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1073 results

Full text 2026

Defining neurovascular ecosystem states with single-cell multi-omics and machine learning: insights into cerebrovascular remodeling in the tumor context

Kong D, Chen Y, Wang W, et al.

<h4>Objective</h4>To define neurovascular ecosystem states within the tumor microenvironment and elucidate the regulatory basis of cerebrovascular remodeling through single-cell multi-omics and interpretable machine learning.<h4>Methods</h4>An orthotopic murine brain tumor model was established. Single-cell RNA sequencing (scRNA-seq), …

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Epigenetics Single-Cell Transcriptomics
Full text 2026

Study on the Potential Molecular Mechanism of Keloid Disease Associated With Single Cell Combined Mendelian Randomization

Wu HH, Meng YX, Liu JH, et al.

<h4>Background</h4>Keloids are pathological scars with incompletely understood pathogenesis. This study aims to identify the key genes and regulatory networks potentially involved in keloid formation by integrating single-cell transcriptomics (scRNA-seq), protein quantitative trait loci (pQTL), Mendelian …

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Single-Cell Transcriptomics
Full text 2026

Estimating time since influenza virus exposure using single-cell proteomic data

Rizzo Nervo K, Hajiakhoond Bidoki N, Chen H, et al.

<h4>Introduction</h4>Determining when the onset of a respiratory infection occurred is important for effective clinical management and can aid in mapping transmission events. However, current diagnostic assays report only pathogen detection status and do not provide …

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Metagenomics Single-Cell
Full text 2026

Single-cell landscape of immune cells in multiple autoimmune diseases

Zhu L, Sun W, Chen K, et al.

Autoimmune pathologies arise from dysregulated immune activation, yet conserved molecular programs across autoimmune contexts remain incompletely characterized. Here, we analyzed integrative single-cell RNA sequencing data of over 1.3 million cells from 239 samples spanning six …

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Bioinformatics Single-Cell Transcriptomics
Full text 2025

Single-cell RNA-seq data normalization: A benchmarking study

Ge Q, Sheng Y, Lu J, et al.

This study examines the noise and biases introduced by technical factors in single-cell RNA sequencing (scRNA-seq) data, presenting a thorough benchmarking analysis of six widely utilized normalization methods. The evaluation of these methods is conducted …

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Single-Cell Transcriptomics
Full text 2026

Single-cell-based identification of drug synergy with immunotherapy via tumor microenvironment remodeling

Wang Z, Hu J, Liu K, et al.

<h4>Background</h4>Identifying effective therapeutic drugs in the intricate tumor microenvironment (TME) is challenging, further complicated by the lack of a systematic framework for analyzing TME perturbations in response to therapeutic interventions.<h4>Methods</h4>To address this, we established the …

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Bioinformatics Single-Cell Transcriptomics
Full text 2026

singIST: An integrative method for comparative single-cell transcriptomics between disease models and humans

Moruno-Cuenca A, Picart-Armada S, Bogle R, et al.

<h4>Motivation</h4>Disease models are fundamental tools in drug discovery and early-stage drug development, but they only approximate human disease, and selecting a suitable model is challenging. Quantitative computational methods exist to assess molecular resemblance to human …

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Bioinformatics Single-Cell Transcriptomics
Full text 2026

sCellST predicts single-cell gene expression from H&amp; E images

Chadoutaud L, Lerousseau M, Herrero-Saboya D, et al.

Understanding the spatial organization of individual cell types within tissue and how this organization is disrupted in disease, is a central question in biology and medicine. Hematoxylin and eosin-stained slides are widely available and provide …

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Single-Cell