Standard benchmark functions. حسب Yanzhao Gu (21192659)

"…The experimental results showed that GWOA achieved better convergence speed and solution accuracy than other algorithms in most test functions, especially in multimodal and compositional optimization problems, with an Overall Efficiency (OE) value of 74.46%. …"

Standard benchmark functions [42]. حسب Junhao Wei (6816803)

"…In the experimental section, we validate the efficiency and superiority of LSWOA by comparing it with outstanding metaheuristic algorithms and excellent WOA variants. The experimental results show that LSWOA exhibits significant optimization performance on the benchmark functions with various dimensions. …"

Ave and Std of different algorithms. حسب Yanzhao Gu (21192659)

"…The experimental results showed that GWOA achieved better convergence speed and solution accuracy than other algorithms in most test functions, especially in multimodal and compositional optimization problems, with an Overall Efficiency (OE) value of 74.46%. …"

Parameter settings for metaheuristic algorithm. حسب Yanzhao Gu (21192659)

"…The experimental results showed that GWOA achieved better convergence speed and solution accuracy than other algorithms in most test functions, especially in multimodal and compositional optimization problems, with an Overall Efficiency (OE) value of 74.46%. …"

F4 function and convergence curve graph. حسب Jiangli Yu (4601986)

F5 function and convergence curve graph. حسب Jiangli Yu (4601986)

F1 function and convergence curve graph. حسب Jiangli Yu (4601986)

F6 function and convergence curve graph. حسب Jiangli Yu (4601986)

F7 function and convergence curve graph. حسب Jiangli Yu (4601986)

F10 function and convergence curve graph. حسب Jiangli Yu (4601986)

F9 function and convergence curve graph. حسب Jiangli Yu (4601986)

F2 function and convergence curve graph. حسب Jiangli Yu (4601986)

F8 function and convergence curve graph. حسب Jiangli Yu (4601986)

F3 function and convergence curve graph. حسب Jiangli Yu (4601986)

Table 1_Explainable machine learning reveals ribosome biogenesis biomarkers in preeclampsia risk prediction.xlsx حسب Jingjing Chen (293564)

"…</p>Methods<p>We integrated placental transcriptomic data from two datasets (GSE75010, GSE10588) to systematically investigate ribosome biogenesis dysregulation in preeclampsia. Functional enrichment analyses delineated the dysregulation of pathways, while weighted gene co-expression network analysis identified hub genes within ribosome biogenesis-associated modules. …"

Table 4_Explainable machine learning reveals ribosome biogenesis biomarkers in preeclampsia risk prediction.xlsx حسب Jingjing Chen (293564)

"…</p>Methods<p>We integrated placental transcriptomic data from two datasets (GSE75010, GSE10588) to systematically investigate ribosome biogenesis dysregulation in preeclampsia. Functional enrichment analyses delineated the dysregulation of pathways, while weighted gene co-expression network analysis identified hub genes within ribosome biogenesis-associated modules. …"

Table 5_Explainable machine learning reveals ribosome biogenesis biomarkers in preeclampsia risk prediction.xlsx حسب Jingjing Chen (293564)

"…</p>Methods<p>We integrated placental transcriptomic data from two datasets (GSE75010, GSE10588) to systematically investigate ribosome biogenesis dysregulation in preeclampsia. Functional enrichment analyses delineated the dysregulation of pathways, while weighted gene co-expression network analysis identified hub genes within ribosome biogenesis-associated modules. …"

Table 2_Explainable machine learning reveals ribosome biogenesis biomarkers in preeclampsia risk prediction.xlsx حسب Jingjing Chen (293564)

"…</p>Methods<p>We integrated placental transcriptomic data from two datasets (GSE75010, GSE10588) to systematically investigate ribosome biogenesis dysregulation in preeclampsia. Functional enrichment analyses delineated the dysregulation of pathways, while weighted gene co-expression network analysis identified hub genes within ribosome biogenesis-associated modules. …"

Table 3_Explainable machine learning reveals ribosome biogenesis biomarkers in preeclampsia risk prediction.xlsx حسب Jingjing Chen (293564)

"…</p>Methods<p>We integrated placental transcriptomic data from two datasets (GSE75010, GSE10588) to systematically investigate ribosome biogenesis dysregulation in preeclampsia. Functional enrichment analyses delineated the dysregulation of pathways, while weighted gene co-expression network analysis identified hub genes within ribosome biogenesis-associated modules. …"

Data Sheet 1_Explainable machine learning reveals ribosome biogenesis biomarkers in preeclampsia risk prediction.docx حسب Jingjing Chen (293564)

"…</p>Methods<p>We integrated placental transcriptomic data from two datasets (GSE75010, GSE10588) to systematically investigate ribosome biogenesis dysregulation in preeclampsia. Functional enrichment analyses delineated the dysregulation of pathways, while weighted gene co-expression network analysis identified hub genes within ribosome biogenesis-associated modules. …"