Supplementary Tables from SpatialDeX Is a Reference-Free Method for Cell-Type Deconvolution of Spatial Transcriptomics Data in Solid Tumors by Xinyi Liu (20493753)

Functional enrichment analyses of Co-genes. by Qingcong Zheng (11169094)

Supplementary Figure S2 from SpatialDeX Is a Reference-Free Method for Cell-Type Deconvolution of Spatial Transcriptomics Data in Solid Tumors by Xinyi Liu (20493753)

Supplementary Figure S7 from SpatialDeX Is a Reference-Free Method for Cell-Type Deconvolution of Spatial Transcriptomics Data in Solid Tumors by Xinyi Liu (20493753)

Supplementary Figure S6 from SpatialDeX Is a Reference-Free Method for Cell-Type Deconvolution of Spatial Transcriptomics Data in Solid Tumors by Xinyi Liu (20493753)

Supplementary Figure S5 from SpatialDeX Is a Reference-Free Method for Cell-Type Deconvolution of Spatial Transcriptomics Data in Solid Tumors by Xinyi Liu (20493753)

Supplementary Figure S8 from SpatialDeX Is a Reference-Free Method for Cell-Type Deconvolution of Spatial Transcriptomics Data in Solid Tumors by Xinyi Liu (20493753)

Supplementary Figure S1 from SpatialDeX Is a Reference-Free Method for Cell-Type Deconvolution of Spatial Transcriptomics Data in Solid Tumors by Xinyi Liu (20493753)

Supplementary Figure S4 from SpatialDeX Is a Reference-Free Method for Cell-Type Deconvolution of Spatial Transcriptomics Data in Solid Tumors by Xinyi Liu (20493753)

Supplementary Figure S9 from SpatialDeX Is a Reference-Free Method for Cell-Type Deconvolution of Spatial Transcriptomics Data in Solid Tumors by Xinyi Liu (20493753)

Supplementary Figure S3 from SpatialDeX Is a Reference-Free Method for Cell-Type Deconvolution of Spatial Transcriptomics Data in Solid Tumors by Xinyi Liu (20493753)

Trainable parameters for different algorithms. by Anwar Hossain Efat (19942283)

Assessing the predictive performance of cell counts in spots (Cell2Spatial vs. CytoSPACE). by Huamei Li (8815955)

Subjects: “…Cell Biology…”

Core genes were selected through PPI analysis based on three algorithms. by Dong-Hee Han (140305)

“…<p>Among 46 DEGs whose expression significantly changed in A549 and BEAS-2B cell lines, the core genes were selected using three algorithms: MCC, MNC, and DEGREE. …”

Connectivity of dysregulated proteins in SCA1 cells. by Aimilia-Christina Vagiona (17584758)

The fitness score results of CEC2020 functions. by Sarah A. Alzakari (19704611)

Subjects:

Functional enrichment and correlation analysis of hub DE-SRGs. by Xihao Shen (20347942)

Subjects: “…Cell Biology…”

Python code for a rule-based NLP model for mapping circular economy indicators to SDGs by Zahir Barahmand (18008947)

“…The package includes:</p><ul><li>The complete Python codebase implementing the classification algorithm</li><li>A detailed manual outlining model features, requirements, and usage instructions</li><li>Sample input CSV files and corresponding processed output files to demonstrate functionality</li><li>Keyword dictionaries for all 17 SDGs, distinguishing strong and weak matches</li></ul><p dir="ltr">These materials enable full reproducibility of the study, facilitate adaptation for related research, and offer transparency in the methodological framework.…”

Example of how the Resnet34UNet model functions. by Henrik Mustonen (20378529)

The actual training effect of four algorithms on original photo data (All images are original images taken by the author). by Xiaojun Wang (50332)

Subjects: “…Cell Biology…”