Table4_Transcriptome combined with Mendelian randomization to screen key genes associated with mitochondrial and programmed cell death causally associated with diabetic retinopathy... by Shule Jiang (20295756)

“…Key genes were identified through protein-protein interaction (PPI) analysis using six algorithms (DEgree, DMNC, EPC, MCC, Genes are BottleNeck, and MNC) within Cytoscape software. …”

Image1_Transcriptome combined with Mendelian randomization to screen key genes associated with mitochondrial and programmed cell death causally associated with diabetic retinopathy... by Shule Jiang (20295756)

“…Key genes were identified through protein-protein interaction (PPI) analysis using six algorithms (DEgree, DMNC, EPC, MCC, Genes are BottleNeck, and MNC) within Cytoscape software. …”

Code by Baoqiang Chen (21099509)

“…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 by Baoqiang Chen (21099509)

“…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). …”

Table 1_Exploring the role of TikTok for intersectionality marginalized groups: the case of Muslim female content creators in Germany.docx by Fatima El Sayed (20146977)

“…This shortcoming reflects a broader lack of research on the experiences of marginalized groups within TikTok’s logics and affordances, and what functions the platform fulfills for these communities. …”

Oryza australiensis species-specific gene and protein candidates by Sabrina Morrison (19846869)

“…</p><p dir="ltr">The protein sequence data for both <i>O. australiensis</i> and <i>O. sativa</i> (Osativa323v7 protein file Phytozome). were filtered for the longest isomer and then analysed for orthologous and unique protein clusters within the O. australiensis genome using OrthoVenn3 (parameters: OrthoFinder algorithm, E-value: 1e-2, Inflation value:1.50) (Sun et al., 2023, Emms and Kelly, 2019). …”

Image 1_MS4A7 based metabolic gene signature as a prognostic predictor in lung adenocarcinoma.jpeg by Yan Jiang (12139)

“…</p>Methods<p>A prognostic signature for LUAD was developed using the LASSO-Cox regression algorithm with RNA-seq data from 500 LUAD patients in The Cancer Genome Atlas database. …”

Image 3_MS4A7 based metabolic gene signature as a prognostic predictor in lung adenocarcinoma.jpeg by Yan Jiang (12139)

“…</p>Methods<p>A prognostic signature for LUAD was developed using the LASSO-Cox regression algorithm with RNA-seq data from 500 LUAD patients in The Cancer Genome Atlas database. …”

Image 10_MS4A7 based metabolic gene signature as a prognostic predictor in lung adenocarcinoma.jpeg by Yan Jiang (12139)

“…</p>Methods<p>A prognostic signature for LUAD was developed using the LASSO-Cox regression algorithm with RNA-seq data from 500 LUAD patients in The Cancer Genome Atlas database. …”

Image 4_MS4A7 based metabolic gene signature as a prognostic predictor in lung adenocarcinoma.jpeg by Yan Jiang (12139)

“…</p>Methods<p>A prognostic signature for LUAD was developed using the LASSO-Cox regression algorithm with RNA-seq data from 500 LUAD patients in The Cancer Genome Atlas database. …”

Image 8_MS4A7 based metabolic gene signature as a prognostic predictor in lung adenocarcinoma.jpeg by Yan Jiang (12139)

“…</p>Methods<p>A prognostic signature for LUAD was developed using the LASSO-Cox regression algorithm with RNA-seq data from 500 LUAD patients in The Cancer Genome Atlas database. …”

Image 2_MS4A7 based metabolic gene signature as a prognostic predictor in lung adenocarcinoma.jpeg by Yan Jiang (12139)

“…</p>Methods<p>A prognostic signature for LUAD was developed using the LASSO-Cox regression algorithm with RNA-seq data from 500 LUAD patients in The Cancer Genome Atlas database. …”

Image 9_MS4A7 based metabolic gene signature as a prognostic predictor in lung adenocarcinoma.jpeg by Yan Jiang (12139)

“…</p>Methods<p>A prognostic signature for LUAD was developed using the LASSO-Cox regression algorithm with RNA-seq data from 500 LUAD patients in The Cancer Genome Atlas database. …”

Image 6_MS4A7 based metabolic gene signature as a prognostic predictor in lung adenocarcinoma.jpeg by Yan Jiang (12139)

“…</p>Methods<p>A prognostic signature for LUAD was developed using the LASSO-Cox regression algorithm with RNA-seq data from 500 LUAD patients in The Cancer Genome Atlas database. …”

Image 7_MS4A7 based metabolic gene signature as a prognostic predictor in lung adenocarcinoma.jpeg by Yan Jiang (12139)

“…</p>Methods<p>A prognostic signature for LUAD was developed using the LASSO-Cox regression algorithm with RNA-seq data from 500 LUAD patients in The Cancer Genome Atlas database. …”

Image 5_MS4A7 based metabolic gene signature as a prognostic predictor in lung adenocarcinoma.jpeg by Yan Jiang (12139)

“…</p>Methods<p>A prognostic signature for LUAD was developed using the LASSO-Cox regression algorithm with RNA-seq data from 500 LUAD patients in The Cancer Genome Atlas database. …”

Data_Sheet_3_Potential diagnostic markers and therapeutic targets for non-alcoholic fatty liver disease and ulcerative colitis based on bioinformatics analysis and machine learning... by Zheng Luo (284622)

“…Subsequently, the Cytohubba algorithm within Cytoscape was used to identify central genes. …”

Data_Sheet_4_Potential diagnostic markers and therapeutic targets for non-alcoholic fatty liver disease and ulcerative colitis based on bioinformatics analysis and machine learning... by Zheng Luo (284622)

“…Subsequently, the Cytohubba algorithm within Cytoscape was used to identify central genes. …”

Data_Sheet_2_Potential diagnostic markers and therapeutic targets for non-alcoholic fatty liver disease and ulcerative colitis based on bioinformatics analysis and machine learning... by Zheng Luo (284622)

“…Subsequently, the Cytohubba algorithm within Cytoscape was used to identify central genes. …”

Data_Sheet_1_Potential diagnostic markers and therapeutic targets for non-alcoholic fatty liver disease and ulcerative colitis based on bioinformatics analysis and machine learning... by Zheng Luo (284622)

“…Subsequently, the Cytohubba algorithm within Cytoscape was used to identify central genes. …”