Image 4_The analysis of gene co-expression network and immune infiltration revealed biomarkers between triple-negative and non-triple negative breast cancer.tif حسب Yao Yi (459571)

"…CIBERSORT analysis was used to characterize the composition of immune cells within complex tissues based on gene expression data, typically derived from bulk RNA sequencing or microarray datasets. …"

Data Sheet 1_Epigenetic modifications in developmental coordination disorder: association between DNA methylation and motor performance.docx حسب Fangfang Huang (821089)

"…Among the key DMPs, methylation levels at cg18187326 (FAM45A) and cg11968956 (FAM184A) were significantly associated with both total motor and gross motor scores. In addition, cg03597174 (SEZ6) was negatively associated, while cg05986449 (GPD2) was positively associated with gross motor function.…"

Data Sheet 2_Epigenetic modifications in developmental coordination disorder: association between DNA methylation and motor performance.xlsx حسب Fangfang Huang (821089)

"…Among the key DMPs, methylation levels at cg18187326 (FAM45A) and cg11968956 (FAM184A) were significantly associated with both total motor and gross motor scores. In addition, cg03597174 (SEZ6) was negatively associated, while cg05986449 (GPD2) was positively associated with gross motor function.…"

Table 1_Overlapping genes connect rheumatoid arthritis and head and neck cancer: coincidence or shared immune pathophysiology?.xlsx حسب Ran Wang (169166)

"…An AI-driven computational pipeline applied the Adjusted Binomial Method Algorithm (ABMA) to assess association reliability. …"

Image 2_Intra-tumor heterogeneity-resistant gene signature predicts prognosis and immune infiltration in breast cancer.jpeg حسب Haixing Shen (22315486)

"…A machine learning framework incorporating ten algorithms was used to construct a prognostic signature.The expression levels and oncogenic function of the prognostic genes were validated through RT-qPCR and in vitro experiments.…"

Daniel Jaschke - Talk "Quantum computing @ INFN" (2024) حسب Daniel Jaschke (17341783)

"…Quantum red TEA out of the Quantum TEA library specifically addresses handling tensors with different libraries or hardware, where the tensors are the building block of tensor network algorithms. The benchmark problem is a variational search of a ground state in an interacting model. …"

Image 1_Intra-tumor heterogeneity-resistant gene signature predicts prognosis and immune infiltration in breast cancer.jpeg حسب Haixing Shen (22315486)

"…A machine learning framework incorporating ten algorithms was used to construct a prognostic signature.The expression levels and oncogenic function of the prognostic genes were validated through RT-qPCR and in vitro experiments.…"

Supplementary file 1_Probiotic modulation of maternal gut and milk microbiota and potential implications for infant microbial development in the perinatal period.docx حسب Kian Deng Tye (14200517)

"…Predictive genus clusters associated with probiotics demonstrated robust classification performance, suggesting functional shifts in microbial communities with potential implications for immune programming in early life.…"

Raw LC-MS/MS and RNA-Seq Mitochondria data حسب Stefano Martellucci (16284377)

"…The missing values were imputed with the minimum intensity value for each specific data set; (b) for samples expressed in both scLRP1+/+ and scLRP1-/- tissue, the filtering process required 2 or more proteins to be detected in both scLRP1+/+ and scLRP1-/- samples. …"

DataSheet1_Mitochondrial-related genes as prognostic and metastatic markers in breast cancer: insights from comprehensive analysis and clinical models.docx حسب Yutong Fang (16621143)

"…Moreover, leveraging the GSE102484 dataset, we conducted differential gene expression analysis to identify MRGs related to metastasis, subsequently developing metastasis models via 10 distinct machine-learning algorithms and then selecting the best-performing model. …"

Table1_Mitochondrial-related genes as prognostic and metastatic markers in breast cancer: insights from comprehensive analysis and clinical models.xlsx حسب Yutong Fang (16621143)

"…Moreover, leveraging the GSE102484 dataset, we conducted differential gene expression analysis to identify MRGs related to metastasis, subsequently developing metastasis models via 10 distinct machine-learning algorithms and then selecting the best-performing model. …"

Data Sheet 1_The potential of ME1 in guiding immunotherapeutic strategies for ovarian cancer: insights from pan-cancer research.docx حسب Jiahui Wei (8289561)

"…</p>Methods<p>We analyzed the ME1 expression levels in both normal and tumor tissues across various cancer types. …"

Table 1_The potential of ME1 in guiding immunotherapeutic strategies for ovarian cancer: insights from pan-cancer research.docx حسب Jiahui Wei (8289561)

"…</p>Methods<p>We analyzed the ME1 expression levels in both normal and tumor tissues across various cancer types. …"

Image 4_Integrated machine learning analysis of 30 cell death patterns identifies a novel prognostic signature in glioma.jpeg حسب Minhao Huang (4952764)

"…A pan-death prognostic signature (Cell-Death Score, CDS) was constructed using 114 machine learning algorithm combinations, refined via CoxBoost to select 25 key genes. …"

Table 2_Integrated machine learning analysis of 30 cell death patterns identifies a novel prognostic signature in glioma.xlsx حسب Minhao Huang (4952764)

"…A pan-death prognostic signature (Cell-Death Score, CDS) was constructed using 114 machine learning algorithm combinations, refined via CoxBoost to select 25 key genes. …"

Table 1_Integrated machine learning analysis of 30 cell death patterns identifies a novel prognostic signature in glioma.xlsx حسب Minhao Huang (4952764)

"…A pan-death prognostic signature (Cell-Death Score, CDS) was constructed using 114 machine learning algorithm combinations, refined via CoxBoost to select 25 key genes. …"

Image 3_Integrated machine learning analysis of 30 cell death patterns identifies a novel prognostic signature in glioma.jpeg حسب Minhao Huang (4952764)

"…A pan-death prognostic signature (Cell-Death Score, CDS) was constructed using 114 machine learning algorithm combinations, refined via CoxBoost to select 25 key genes. …"

Image 2_Integrated machine learning analysis of 30 cell death patterns identifies a novel prognostic signature in glioma.jpeg حسب Minhao Huang (4952764)

"…A pan-death prognostic signature (Cell-Death Score, CDS) was constructed using 114 machine learning algorithm combinations, refined via CoxBoost to select 25 key genes. …"

Table 3_Integrated machine learning analysis of 30 cell death patterns identifies a novel prognostic signature in glioma.xlsx حسب Minhao Huang (4952764)

"…A pan-death prognostic signature (Cell-Death Score, CDS) was constructed using 114 machine learning algorithm combinations, refined via CoxBoost to select 25 key genes. …"

Image 1_Integrated machine learning analysis of 30 cell death patterns identifies a novel prognostic signature in glioma.jpeg حسب Minhao Huang (4952764)

"…A pan-death prognostic signature (Cell-Death Score, CDS) was constructed using 114 machine learning algorithm combinations, refined via CoxBoost to select 25 key genes. …"