Image 8_Impact of ITH on PRAD patients and feasibility analysis of the positive correlation gene MYLK2 applied to PRAD treatment.png by Chuanyu Ma (6701108)

“…The ITH-score of PRAD samples was evaluated using the DEPTH algorithm. The optimal cut-off value of RiskScore was calculated based on the difference in survival curves, and PRAD patients were classified into high ITH and low ITH groups based on the optimal cut-off value. …”

Table 1_Impact of ITH on PRAD patients and feasibility analysis of the positive correlation gene MYLK2 applied to PRAD treatment.xlsx by Chuanyu Ma (6701108)

“…The ITH-score of PRAD samples was evaluated using the DEPTH algorithm. The optimal cut-off value of RiskScore was calculated based on the difference in survival curves, and PRAD patients were classified into high ITH and low ITH groups based on the optimal cut-off value. …”

Data Sheet 2_Impact of ITH on PRAD patients and feasibility analysis of the positive correlation gene MYLK2 applied to PRAD treatment.pdf by Chuanyu Ma (6701108)

“…The ITH-score of PRAD samples was evaluated using the DEPTH algorithm. The optimal cut-off value of RiskScore was calculated based on the difference in survival curves, and PRAD patients were classified into high ITH and low ITH groups based on the optimal cut-off value. …”

Image 11_Impact of ITH on PRAD patients and feasibility analysis of the positive correlation gene MYLK2 applied to PRAD treatment.png by Chuanyu Ma (6701108)

“…The ITH-score of PRAD samples was evaluated using the DEPTH algorithm. The optimal cut-off value of RiskScore was calculated based on the difference in survival curves, and PRAD patients were classified into high ITH and low ITH groups based on the optimal cut-off value. …”

Image 2_Impact of ITH on PRAD patients and feasibility analysis of the positive correlation gene MYLK2 applied to PRAD treatment.tif by Chuanyu Ma (6701108)

“…The ITH-score of PRAD samples was evaluated using the DEPTH algorithm. The optimal cut-off value of RiskScore was calculated based on the difference in survival curves, and PRAD patients were classified into high ITH and low ITH groups based on the optimal cut-off value. …”

Table 2_Impact of ITH on PRAD patients and feasibility analysis of the positive correlation gene MYLK2 applied to PRAD treatment.xlsx by Chuanyu Ma (6701108)

“…The ITH-score of PRAD samples was evaluated using the DEPTH algorithm. The optimal cut-off value of RiskScore was calculated based on the difference in survival curves, and PRAD patients were classified into high ITH and low ITH groups based on the optimal cut-off value. …”

Image 6_Impact of ITH on PRAD patients and feasibility analysis of the positive correlation gene MYLK2 applied to PRAD treatment.jpeg by Chuanyu Ma (6701108)

“…The ITH-score of PRAD samples was evaluated using the DEPTH algorithm. The optimal cut-off value of RiskScore was calculated based on the difference in survival curves, and PRAD patients were classified into high ITH and low ITH groups based on the optimal cut-off value. …”

Data Sheet 1_Impact of ITH on PRAD patients and feasibility analysis of the positive correlation gene MYLK2 applied to PRAD treatment.pdf by Chuanyu Ma (6701108)

“…The ITH-score of PRAD samples was evaluated using the DEPTH algorithm. The optimal cut-off value of RiskScore was calculated based on the difference in survival curves, and PRAD patients were classified into high ITH and low ITH groups based on the optimal cut-off value. …”

Image 5_Impact of ITH on PRAD patients and feasibility analysis of the positive correlation gene MYLK2 applied to PRAD treatment.jpeg by Chuanyu Ma (6701108)

“…The ITH-score of PRAD samples was evaluated using the DEPTH algorithm. The optimal cut-off value of RiskScore was calculated based on the difference in survival curves, and PRAD patients were classified into high ITH and low ITH groups based on the optimal cut-off value. …”

Image 4_Impact of ITH on PRAD patients and feasibility analysis of the positive correlation gene MYLK2 applied to PRAD treatment.tif by Chuanyu Ma (6701108)

