From: Using published pathway figures in enrichment analysis and machine learning
Rank | Pathway | Ref | Top Gene | Importance Score | CV Accuracy | Prediction Accuracy | Specificity | Sensitivity | F1 |
---|---|---|---|---|---|---|---|---|---|
1 | PMC2937358__F1 | CXCL6 | 0.61 | 0.72 | 0.72 | 0.61 | 0.83 | 0.69 | |
2 | PMC2653381__F1 | GSTM4 | 0.25 | 0.69 | 0.7 | 0.58 | 0.83 | 0.67 | |
3 | PMC5772637__F6 | CASP9 | 0.91 | 0.69 | 0.68 | 0.84 | 0.52 | 0.73 | |
4 | PMC5772637__F7 | CASP9 | 1.54 | 0.68 | 0.72 | 0.77 | 0.66 | 0.74 | |
5 | PMC8040471__F7 | CASP9 | 0.45 | 0.68 | 0.67 | 0.81 | 0.52 | 0.71 | |
6 | PMC6759650__F5 | CYCS | 0.37 | 0.67 | 0.78 | 0.71 | 0.86 | 0.77 | |
7 | PMC7811378__F9 | CASP9 | 0.85 | 0.67 | 0.78 | 0.84 | 0.72 | 0.8 | |
8 | PMC5715135__F7 | CASP9 | 0.15 | 0.67 | 0.75 | 0.84 | 0.66 | 0.78 | |
9 | PMC2673236__F1 | ACSM3 | 1.32 | 0.67 | 0.72 | 0.74 | 0.69 | 0.73 | |
10 | PMC387764__F8 | CASP9 | 1.78 | 0.67 | 0.68 | 0.74 | 0.62 | 0.71 | |
11 | PMC6947643__F2 | HEY1 | 1.23 | 0.67 | 0.67 | 0.84 | 0.48 | 0.72 | |
12 | PMC7409684__F1 | WNT11 | 0.18 | 0.67 | 0.67 | 0.68 | 0.66 | 0.68 | |
13 | PMC8023395__F2 | EGFR | 0.17 | 0.66 | 0.73 | 0.84 | 0.62 | 0.76 | |
14 | PMC4336604__F9 | MAPK9 | 0.33 | 0.66 | 0.72 | 0.74 | 0.69 | 0.73 | |
15 | PMC6499473__F1 | PARP1 | 0.23 | 0.66 | 0.72 | 0.61 | 0.83 | 0.69 | |
16 | PMC3219187__F5 | ZBTB7A | 2.29 | 0.66 | 0.7 | 0.81 | 0.59 | 0.74 | |
17 | PMC6024909__F4 | CDK1 | 0.26 | 0.66 | 0.7 | 0.52 | 0.9 | 0.64 | |
18 | PMC2694962__F1 | ACSM3 | 1.52 | 0.66 | 0.68 | 0.48 | 0.9 | 0.61 | |
19 | PMC5256616__F6 | CASP9 | 0.36 | 0.66 | 0.68 | 0.48 | 0.9 | 0.61 | |
20 | PMC4407294__F2 | NOTCH2 | 0.7 | 0.66 | 0.67 | 0.52 | 0.83 | 0.62 | |
21 | PMC6305585__F2 | CPEB1 | 0.77 | 0.66 | 0.67 | 0.71 | 0.62 | 0.69 | |
63 | R-HSA-8864260 | [86] | HSPD1 | 0.25 | 0.64 | 0.68 | 0.81 | 0.55 | 0.72 |
115 | KEGG_hsa01522 | [87] | BAX | 0.11 | 0.62 | 0.85 | 0.9 | 0.79 | 0.86 |