by Manyi Zheng (22221913)

“…</p>Results<p>Single-cell RNA sequencing identified 16 distinct cellular subpopulations, among which MM cells were split into four subsets according to functional characteristics. Enrichment analyses, including KEGG, GO, and GSEA, revealed that the MDEGs were closely linked to key biological processes in SCI. …”

Table 4_Novel diagnostic biomarkers associated with macrophage-microglia in spinal cord injury.xlsx by Manyi Zheng (22221913)

“…</p>Results<p>Single-cell RNA sequencing identified 16 distinct cellular subpopulations, among which MM cells were split into four subsets according to functional characteristics. Enrichment analyses, including KEGG, GO, and GSEA, revealed that the MDEGs were closely linked to key biological processes in SCI. …”

Table 1_Novel diagnostic biomarkers associated with macrophage-microglia in spinal cord injury.xlsx by Manyi Zheng (22221913)

“…</p>Results<p>Single-cell RNA sequencing identified 16 distinct cellular subpopulations, among which MM cells were split into four subsets according to functional characteristics. Enrichment analyses, including KEGG, GO, and GSEA, revealed that the MDEGs were closely linked to key biological processes in SCI. …”

Data Sheet 2_Novel diagnostic biomarkers associated with macrophage-microglia in spinal cord injury.pdf by Manyi Zheng (22221913)

“…</p>Results<p>Single-cell RNA sequencing identified 16 distinct cellular subpopulations, among which MM cells were split into four subsets according to functional characteristics. Enrichment analyses, including KEGG, GO, and GSEA, revealed that the MDEGs were closely linked to key biological processes in SCI. …”

Supplementary file 1_Novel diagnostic biomarkers associated with macrophage-microglia in spinal cord injury.xlsx by Manyi Zheng (22221913)

“…</p>Results<p>Single-cell RNA sequencing identified 16 distinct cellular subpopulations, among which MM cells were split into four subsets according to functional characteristics. Enrichment analyses, including KEGG, GO, and GSEA, revealed that the MDEGs were closely linked to key biological processes in SCI. …”

Table 1_Identification of immune and major depressive disorder-related diagnostic markers for early nonalcoholic fatty liver disease by WGCNA and machine learning.xlsx by Yuyun Jia (21604337)

“…</p>Results<p>Fourteen genes strongly linked to both the immune system and the two conditions were identified. …”

Table 2_Novel diagnostic biomarkers associated with macrophage-microglia in spinal cord injury.xlsx by Manyi Zheng (22221913)

“…</p>Results<p>Single-cell RNA sequencing identified 16 distinct cellular subpopulations, among which MM cells were split into four subsets according to functional characteristics. Enrichment analyses, including KEGG, GO, and GSEA, revealed that the MDEGs were closely linked to key biological processes in SCI. …”

Supplementary file 2_Novel diagnostic biomarkers associated with macrophage-microglia in spinal cord injury.xlsx by Manyi Zheng (22221913)

“…</p>Results<p>Single-cell RNA sequencing identified 16 distinct cellular subpopulations, among which MM cells were split into four subsets according to functional characteristics. Enrichment analyses, including KEGG, GO, and GSEA, revealed that the MDEGs were closely linked to key biological processes in SCI. …”

Table 3_Novel diagnostic biomarkers associated with macrophage-microglia in spinal cord injury.xlsx by Manyi Zheng (22221913)

“…</p>Results<p>Single-cell RNA sequencing identified 16 distinct cellular subpopulations, among which MM cells were split into four subsets according to functional characteristics. Enrichment analyses, including KEGG, GO, and GSEA, revealed that the MDEGs were closely linked to key biological processes in SCI. …”

Data Sheet 1_Correlation between oral microbial characteristics and overall bone density of Postmenopausal women based on macrogenomic analysis.pdf by Man Liu (697951)

“…KEGG pathway analysis was used to reveal variations in microbial functions. Based on these analyses, predictive models for bone density status were constructed using LASSO regression and random forest algorithms.…”

Table 1_Identification of crosstalk genes and diagnostic biomarkers in systemic sclerosis associated sarcopenia through integrative analysis and machine learning.docx by Yanfang Wu (206076)

“…Immune cell infiltration profiles and functional correlations were also examined.</p>Results<p>Five key CGs—NOX4, STC2, NEK6, IGSF10, and EMX2—were identified as molecular links between SSc and sarcopenia. …”

Image 2_Integrated transcriptomic and single-cell RNA-seq analysis identifies CLCNKB, KLK1 and PLEKHA4 as key gene of AKI-to-CKD progression.tif by Fanhua Zeng (2097133)

“…Functional enrichment, drug prediction analyses and immune cells infiltration were conducted to investigate the functional mechanisms of the identified biomarkers. …”

Image 1_Integrated transcriptomic and single-cell RNA-seq analysis identifies CLCNKB, KLK1 and PLEKHA4 as key gene of AKI-to-CKD progression.tif by Fanhua Zeng (2097133)

“…Functional enrichment, drug prediction analyses and immune cells infiltration were conducted to investigate the functional mechanisms of the identified biomarkers. …”

Table 1_Integrated transcriptomic and single-cell RNA-seq analysis identifies CLCNKB, KLK1 and PLEKHA4 as key gene of AKI-to-CKD progression.xlsx by Fanhua Zeng (2097133)

“…Functional enrichment, drug prediction analyses and immune cells infiltration were conducted to investigate the functional mechanisms of the identified biomarkers. …”

Turkish_native_goat_genotypes by Yalçın YAMAN (20209833)

“…An ensemble feature-importance analysis, evaluated through 10,000 permutations, identified 31 FDR-significant SNPs representing markers consistently associated with MAP status. Functional annotation indicated involvement of immune-related processes such as cytokine–receptor signalling, antigen presentation, glycan-mediated T-cell regulation, and NF-κB–linked inflammatory pathways. …”

Table 1_Development and validation of a machine-learning-based model for identification of genes associated with sepsis-associated acute kidney injury.docx by Chen Lin (95910)

“…Finally, we used functional enrichment analysis to identify potential therapeutic agents for AKI.…”

Table 2_Innate immune cell barrier-related genes inform precision prognosis in pancreatic cancer.xlsx by Qiang Luo (387063)

“…Prognostic modeling of PC was developed using 14 machine learning algorithms, with performance validated through long-term survival metrics, functional enrichment, immune infiltration analysis, and drug sensitivity profiling. …”