datasheet1_Graph Neural Networks for Maximum Constraint Satisfaction.pdf by Jan Tönshoff (10192709)

Table3_Comprehensive analysis of the progression mechanisms of CRPC and its inhibitor discovery based on machine learning algorithms.XLSX by Zhen Wang (72451)

“…The biological functional enrichment analysis indicated that DEGs were mainly enriched in pathways related to the cell cycle and metabolism. …”

Table2_Comprehensive analysis of the progression mechanisms of CRPC and its inhibitor discovery based on machine learning algorithms.XLSX by Zhen Wang (72451)

“…The biological functional enrichment analysis indicated that DEGs were mainly enriched in pathways related to the cell cycle and metabolism. …”

Table1_Comprehensive analysis of the progression mechanisms of CRPC and its inhibitor discovery based on machine learning algorithms.XLSX by Zhen Wang (72451)

“…The biological functional enrichment analysis indicated that DEGs were mainly enriched in pathways related to the cell cycle and metabolism. …”

DataSheet1_Comprehensive analysis of immune-related gene signature based on ssGSEA algorithms in the prognosis and immune landscape of hepatocellular carcinoma.ZIP by Liangliang Wang (580395)

“…Furthermore, Cox regression analysis revealed 49 DEGs that were associated with survival. Then, 19 DEGs were screened using the LASSO algorithm for IRGs construction and patients were classified into high- and low-risk groups. …”

Steps in the extraction of 14 coordinates from the CT slices for the curved MPR. by Linus Woitke (22783534)

“…The image is then cleaned in c) using morphological filtering with an <i>opening</i> operation to remove small-scale noise. …”

Table1_Construction of predictive model of interstitial fibrosis and tubular atrophy after kidney transplantation with machine learning algorithms.xlsx by Yu Yin (329063)

“…Necroptosis as a type of programmed death plays an important role in the development of IFTA, and in the late functional decline and even loss of grafts. In this study, 13 machine learning algorithms were used to construct IFTA diagnostic models based on necroptosis-related genes.…”

Image1_Construction of predictive model of interstitial fibrosis and tubular atrophy after kidney transplantation with machine learning algorithms.pdf by Yu Yin (329063)

“…Necroptosis as a type of programmed death plays an important role in the development of IFTA, and in the late functional decline and even loss of grafts. In this study, 13 machine learning algorithms were used to construct IFTA diagnostic models based on necroptosis-related genes.…”

Image_1_Identification of energy metabolism-related biomarkers for risk prediction of heart failure patients using random forest algorithm.TIFF by Hao Chen (5190)

“…The clustering analysis showed that HF patients could be classified into two subtypes based on the energy metabolism-related genes, and functional analyses demonstrated that the identified DEGs among two clusters were mainly involved in immune response regulating signaling pathway and lipid and atherosclerosis. ssGSEA analysis revealed that there were significant differences in the infiltration levels of immune cells between two subtypes of HF patients. …”

Table_1_Identification of energy metabolism-related biomarkers for risk prediction of heart failure patients using random forest algorithm.XLSX by Hao Chen (5190)

“…The clustering analysis showed that HF patients could be classified into two subtypes based on the energy metabolism-related genes, and functional analyses demonstrated that the identified DEGs among two clusters were mainly involved in immune response regulating signaling pathway and lipid and atherosclerosis. ssGSEA analysis revealed that there were significant differences in the infiltration levels of immune cells between two subtypes of HF patients. …”

PathOlOgics_RBCs Python Scripts.zip by Ahmed Elsafty (16943883)

“…</p><p dir="ltr">In terms of classification, a second algorithm was developed and employed to preliminary sort or group the individual cells (after excluding the overlapping cells manually) into different categories using five geometric measurements applied to the extracted contour from each binary image mask (see PathOlOgics_script_2; preliminary shape measurements). …”

Thesis-RAMIS-Figs_Slides by Felipe Santibañez-Leal (10967991)

“…Importantly, this strategy locates samples adaptively on the transition between facies which improves the performance of conventional \emph{<i>MPS</i>} algorithms. In conclusion, this work shows that preferential sampling can contribute in \emph{<i>MPS</i>} even at very small sampling regimes and, as a corollary, demonstrates that prior models (obtained form a training image) can be used effectively not only to simulate non-sensed variables of the field, but to decide where to measure next.…”

Table_6_Effect of Pyroptosis-Related Genes on the Prognosis of Breast Cancer.xlsx by Ying Zhou (25031)

“…</p>Results<p>A total of 49 PRGs were obtained from public database and 35 of them were significantly differentially expressed genes (DEGs). Cluster analysis was then performed to explore the relationship between DEGs with overall survival. …”

Table_1_Effect of Pyroptosis-Related Genes on the Prognosis of Breast Cancer.xlsx by Ying Zhou (25031)

“…</p>Results<p>A total of 49 PRGs were obtained from public database and 35 of them were significantly differentially expressed genes (DEGs). Cluster analysis was then performed to explore the relationship between DEGs with overall survival. …”

Image_1_Effect of Pyroptosis-Related Genes on the Prognosis of Breast Cancer.tif by Ying Zhou (25031)

“…</p>Results<p>A total of 49 PRGs were obtained from public database and 35 of them were significantly differentially expressed genes (DEGs). Cluster analysis was then performed to explore the relationship between DEGs with overall survival. …”

Table_2_Effect of Pyroptosis-Related Genes on the Prognosis of Breast Cancer.xlsx by Ying Zhou (25031)

“…</p>Results<p>A total of 49 PRGs were obtained from public database and 35 of them were significantly differentially expressed genes (DEGs). Cluster analysis was then performed to explore the relationship between DEGs with overall survival. …”

Table_4_Effect of Pyroptosis-Related Genes on the Prognosis of Breast Cancer.xlsx by Ying Zhou (25031)

“…</p>Results<p>A total of 49 PRGs were obtained from public database and 35 of them were significantly differentially expressed genes (DEGs). Cluster analysis was then performed to explore the relationship between DEGs with overall survival. …”

Table_5_Effect of Pyroptosis-Related Genes on the Prognosis of Breast Cancer.xlsx by Ying Zhou (25031)

“…</p>Results<p>A total of 49 PRGs were obtained from public database and 35 of them were significantly differentially expressed genes (DEGs). Cluster analysis was then performed to explore the relationship between DEGs with overall survival. …”

Table_3_Effect of Pyroptosis-Related Genes on the Prognosis of Breast Cancer.xlsx by Ying Zhou (25031)

“…</p>Results<p>A total of 49 PRGs were obtained from public database and 35 of them were significantly differentially expressed genes (DEGs). Cluster analysis was then performed to explore the relationship between DEGs with overall survival. …”

Image1_Construction of a Support Vector Machine–Based Classifier for Pulmonary Arterial Hypertension Patients.tif by Zhenglu Shang (11739470)

“…Then 110 differentially expressed genes (DEGs) were obtained. Afterward, the PPI network based on DEGs was constructed, followed by the analysis of functional modules, whose results showed that the genes in the major function modules significantly enriched in immune-related functions. …”