GameOfLife Prediction Dataset حسب David Towers (12857447)

"…This task is relatively simple for a human to do if a bit tedious, and should theoretically be simple for Machine Learning algorithms. Each cells's state is calculated based off the number of alive neighbour's in the previous step. …"

Code حسب Baoqiang Chen (21099509)

"…We divided the dataset into training and test sets, using 70% of the genes for training and 30% for testing. We implemented machine learning algorithms using the following R packages: rpart for Decision Trees, gbm for Gradient Boosting Machines (GBM), ranger for Random Forests, the glm function for Generalized Linear Models (GLM), and xgboost for Extreme Gradient Boosting (XGB). …"

Core data حسب Baoqiang Chen (21099509)

"…We divided the dataset into training and test sets, using 70% of the genes for training and 30% for testing. We implemented machine learning algorithms using the following R packages: rpart for Decision Trees, gbm for Gradient Boosting Machines (GBM), ranger for Random Forests, the glm function for Generalized Linear Models (GLM), and xgboost for Extreme Gradient Boosting (XGB). …"

Data Sheet 2_Comprehensive analysis of regulatory B Cell related genes in prognosis and therapeutic response in lung adenocarcinoma.xlsx حسب Liangyu Zhang (8947964)

"…Differentially expressed genes between the two clusters were then used to construct the BREGI using 32 algorithms, including traditional regression, machine learning, deep learning, and 274 different combinations. …"

Data Sheet 1_Comprehensive analysis of regulatory B Cell related genes in prognosis and therapeutic response in lung adenocarcinoma.docx حسب Liangyu Zhang (8947964)

"…Differentially expressed genes between the two clusters were then used to construct the BREGI using 32 algorithms, including traditional regression, machine learning, deep learning, and 274 different combinations. …"

Data Sheet 1_Deciphering novel mitochondrial signatures: multi-omics analysis uncovers cross-disease markers and oligodendrocyte pathways in Alzheimer’s disease and glioblastoma.do... حسب Xuan Xu (781842)

"…</p>Methods<p>In this study, we analyzed single-cell transcriptomic data using 10 machine learning algorithms to identify mitochondria-associated cell-specific markers. …"

Table 1_Deciphering novel mitochondrial signatures: multi-omics analysis uncovers cross-disease markers and oligodendrocyte pathways in Alzheimer’s disease and glioblastoma.xlsx حسب Xuan Xu (781842)

"…</p>Methods<p>In this study, we analyzed single-cell transcriptomic data using 10 machine learning algorithms to identify mitochondria-associated cell-specific markers. …"

Table 1_Integrated transcriptomic and network analysis reveals candidate immune–metabolic biomarkers in children with the inattentive type of ADHD.xlsx حسب Qiaoyan Shao (22357861)

"…High-confidence biomarkers were selected via a multi-step pipeline combining protein-protein interaction (PPI) network analysis and machine learning feature selection (LASSO regression, Boruta algorithm). …"

Image 1_Integrated transcriptomic and network analysis reveals candidate immune–metabolic biomarkers in children with the inattentive type of ADHD.tif حسب Qiaoyan Shao (22357861)

"…High-confidence biomarkers were selected via a multi-step pipeline combining protein-protein interaction (PPI) network analysis and machine learning feature selection (LASSO regression, Boruta algorithm). …"

Table 1_Bridging aging, immunity, and atherosclerosis: novel insights into senescence-related genes.xlsx حسب Yan Lu (32611)

"…Subsequently, differential expression analysis, weighted gene co-expression network analysis, accompanied by 3 machine learning algorithms, LASSO, SVM and RF, were performed to identify diagnostic genes. …"

Table 2_Integrated transcriptomic and network analysis reveals candidate immune–metabolic biomarkers in children with the inattentive type of ADHD.xlsx حسب Qiaoyan Shao (22357861)

"…High-confidence biomarkers were selected via a multi-step pipeline combining protein-protein interaction (PPI) network analysis and machine learning feature selection (LASSO regression, Boruta algorithm). …"

Table 2_Histone-related gene WDR77 promotes tumor progression through cell cycle regulation in skin cutaneous melanoma.xls حسب Haoxue Zhang (12208580)

"…</p>Methods<p>Transcriptomic data from TCGA-SKCM and five GEO datasets were analyzed. Ten machine learning algorithms were integrated to build 101 prognostic models. …"

DataSheet2_Shedding light on the DICER1 mutational spectrum of uncertain significance in malignant neoplasms.PDF حسب D. S. Bug (19791612)

"…The latest contemporary methods of variant effect prediction utilize machine learning algorithms on bulk data, yielding suboptimal correlation with biological data. …"

Table 3_Histone-related gene WDR77 promotes tumor progression through cell cycle regulation in skin cutaneous melanoma.xlsx حسب Haoxue Zhang (12208580)

"…</p>Methods<p>Transcriptomic data from TCGA-SKCM and five GEO datasets were analyzed. Ten machine learning algorithms were integrated to build 101 prognostic models. …"

DataSheet2_Shedding light on the DICER1 mutational spectrum of uncertain significance in malignant neoplasms.PDF حسب D. S. Bug (19791612)

"…The latest contemporary methods of variant effect prediction utilize machine learning algorithms on bulk data, yielding suboptimal correlation with biological data. …"

Table 1_Histone-related gene WDR77 promotes tumor progression through cell cycle regulation in skin cutaneous melanoma.xlsx حسب Haoxue Zhang (12208580)

"…</p>Methods<p>Transcriptomic data from TCGA-SKCM and five GEO datasets were analyzed. Ten machine learning algorithms were integrated to build 101 prognostic models. …"

Data Sheet 2_Histone-related gene WDR77 promotes tumor progression through cell cycle regulation in skin cutaneous melanoma.zip حسب Haoxue Zhang (12208580)

"…</p>Methods<p>Transcriptomic data from TCGA-SKCM and five GEO datasets were analyzed. Ten machine learning algorithms were integrated to build 101 prognostic models. …"

Data Sheet 1_Histone-related gene WDR77 promotes tumor progression through cell cycle regulation in skin cutaneous melanoma.zip حسب Haoxue Zhang (12208580)

"…</p>Methods<p>Transcriptomic data from TCGA-SKCM and five GEO datasets were analyzed. Ten machine learning algorithms were integrated to build 101 prognostic models. …"

DataSheet1_Shedding light on the DICER1 mutational spectrum of uncertain significance in malignant neoplasms.PDF حسب D. S. Bug (19791612)

"…The latest contemporary methods of variant effect prediction utilize machine learning algorithms on bulk data, yielding suboptimal correlation with biological data. …"

DataSheet1_Shedding light on the DICER1 mutational spectrum of uncertain significance in malignant neoplasms.PDF حسب D. S. Bug (19791612)

"…The latest contemporary methods of variant effect prediction utilize machine learning algorithms on bulk data, yielding suboptimal correlation with biological data. …"