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VUScope: a mathematical model for evaluating image-based drug response measurements and predicting long-term incubation outcomes
<h4>Motivation</h4>Live-cell imaging-based drug screening increases the likelihood of identifying effective and safe drugs by providing dynamic, high-content, and physiologically relevant data. As a result, it improves the success rate of drug development and facilitates the …
Read PDFShared molecular features and candidate pathways underlying gastric cancer-depression comorbidity: a systems biology analysis
The bidirectional association between gastric cancer (GC) and depression remains incompletely elucidated. This investigation examines the genetic and molecular correlations between GC and depression through bioinformatics and experimental approaches. Utilizing Gene Expression Omnibus (RRID: SCR_005012), …
Read PDF<i>PSMD6</i> as a biomarker for hepatocellular carcinoma: A comprehensive bioinformatics analysis and <i>in vitro</i> validation
Hepatocellular carcinoma (HCC) is a lethal malignancy with limited diagnostic biomarkers. The present study aims to comprehensively investigate the expression, clinical prognostic significance, and potential mechanisms of PSMD6 in HCC through comprehensive bioinformatics analyses and …
Read PDFLATS2 expression differences in lung adenocarcinoma and lung squamous cell carcinoma analyzed using bioinformatics and experimental approaches
The present study aimed to investigate the role and expression of large tumor suppressor kinase 2 (LATS2) in lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC). The expression levels of LATS2 in LUAD and …
Read PDFMolViewStories: Interactive molecular storytelling
Effectively communicating knowledge related to molecular structures and their associated data remains a challenge, as traditional static figures limit interactivity and professional visualization tools often require substantial expertise. MolViewStories addresses these limitations by providing an …
Read PDFSeqHIVE: a Python package to convert the biological sequences to informative vectors for sequence property predictions
Sequence-based analysis and prediction form a cornerstone of bioinformatics investigations of the sequence-structure-function paradigm across DNA, RNA, and proteins. The exponential growth in sequence data necessitates sequence encoding methods and advanced predictive models. This study …
Read PDFCorrection: Computational discovery of SARS-CoV-2 viral entry inhibitory peptides from <i>Androctonus mauretanicus</i> scorpion venom: molecular docking and molecular dynamics simulations targeting the spike protein
[This corrects the article DOI: 10.3389/fbinf.2026.1677524.].
Read PDFDeepCE: a deep learning framework for correlation-enhanced gene regulatory network inference in single-cell RNA sequencing data
<h4>Motivation</h4>Single-cell RNA sequencing has substantially advanced our understanding of gene expression dynamics and cellular heterogeneity. In recent years, deep learning (DL) has emerged as a promising approach to infer genetic regulation. However, these methods still …
Read PDFAnalysis of core target genes of vagus nerve stimulation in epilepsy, ischemic stroke, and depression: Separate insights from network pharmacology, bioinformatics, and Mendelian randomization
Epilepsy, ischemic stroke, and depression, as common neurological diseases, pose a serious threat to human health. Although vagus nerve stimulation (VNS) has been applied in the treatment of these diseases, its exact mechanism of action …
Read PDFZNF473 as a biomarker and potential therapeutic target in cancer: integrated bioinformatics and experimental evidence with a focus on hepatocellular carcinoma
<h4>Objective</h4>Zinc finger protein 473 (ZNF473) has been implicated as a regulatory factor in several cancer types; however, its precise biological functions and underlying mechanisms remain incompletely defined. This study aimed to evaluate the biological and …
Read PDFInvestigating the association of NBN gene polymorphisms with multiple cancers through statistical meta-analysis and bioinformatics insights
Several individual genetic association studies, including meta-analyses, have investigated the association of two SNPs (rs1805794 and rs709816) of NBN gene with multiple cancer risks. However, their findings were inconsistent, making it challenging to use NBN …
Read PDFUnveiling the therapeutic potential of gut microbiota metabolites for the treatment of renal fibrosis based on network pharmacology study
<h4>Background</h4>Renal fibrosis is a progressive injury contributing to renal function deterioration. Mounting evidence has underscored the profound impact of gut microbiota metabolites on host health and disease, yet their underlying mechanisms against renal fibrosis remain …
Read PDFRISK: a next-generation tool for biological network annotation and visualization
<h4>Summary</h4>Analyzing biological networks demands scalable annotation tools, yet existing methods fall short in clustering power, statistical flexibility, and broad data compatibility. We introduce Regional Inference of Significant Kinships (RISK), a next-generation tool that overcomes these …
Read PDFClustering methods for categorical time series and sequences : a scoping review
<h4>Objective</h4>To provide an overview of clustering methods for categorical time series (CTS), a data structure common in epidemiology, sociology, biology, and marketing, and to support method selection according to data characteristics.<h4>Materials and methods</h4>We searched PubMed …
Read PDFLiquid Biopsy in Cancer: The Importance of Integrating Bioinformatics Approaches Towards the Development of a Personalized Molecular Profile
Liquid biopsy is now a valuable complementary tool that oncologists use to obtain a more complete picture of their patients' condition in real time [...].
Read PDFA deep learning framework for comprehensive prediction of human RNA G-quadruplex-binding proteins
<h4>Motivation</h4>G-quadruplex-binding proteins (G4BPs) play key roles in RNA metabolism and stress response, yet their identification remains experimentally challenging. Here, we present a deep learning (DL) framework for the prediction of RNA G4BPs (RG4BPs), integrating diverse …
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