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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Bibliográfalaš dieđut
Váldodahkki:	Yongbin Zeng (529358) (author)
Eará dahkkit:	Lixiang Xiong (20280585) (author), Yungui Luo (22684343) (author)
Almmustuhtton:	2025
Fáttát:	Genetics optimal frequency graph global random walk with restart local enclosing subgraph graph representation learning pseudogene and miRNA association prediction
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Table 1_OFGPMA: Optimal frequency graph representation learning for pseudogene and miRNA association prediction.xlsx
Dahkki: Yongbin Zeng (529358)
Almmustuhtton: (2025)

Data Sheet 1_MicroRNA identification and expression analysis of wheat thermo-sensitive male sterile line BNS366 for fertility transformation.zip
Dahkki: Junpeng Chen (4927267)
Almmustuhtton: (2025)

Diversity of augmented graphs.
Dahkki: Hossein Rafieizadeh (22676722)
Almmustuhtton: (2025)

Structural and node-level augmentations for graph anomalies.
Dahkki: Hossein Rafieizadeh (22676722)
Almmustuhtton: (2025)

Condensed summary of graph anomaly detection methods and their key strengths and limitations.
Dahkki: Hossein Rafieizadeh (22676722)
Almmustuhtton: (2025)

Schematic representation of key findings.
Dahkki: Adam J. O. Dede (11554007)
Almmustuhtton: (2025)

Table 1_A community-based, medical student-led walking and education program was associated with a reduction in frailty levels among adults with elevated frailty.docx
Dahkki: Myles W. O’Brien (16400379)
Almmustuhtton: (2025)

Comparison of anthropometric measurements, body composition and clinical variables among participants with low-grade MI and SLE and according to BMI status of the population.
Dahkki: Lourdes Chero-Sandoval (22683418)
Almmustuhtton: (2025)

Ablation on Amazon.
Dahkki: Hossein Rafieizadeh (22676722)
Almmustuhtton: (2025)

Anomaly detection performance (AUROC).
Dahkki: Hossein Rafieizadeh (22676722)
Almmustuhtton: (2025)

Description of the datasets statistics and their anomaly ratios.
Dahkki: Hossein Rafieizadeh (22676722)
Almmustuhtton: (2025)

Abbreviations and notation.
Dahkki: Hossein Rafieizadeh (22676722)
Almmustuhtton: (2025)

Normalized total loss on the Facebook dataset (DCOR with and without RLC).
Dahkki: Hossein Rafieizadeh (22676722)
Almmustuhtton: (2025)

Normalized training loss vs. baselines (Facebook).
Dahkki: Hossein Rafieizadeh (22676722)
Almmustuhtton: (2025)

Dual autoencoder with reconstruction-level contrast.
Dahkki: Hossein Rafieizadeh (22676722)
Almmustuhtton: (2025)

Embedding vs. reconstruction-level contrast (RLC).
Dahkki: Hossein Rafieizadeh (22676722)
Almmustuhtton: (2025)

Anomalies in attributed networks.
Dahkki: Hossein Rafieizadeh (22676722)
Almmustuhtton: (2025)

Quantitative performance comparison of our method and five multilayer network ranking baselines on the GAC dataset across multiple evaluation metrics.
Dahkki: Fatemeh Keikha (20917848)
Almmustuhtton: (2025)

Classification performance across the three simulation settings.
Dahkki: Fatemeh Keikha (20917848)
Almmustuhtton: (2025)

Comparison of Gene Discovery and Performance Evaluation with Baseline Methods.
Dahkki: Fatemeh Keikha (20917848)
Almmustuhtton: (2025)

Case study on Esophageal Squamous Cell Carcinoma (ESCC).
Dahkki: Fatemeh Keikha (20917848)
Almmustuhtton: (2025)

Ablation studies and performance evaluation under varying training conditions.
Dahkki: Fatemeh Keikha (20917848)
Almmustuhtton: (2025)

classification results on simulated datasets and biomarkers and classification results for GAC dataset.
Dahkki: Fatemeh Keikha (20917848)
Almmustuhtton: (2025)

Simulation networks and gene expression analysis across disease states.
Dahkki: Fatemeh Keikha (20917848)
Almmustuhtton: (2025)

Overview of the TransMarker framework for identifying DNBs from single cell time course data.
Dahkki: Fatemeh Keikha (20917848)
Almmustuhtton: (2025)

Robustness analysis of the entropic regularization parameter in the Gromov–Wasserstein alignment step of TransMarker.
Dahkki: Fatemeh Keikha (20917848)
Almmustuhtton: (2025)

Robustness of TransMarker concerning the selection and completeness of the prior knowledge network.
Dahkki: Fatemeh Keikha (20917848)
Almmustuhtton: (2025)

UpSet diagram illustrating the overlap of DNBs selected by our method and top-ranked genes by the 13 baseline centrality-based ranking algorithms.
Dahkki: Fatemeh Keikha (20917848)
Almmustuhtton: (2025)

Functional enrichment analysis of the 28 DNB genes identified for ESCC.
Dahkki: Fatemeh Keikha (20917848)
Almmustuhtton: (2025)

Functional enrichment analysis of the DNBs identified for GAC.
Dahkki: Fatemeh Keikha (20917848)
Almmustuhtton: (2025)

Mean expression levels of biomarker genes across various disease states.
Dahkki: Fatemeh Keikha (20917848)
Almmustuhtton: (2025)

Gene regulatory networks for different states of GAC post-rewiring.
Dahkki: Fatemeh Keikha (20917848)
Almmustuhtton: (2025)

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.
Dahkki: Fatemeh Keikha (20917848)
Almmustuhtton: (2025)

Table 1_Cross-species validation of a 6-miRNA blood signature for Parkinson’s disease: from MPTP mice to human PBMC and serum exosomes.docx
Dahkki: Nagyum Jung (22686458)
Almmustuhtton: (2025)

Individual memory performance was predicted by a subset of iEEG signal components.
Dahkki: Adam J. O. Dede (11554007)
Almmustuhtton: (2025)

Short periods of increased connectivity between ROIs are characterized by a sparse overall network state.
Dahkki: Adam J. O. Dede (11554007)
Almmustuhtton: (2025)

Patterns of connectivity were different depending on time alignment.
Dahkki: Adam J. O. Dede (11554007)
Almmustuhtton: (2025)

Patterns of mnemonic differences in phase clustering are dependent on time alignment.
Dahkki: Adam J. O. Dede (11554007)
Almmustuhtton: (2025)

High-frequency broadband (HFB) peak latency timing changes with memory.
Dahkki: Adam J. O. Dede (11554007)
Almmustuhtton: (2025)

Task and channel coverage.
Dahkki: Adam J. O. Dede (11554007)
Almmustuhtton: (2025)

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