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BACKGROUND: Diabetic nephropathy (DN) has been pathophysiologically associated with macrophage activity; however, the molecular mechanisms underlying this relationship remain unclear. This study aimed to explore the regulatory mechanisms linking DN and macrophages using integrated bioinformatics …
Read PDFBACKGROUND: Single-cell RNA sequencing (scRNA-seq) is considered a revolution in gene expression studies and offers significant benefits across various fields of biomedical or clinical applications. However, a high proportion of technical dropouts in scRNA-seq data …
Read PDFBackground: Papillary thyroid cancer is a common head and neck malignancy with a globally rising incidence. While most patients attain favorable prognosis following standard treatment, a subset develops recurrence and metastasis—two key factors that compromise …
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Read PDF<h4>Background and objective</h4>Coronary endothelial dysfunction is considered one of the key pathological components in acute myocardial infarction (AMI). This study aimed to explore the expression patterns and potential significance of the differentially expressed genes SULF1 …
Read PDF<h4>Motivation</h4>Single-cell Hi-C (scHi-C) technologies have significantly advanced our understanding of the 3D genome organization. However, scHi-C data are often sparse and noisy, leading to substantial computational challenges in downstream analyses.<h4>Results</h4>In this study, we introduce SHICEDO, …
Read PDF<h4>Summary</h4>SISTEM is a software package and mathematical framework for simulating tumor evolution and cell migrations at single-cell resolution. Unlike existing frameworks which simulate cancer cell populations under the neutral coalescent or using simple birth-death models, …
Read PDF<h4>Motivation</h4>Single-cell technologies enable high-resolution cellular studies but face challenges in identifying differential features due to data complexity.<h4>Results</h4>We present OTMODE, a non-parametric method using unbalanced Sinkhorn algorithm and Wald test to improve differential feature identification in …
Read PDF<h4>Motivation</h4>Signal transduction networks regulate many essential biological processes and are frequently aberrated in diseases such as cancer. A mechanistic understanding of such networks, and how they differ between cell populations, is essential to design effective …
Read PDF<h4>Motivation</h4>Targeted enrichment can offset the bias and depth requirements of random-primed second-strand synthesis in 3'-end RNA-seq by reallocating reads to transcripts of interest. We present PeakPrime, a reproducible Nextflow pipeline that (i) identifies high-coverage 3 …
Read PDF<h4>Motivation</h4>Single-cell RNA sequencing (scRNA-Seq) technology enables detailed exploration of gene expression at the individual cell level, crucial for annotating cell types and understanding cellular diversity. Traditional methods for cell type annotation often rely on marker …
Read PDF<h4>Summary</h4>SCODE reconstructs gene regulatory networks from single-cell RNA sequencing (scRNA-seq) data using an ordinary differential equation (ODE) model, and has been successfully applied to a wide range of scRNA-seq datasets, including mouse, human, and plant …
Read PDF<h4>Motivation</h4>In single-cell studies, a common question is whether there is a change in cell composition between conditions. While ideally, one needs absolute cell counts (number of cells per volumetric unit in a sample) to address …
Read PDF<h4>Motivation</h4>Incomplete gene models negatively impact single-cell gene expression quantification. This is particularly true in non-model species where often gene 3' ends are inaccurately annotated, while most scRNA-seq methods only capture the 3' transcript region. This …
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>Motivation</h4>Chromatin 3D folding creates numerous DNA interactions, participating in gene expression regulation. Single-cell chromatin-accessibility assays now profile hundreds of thousands of cells, challenging existing methods for mapping cis-regulatory interactions.<h4>Results</h4>We present CIRCE, a fast and scalable …
Read PDF<h4>Background</h4>Osteoarthritis has become a global health challenge due to its complex pathologic mechanisms. Spliceosome-associated factor 2 (SYF2) has been reported in tumors and neurological diseases, but not in studies of osteoarthritis. We employed single-cell sequencing …
Read PDF<h4>Motivation</h4>Large language models (LLMs) are rapidly becoming indispensable across the life‑sciences spectrum, from literature mining through clinical decision support to experimental design. Yet, in single‑cell RNA‑sequencing (scRNA‑seq) analysis, most LLM‑enabled tools remain opaque: they output …
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>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 …
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