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BACKGROUND: The nectin cell adhesion molecule 4 (NECTIN4) has been implicated in tumor progression and immune evasion, yet its role and translational targeted imaging potential in lung cancer remain unclear. Therefore, this study aims to …
Read PDFWe aim to highlight problems with the biological interpretation of computationally-derived hypoxia signatures for neuro-oncology research. By reviewing important experimental work in the field, we discuss common misinterpretations of the concepts of normoxia and hypoxia. …
Read PDF<h4>Background</h4>Endometriosis (EMs) is a chronic inflammatory disease characterized by ectopic endometrial growth. This study aimed to identify and analyze potential signatures of pyroptosis-related genes in EMs.<h4>Methods</h4>We conducted a comprehensive bioinformatics analysis using transcriptomic datasets from …
Read PDF<h4>Background</h4>Gastric cancer (GC) is the fourth most common cause of death among cancers in the world, and the most prevalent type of GC is adenocarcinoma. The Cancer Genome Atlas (TCGA) project introduced 4 molecular subtypes …
Read PDF<h4>Motivation</h4>Single-cell heterogeneity analysis faces significant challenges due to the high dimensionality, complexity, and noise inherent in scRNA-seq data, especially when aiming for precise cell type classification. Existing analytical methods often exhibit limited generalization ability and …
Read PDF<h4>Objective</h4>To investigate the link between UVB-induced skin photodamage and cuproptosis, and identify key regulatory genes.<h4>Methods</h4>Transcriptomic data from UVB-irradiated human skin (GSE41078) were obtained from GEO. Differentially expressed genes (DEGs) were identified, followed by GO and …
Read PDFBACKGROUND: Personalized and precision medicine aim to identify predictive biomarkers from patient-specific proteogenomic profiles and to uncover tailored therapeutic strategies by targeting deregulated proteins driving disease phenotypes. METHODS: To address these challenges, we developed MultiOmicsXplorer, …
Read PDF<h4>Motivation</h4>RNA sequencing enables the characterization of a cell's transcript isoforms in healthy and disease conditions. In the context of cancer, local transcript variability may translate to splicing-derived tumor-associated peptides recognized by the immune system. A …
Read PDFThis review explores the role of bioinformatics in identifying novel biomarkers for immune cell exhaustion (ICE), a dysfunction state in T cells during chronic infections and cancer. ICE, marked by upregulation of inhibitory receptors such …
Read PDF<h4>Objective</h4>Genome-wide association studies have identified shared genetic risk loci between schizophrenia (SCZ) and multiple sclerosis (MS), suggesting overlapping biological mechanisms despite distinct clinical presentations. Here, we aimed to characterize the biological plausibility of <i>KIF21B</i> as …
Read PDF<h4>Motivation</h4>The analysis of RNA isoforms using long-read single-cell RNA sequencing (scRNA-seq) represents a frontier in gene expression research, offering deeper insights beyond traditional gene-level analysis. However, specialized analytical methods tailored for this advanced technology remain …
Read PDF<h4>Background</h4>Allele Specific Expression analysis is an important tool for integrating genome and transcriptome data. It quantifies expression variation between the two haplotypes of a diploid individual distinguished by heterozygous sites, and is a powerful tool …
Read PDFFusion genes play crucial roles in plant biological processes but remain far less explored than their human counterparts, largely due to limited validated datasets and the absence of plant-specific prediction tools. Existing approaches often produce …
Read PDF<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 PDF<h4>Summary</h4>Accurate annotation of coding sequences and translational features within transcript models is essential for interpreting assembled transcriptomes and their functional potential. Existing open reading frame (ORF) prediction tools typically operate on transcript FASTA files and …
Read PDF<h4>Motivation</h4>Spatial transcriptomics (ST) technologies measure gene expression together with spatial locations, but each spot typically contains a mixture of cell types, posing a challenge for downstream analysis. Cell-type deconvolution aims to infer spot-wise cell-type proportions …
Read PDF<h4>Motivation</h4>Digital analysis of biological systems requires methods capable of identifying both broad and nested gene modules reflecting complex biological processes. Existing transcriptomic methods often miss compact gene sets corresponding to subprocesses in specialized cell types, …
Read PDF<h4>Motivation</h4>Spatially resolved transcriptomics (SRT) and spatially resolved proteomics (SRP) data enable the study of gene expression and protein abundances within their precise spatial and cellular contexts in tissues. Certain SRT and SRP technologies also capture …
Read PDF<h4>Motivation</h4>Despite significant advances in spatial transcriptomics, the analysis of formalin-fixed paraffin-embedded (FFPE) tissues, which constitute most clinically available samples, remains challenging. Additionally, capturing both coding and non-coding RNAs in a spatial context poses significant challenges. …
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