Table 2_OFGPMA: Optimal frequency graph representation learning for pseudogene and miRNA association prediction.docx

Table 2_OFGPMA: Optimal frequency graph representation learning for pseudogene and miRNA association prediction.docx

<p>Pseudogenes are genomic segments that resemble functional genes structurally yet remain biologically inactive. MicroRNAs (miRNAs), a subclass of non-coding RNAs, are critical regulators of various cellular mechanisms. These pseudogenes and miRNAs interact mutually, forming competitive endog...

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Príomhchruthaitheoir:	Yongbin Zeng (529358) (author)
Rannpháirtithe:	Lixiang Xiong (20280585) (author), Yungui Luo (22684343) (author)
Foilsithe / Cruthaithe:	2025
Ábhair:	Genetics optimal frequency graph global random walk with restart local enclosing subgraph graph representation learning pseudogene and miRNA association prediction
Clibeanna:	Cuir clib leis Níl clibeanna ann, Bí ar an gcéad duine le clib a chur leis an taifead seo!

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Table 1_OFGPMA: Optimal frequency graph representation learning for pseudogene and miRNA association prediction.xlsx
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Diversity of augmented graphs.
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Structural and node-level augmentations for graph anomalies.
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Anomaly detection performance (AUROC).
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Abbreviations and notation.
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Anomalies in attributed networks.
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Case study on Esophageal Squamous Cell Carcinoma (ESCC).
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Simulation networks and gene expression analysis across disease states.
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Robustness analysis of the entropic regularization parameter in the Gromov–Wasserstein alignment step of TransMarker.
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Robustness of TransMarker concerning the selection and completeness of the prior knowledge network.
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UpSet diagram illustrating the overlap of DNBs selected by our method and top-ranked genes by the 13 baseline centrality-based ranking algorithms.
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Functional enrichment analysis of the 28 DNB genes identified for ESCC.
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Functional enrichment analysis of the DNBs identified for GAC.
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Mean expression levels of biomarker genes across various disease states.
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Gene regulatory networks for different states of GAC post-rewiring.
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UMAP visualizations of extracted CD8<sup> + </sup> T and CD4<sup> + </sup> T cell barcodes, employed for downstream subsequent single-cell trajectory and classification analyses.
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Individual memory performance was predicted by a subset of iEEG signal components.
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Short periods of increased connectivity between ROIs are characterized by a sparse overall network state.
de réir: Adam J. O. Dede (11554007)
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Patterns of connectivity were different depending on time alignment.
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Patterns of mnemonic differences in phase clustering are dependent on time alignment.
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High-frequency broadband (HFB) peak latency timing changes with memory.
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Task and channel coverage.
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