Bioinformatics and Genomic Networks

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Deciphering the functional architecture of the transcriptome is essential for understanding molecular regulation and biological complexity, particularly in non-model plant species. Most transcriptomic studies rely primarily on expression-level comparisons, which may overlook higher-order functional organization. Here,…

Abstract Background and Objective Variational Autoencoders (VAEs) offer a powerful framework for unsupervised anomaly detection and data clustering, often surpassing traditional methods. A core strength of VAEs lies in their ability to model data distributions probabilistically, enabling robust identification of anoma…

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Cohort-wide pathway correlations can hide strong relationships that differ across tumor states. We asked whether this occurs in TNBC/basal-like breast cancer by ordering tumors on prespecified Hallmark pathway axes and comparing pathway correlations in fixed low and high states under complete-family error control. The…

• VarXOmics is an integrated and versatile web server for genomic data querying, variant analysis, and prioritization. • It consolidates multi-omics datasets of eQTL, pQTL, GWAS, MR, and pharmacogenomics information to provide holistic insights into the diverse effects of genetic variation. • It facilitates the identi…

Abstract Somatic mutations can alter normal cells and lead to cancer development. Yet distinguishing functional driver mutations from neutral passenger mutations remains a significant challenge. Traditional genomic tools often prioritize linear overlap searches, failing to capture the complex, three-dimensional regula…

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Abstract Background A vast majority of somatic mutations in cancer reside in non-coding regions, yet systematically predicting their functional impact on gene regulation remains a significant challenge. These variants often enforce their effects by altering the binding affinity of transcription factors (TFs) to cis-re…

e20716 Background: Non-small cell lung cancer (NSCLC) in non-smoking women represents a biologically distinct subgroup in which actionable therapeutic targets can be identified and may also have broader relevance across diverse NSCLC subgroups. This study aimed to identify hub genes from tumor-normal transcriptomics a…

Purpose: Breast cancer (BC) is a highly heterogeneous malignancy, and current treatments often suffer from toxicity, limited selectivity, and high cost. This study aimed to integrate transcriptome-level data, multi-layered network analysis, and drug repositioning strategies to identify candidate diagnostic and prognos…