Significantly enriched Gene Ontology (GO) terms among the 512 genes showing significant results in the all ancestry TWAS. Enrichment analyses were conducted using the multi-query i... by Jenna C. Carlson (3950024)

Patch-level landscape metrics derived using the <i>HabSpace</i> function of <i>HabplanR</i> for the entire 35 three-year projection period, across two possible Habplan solutions. by Max D. Jones (6269006)

Table 1_Comprehensive analysis of anoikis-related gene signature in ulcerative colitis using machine learning algorithms.xlsx by Peng Liu (120506)

“…Subsequently, Single sample GSEA (ssGSEA) was executed to explore the relationships within immune cell infiltration, UC subtypes, and key anoikis-DEGs. …”

Image 1_Comprehensive analysis of anoikis-related gene signature in ulcerative colitis using machine learning algorithms.tiff by Peng Liu (120506)

“…Subsequently, Single sample GSEA (ssGSEA) was executed to explore the relationships within immune cell infiltration, UC subtypes, and key anoikis-DEGs. …”

Image 4_Comprehensive analysis of anoikis-related gene signature in ulcerative colitis using machine learning algorithms.tiff by Peng Liu (120506)

“…Subsequently, Single sample GSEA (ssGSEA) was executed to explore the relationships within immune cell infiltration, UC subtypes, and key anoikis-DEGs. …”

Image 5_Comprehensive analysis of anoikis-related gene signature in ulcerative colitis using machine learning algorithms.tiff by Peng Liu (120506)

“…Subsequently, Single sample GSEA (ssGSEA) was executed to explore the relationships within immune cell infiltration, UC subtypes, and key anoikis-DEGs. …”

Image 3_Comprehensive analysis of anoikis-related gene signature in ulcerative colitis using machine learning algorithms.tiff by Peng Liu (120506)

“…Subsequently, Single sample GSEA (ssGSEA) was executed to explore the relationships within immune cell infiltration, UC subtypes, and key anoikis-DEGs. …”

Image 2_Comprehensive analysis of anoikis-related gene signature in ulcerative colitis using machine learning algorithms.tiff by Peng Liu (120506)

“…Subsequently, Single sample GSEA (ssGSEA) was executed to explore the relationships within immune cell infiltration, UC subtypes, and key anoikis-DEGs. …”

Single-cell RNA sequencing analysis reveals the expression patterns of the prognostic signature across cellular subpopulations. by Xiangxin Wu (22320058)

(a): Sample statistical graphs of different types of defects. by Yazhou Li (277980)

Longitudinal trajectories of functional network development across the birth transition. by Lanxin Ji (20290942)

“…<p><b> </b> (A) One-sample <i>t</i> test on RSFC across all subjects. Stronger RSFC within networks affirms validity of the network clustering algorithm. …”

Multiple sequence alignment of <i>Ov</i>-RAL-2 Glutamine-repeat epitope (GRR) showing identical sequence stretches common to some human proteins. by Derrick Neba Nebangwa (19923731)

Visualization of the image segmentation and labeling pipeline for the first frame of an example movie. by Miriam Schnitzerlein (21446136)

Model performance over epochs. by Ayesha Khalid (7843483)

“…These findings underscore the effectiveness of the ESM-2 model in accurately predicting <i>O-</i>GlcNAc sites within human proteins. Accurately predicting <i>O</i>-GlcNAc sites within human proteins can significantly advance glycoproteomic research by enhancing our understanding of protein function and disease mechanisms, aiding in developing targeted therapies, and facilitating biomarker discovery for improved diagnosis and treatment. …”

Evaluation metrics on test data. by Ayesha Khalid (7843483)

“…These findings underscore the effectiveness of the ESM-2 model in accurately predicting <i>O-</i>GlcNAc sites within human proteins. Accurately predicting <i>O</i>-GlcNAc sites within human proteins can significantly advance glycoproteomic research by enhancing our understanding of protein function and disease mechanisms, aiding in developing targeted therapies, and facilitating biomarker discovery for improved diagnosis and treatment. …”

Comparison with baseline clustering techniques. by Sayantan Kumar (20208872)

Table 1_Analysis and validation of characteristic genes in RNA sequencing datasets from heart failure patients based on multiple algorithms.docx by Yuxuan Li (1674307)

Image 1_Analysis and validation of characteristic genes in RNA sequencing datasets from heart failure patients based on multiple algorithms.tif by Yuxuan Li (1674307)

Data Sheet 2_Machine learning integrates region-specific microbial signatures to distinguish geographically adjacent populations within a province.xlsx by Li Luo (149019)

“…To obtain the optimal model that can distinguish geographically close populations, three machine learning (ML) algorithms based on microbiota or functions were employed.…”

Data Sheet 1_Machine learning integrates region-specific microbial signatures to distinguish geographically adjacent populations within a province.docx by Li Luo (149019)

“…To obtain the optimal model that can distinguish geographically close populations, three machine learning (ML) algorithms based on microbiota or functions were employed.…”