“…The ITH-score of PRAD samples was evaluated using the DEPTH algorithm. The optimal cut-off value of RiskScore was calculated based on the difference in survival curves, and PRAD patients were classified into high ITH and low ITH groups based on the optimal cut-off value. …”

Image 3_Impact of ITH on PRAD patients and feasibility analysis of the positive correlation gene MYLK2 applied to PRAD treatment.tif by Chuanyu Ma (6701108)

“…The ITH-score of PRAD samples was evaluated using the DEPTH algorithm. The optimal cut-off value of RiskScore was calculated based on the difference in survival curves, and PRAD patients were classified into high ITH and low ITH groups based on the optimal cut-off value. …”

Image 10_Impact of ITH on PRAD patients and feasibility analysis of the positive correlation gene MYLK2 applied to PRAD treatment.png by Chuanyu Ma (6701108)

“…The ITH-score of PRAD samples was evaluated using the DEPTH algorithm. The optimal cut-off value of RiskScore was calculated based on the difference in survival curves, and PRAD patients were classified into high ITH and low ITH groups based on the optimal cut-off value. …”

Image 9_Impact of ITH on PRAD patients and feasibility analysis of the positive correlation gene MYLK2 applied to PRAD treatment.png by Chuanyu Ma (6701108)

“…The ITH-score of PRAD samples was evaluated using the DEPTH algorithm. The optimal cut-off value of RiskScore was calculated based on the difference in survival curves, and PRAD patients were classified into high ITH and low ITH groups based on the optimal cut-off value. …”

Image 7_Impact of ITH on PRAD patients and feasibility analysis of the positive correlation gene MYLK2 applied to PRAD treatment.jpeg by Chuanyu Ma (6701108)

“…The ITH-score of PRAD samples was evaluated using the DEPTH algorithm. The optimal cut-off value of RiskScore was calculated based on the difference in survival curves, and PRAD patients were classified into high ITH and low ITH groups based on the optimal cut-off value. …”

Data Sheet 1_Countrywide Corchorus olitorius L. core collection shows an adaptive potential for future climate in Benin.xlsx by Dèdéou A. Tchokponhoué (17403983)

“…The spatial variation of the genomic diversity painted an increasing trend following the South-North ecological gradient, giving rise to four optimal genetic groups based on STRUCTURE analysis while the neighbour-joining analysis revealed three clusters. …”

Data Sheet 1_AlgaeOrtho, a bioinformatics tool for processing ortholog inference results in algae.docx by Mary-Francis LaPorte (20821568)

“…</p>Methods<p>The present study introduces AlgaeOrtho, a user-friendly tool that builds upon the SonicParanoid orthology inference tool (based on an algorithm that identifies potential protein orthologs based on amino acid sequences) and the PhycoCosm database from JGI (Joint Genome Institute) to help researchers identify orthologs of their proteins of interest in multiple diverse algal species.…”

Data Sheet 2_Countrywide Corchorus olitorius L. core collection shows an adaptive potential for future climate in Benin.docx by Dèdéou A. Tchokponhoué (17403983)

“…The spatial variation of the genomic diversity painted an increasing trend following the South-North ecological gradient, giving rise to four optimal genetic groups based on STRUCTURE analysis while the neighbour-joining analysis revealed three clusters. …”

<b>Assessing human and environmental impacts on forest coverage in historical relic sites using XGBoost</b> by Jinlong Chen (20554607)

“…XGBoost is an ensemble learning algorithm based on gradient boosting, designed to improve predictive accuracy and model generalization. …”

DataSheet1_Fast and precise dose estimation for very high energy electron radiotherapy with graph neural networks.PDF by Lorenzo Arsini (15083796)

“…This speed could enable direct integration into treatment planning optimization algorithms and leverage the model’s differentiability for exact gradient computation.…”

Data Sheet 1_Predicting immunotherapy response in stage III-IV non-small cell lung cancer using integrated radiomics and clinical features.docx by Na Geng (1927648)

“…Radiomic features were extracted from contrast-enhanced chest CT images, and LASSO algorithm along with Pearson correlation coefficients were applied to select optimal features and calculate a radiomics score. …”