بدائل البحث:
algorithm protein » algorithm pre (توسيع البحث)
algorithm python » algorithms within (توسيع البحث), algorithm both (توسيع البحث)
algorithm protein » algorithm pre (توسيع البحث)
algorithm python » algorithms within (توسيع البحث), algorithm both (توسيع البحث)
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Profile of dysregulated proteins in SCA1 cells containing polyQ inclusions.
منشور في 2025الموضوعات: -
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Table 1_Explainable machine learning reveals ribosome biogenesis biomarkers in preeclampsia risk prediction.xlsx
منشور في 2025"…</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. …"
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Table 4_Explainable machine learning reveals ribosome biogenesis biomarkers in preeclampsia risk prediction.xlsx
منشور في 2025"…</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. …"
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Table 5_Explainable machine learning reveals ribosome biogenesis biomarkers in preeclampsia risk prediction.xlsx
منشور في 2025"…</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. …"
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Table 2_Explainable machine learning reveals ribosome biogenesis biomarkers in preeclampsia risk prediction.xlsx
منشور في 2025"…</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. …"
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Table 3_Explainable machine learning reveals ribosome biogenesis biomarkers in preeclampsia risk prediction.xlsx
منشور في 2025"…</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. …"
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Data Sheet 1_Explainable machine learning reveals ribosome biogenesis biomarkers in preeclampsia risk prediction.docx
منشور في 2025"…</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. …"
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Overview diagram of the method and contributions of this work.
منشور في 2025"…Panel B shows three tasks that can be performed with the set of HA sites. (1) The HA sites can be used to confirm the protein family alignment and validate a protein’s membership within a family based on the similarity of the progression of attention values. (2) The HA sites can define vectors that can be used to determine pairwise similarities between proteins. (3) The HA sites are also predictive of functionally important regions of the protein, as they are spatially close to active sites and residues crucial to the specificity of the protein.…"
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Flowchart of the entire pipeline.
منشور في 2024"…Finally, the iterative optimization algorithm described in Section Greedy algorithm for clustering of GO terms and in Appendix 4 is applied to the dataset, and an optimized set of functional annotations is returned.…"
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