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

"…Regulatory network reconstruction identified 32 transcription factors, 24 RNA-binding proteins, and 62 miRNAs as putative upstream regulators of key genes. …"

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

"…Regulatory network reconstruction identified 32 transcription factors, 24 RNA-binding proteins, and 62 miRNAs as putative upstream regulators of key genes. …"

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

"…Regulatory network reconstruction identified 32 transcription factors, 24 RNA-binding proteins, and 62 miRNAs as putative upstream regulators of key genes. …"

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

"…Regulatory network reconstruction identified 32 transcription factors, 24 RNA-binding proteins, and 62 miRNAs as putative upstream regulators of key genes. …"

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

"…Regulatory network reconstruction identified 32 transcription factors, 24 RNA-binding proteins, and 62 miRNAs as putative upstream regulators of key genes. …"

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

"…Regulatory network reconstruction identified 32 transcription factors, 24 RNA-binding proteins, and 62 miRNAs as putative upstream regulators of key genes. …"

Analysis of HK2-<i>SOX10</i> mRNA interaction. حسب Ana Luisa Dian (22258504)

PPI network and identification of hub genes. حسب Jun Li (6494)

Average trace of each ROI cluster at maximum silhouette score. حسب Virgil Christian Garcia Castillo (19688355)

Data in the identification of poly I:C interacted proteins and their regulation in transcription level against bacterial infection in zebrafish. حسب Huiyin Lin (21805064)

"…Therefore, these poly I:C-bound proteins cover many aspects of cell activities. We further analyzed the predicted PPI network of these poly I:C-bound proteins using STRING software and then clustered them using the MCL algorithm. …"

Table 1_Overlapping genes connect rheumatoid arthritis and head and neck cancer: coincidence or shared immune pathophysiology?.xlsx حسب Ran Wang (169166)

"…Overlapping genes were analyzed through protein–protein interaction (PPI) networks, functional annotation, and literature-based pathway analyses to elucidate common and distinct mechanisms.…"

Table 3_Successful prediction of LC8 binding to intrinsically disordered proteins sheds light on AlphaFold’s black box.xlsx حسب Douglas R. Walker (3664039)

"…This cutoff, along with a more inclusive cutoff, was used to predict elusive LC8 binding sites in proteins known to bind LC8.</p>Discussion<p>Correlations between binding affinities and AlphaFold scores provide insight into the black box and indicate that AlphaFold learned an inaccurate energy function that nevertheless is useful for making inferences and conclusions about physical systems. …"

Image 1_Successful prediction of LC8 binding to intrinsically disordered proteins sheds light on AlphaFold’s black box.png حسب Douglas R. Walker (3664039)

"…This cutoff, along with a more inclusive cutoff, was used to predict elusive LC8 binding sites in proteins known to bind LC8.</p>Discussion<p>Correlations between binding affinities and AlphaFold scores provide insight into the black box and indicate that AlphaFold learned an inaccurate energy function that nevertheless is useful for making inferences and conclusions about physical systems. …"

Supplementary file 1_Successful prediction of LC8 binding to intrinsically disordered proteins sheds light on AlphaFold’s black box.docx حسب Douglas R. Walker (3664039)

"…This cutoff, along with a more inclusive cutoff, was used to predict elusive LC8 binding sites in proteins known to bind LC8.</p>Discussion<p>Correlations between binding affinities and AlphaFold scores provide insight into the black box and indicate that AlphaFold learned an inaccurate energy function that nevertheless is useful for making inferences and conclusions about physical systems. …"

Table 9_Successful prediction of LC8 binding to intrinsically disordered proteins sheds light on AlphaFold’s black box.xlsx حسب Douglas R. Walker (3664039)

"…This cutoff, along with a more inclusive cutoff, was used to predict elusive LC8 binding sites in proteins known to bind LC8.</p>Discussion<p>Correlations between binding affinities and AlphaFold scores provide insight into the black box and indicate that AlphaFold learned an inaccurate energy function that nevertheless is useful for making inferences and conclusions about physical systems. …"

Data Sheet 1_Successful prediction of LC8 binding to intrinsically disordered proteins sheds light on AlphaFold’s black box.csv حسب Douglas R. Walker (3664039)

"…This cutoff, along with a more inclusive cutoff, was used to predict elusive LC8 binding sites in proteins known to bind LC8.</p>Discussion<p>Correlations between binding affinities and AlphaFold scores provide insight into the black box and indicate that AlphaFold learned an inaccurate energy function that nevertheless is useful for making inferences and conclusions about physical systems. …"

Table 11_Successful prediction of LC8 binding to intrinsically disordered proteins sheds light on AlphaFold’s black box.xlsx حسب Douglas R. Walker (3664039)

"…This cutoff, along with a more inclusive cutoff, was used to predict elusive LC8 binding sites in proteins known to bind LC8.</p>Discussion<p>Correlations between binding affinities and AlphaFold scores provide insight into the black box and indicate that AlphaFold learned an inaccurate energy function that nevertheless is useful for making inferences and conclusions about physical systems. …"

Data Sheet 5_Successful prediction of LC8 binding to intrinsically disordered proteins sheds light on AlphaFold’s black box.csv حسب Douglas R. Walker (3664039)

"…This cutoff, along with a more inclusive cutoff, was used to predict elusive LC8 binding sites in proteins known to bind LC8.</p>Discussion<p>Correlations between binding affinities and AlphaFold scores provide insight into the black box and indicate that AlphaFold learned an inaccurate energy function that nevertheless is useful for making inferences and conclusions about physical systems. …"

Presentation 3_Successful prediction of LC8 binding to intrinsically disordered proteins sheds light on AlphaFold’s black box.pptx حسب Douglas R. Walker (3664039)

"…This cutoff, along with a more inclusive cutoff, was used to predict elusive LC8 binding sites in proteins known to bind LC8.</p>Discussion<p>Correlations between binding affinities and AlphaFold scores provide insight into the black box and indicate that AlphaFold learned an inaccurate energy function that nevertheless is useful for making inferences and conclusions about physical systems. …"

Data Sheet 11_Successful prediction of LC8 binding to intrinsically disordered proteins sheds light on AlphaFold’s black box.csv حسب Douglas R. Walker (3664039)

"…This cutoff, along with a more inclusive cutoff, was used to predict elusive LC8 binding sites in proteins known to bind LC8.</p>Discussion<p>Correlations between binding affinities and AlphaFold scores provide insight into the black box and indicate that AlphaFold learned an inaccurate energy function that nevertheless is useful for making inferences and conclusions about physical systems. …"