Clustering analysis of true-negative antagonistic drug pairs based on the protein synergy scores of the genetic algorithm-selected proteins. حسب Kittisak Taoma (18017669)

Clustering analysis of true-positive synergistic drug pairs based on the protein synergy scores of the genetic algorithm-selected proteins. حسب Kittisak Taoma (18017669)

Table_6_Discriminating Origin Tissues of Tumor Cell Lines by Methylation Signatures and Dys-Methylated Rules.XLSX حسب Shiqi Zhang (709298)

Table_8_Discriminating Origin Tissues of Tumor Cell Lines by Methylation Signatures and Dys-Methylated Rules.XLSX حسب Shiqi Zhang (709298)

Table_4_Discriminating Origin Tissues of Tumor Cell Lines by Methylation Signatures and Dys-Methylated Rules.XLSX حسب Shiqi Zhang (709298)

Table_2_Discriminating Origin Tissues of Tumor Cell Lines by Methylation Signatures and Dys-Methylated Rules.XLSX حسب Shiqi Zhang (709298)

Table_3_Discriminating Origin Tissues of Tumor Cell Lines by Methylation Signatures and Dys-Methylated Rules.XLSX حسب Shiqi Zhang (709298)

Table_5_Discriminating Origin Tissues of Tumor Cell Lines by Methylation Signatures and Dys-Methylated Rules.XLSX حسب Shiqi Zhang (709298)

Table_10_Discriminating Origin Tissues of Tumor Cell Lines by Methylation Signatures and Dys-Methylated Rules.XLSX حسب Shiqi Zhang (709298)

Table_7_Discriminating Origin Tissues of Tumor Cell Lines by Methylation Signatures and Dys-Methylated Rules.XLSX حسب Shiqi Zhang (709298)

Table_9_Discriminating Origin Tissues of Tumor Cell Lines by Methylation Signatures and Dys-Methylated Rules.XLSX حسب Shiqi Zhang (709298)

Table_1_Discriminating Origin Tissues of Tumor Cell Lines by Methylation Signatures and Dys-Methylated Rules.XLSX حسب Shiqi Zhang (709298)

Area under the curve (AUC) obtained when classifying bacterial protective antigens (BPAs) from non-BPAs using a logistic regression classifier comprised of ten features from the da... حسب Ashley I. Heinson (8124374)

Accuracies obtained using a leave tenth out cross validation (LTOCV) to predict bacterial protective antigens (BPAs) or non-BPAs from the dataset BPAD200. حسب Ashley I. Heinson (8124374)

ConvGNN performance with STRING PPI on single omics and multi-omics data. حسب Yonghua Zhuang (11331069)

Convolutional Graph Neural Network performance on single omics data. حسب Yonghua Zhuang (11331069)

ConvGNN performance with COPD-associated PPI by AhGlasso. حسب Yonghua Zhuang (11331069)

Multi-omics data integration through ConvGNN for COPD prediction. حسب Yonghua Zhuang (11331069)

SIMPA’s algorithm and cross validations. حسب Steffen Albrecht (483443)

Machine Learning on Large-Scale Proteomics Data Identifies Tissue and Cell-Type Specific Proteins حسب Tine Claeys (14839428)

"…Based on protein abundance alone, the model was able to predict tissues with 98% accuracy, and cell types with 99% accuracy. …"