Gotowe bibliografie tematyczne / Sc-RNA seq

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Gotowa bibliografia na temat „Sc-RNA seq”

Autor: Grafiati

Data publikacji: 16 listopada 2024

Data aktualizacji: 31 lipca 2025

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Artykuły w czasopismach na temat "Sc-RNA seq"

Song, Zheng, Likai Tan та Immo Prinz. "Human γδ T cell identification from single-cell RNA sequencing datasets by modular TCR expression". Journal of Leukocyte Biology 114, № 6 (2023): 630–38. https://doi.org/10.5281/zenodo.7989561.

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Accurately identifying γδ T cells in large single-cell RNA sequencing (scRNA-seq) datasets without additional single-cell γδ T cell receptor sequencing (sc-γδTCR-seq) or CITE-seq (cellular indexing of transcriptomes and epitopes sequencing) data remains challenging. In this study, we developed a TCR module scoring strategy for human γδ T cell identification (i.e. based on modular gene expression of constant and variable TRA/TRB and TRD genes). We evaluated our method using 5' scRNA-seq datasets comprising both sc-αβTCR-seq and sc-&gamm

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Ma, Shi-Xun, and Su Bin Lim. "Single-Cell RNA Sequencing in Parkinson’s Disease." Biomedicines 9, no. 4 (2021): 368. http://dx.doi.org/10.3390/biomedicines9040368.

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Single-cell and single-nucleus RNA sequencing (sc/snRNA-seq) technologies have enhanced the understanding of the molecular pathogenesis of neurodegenerative disorders, including Parkinson’s disease (PD). Nonetheless, their application in PD has been limited due mainly to the technical challenges resulting from the scarcity of postmortem brain tissue and low quality associated with RNA degradation. Despite such challenges, recent advances in animals and human in vitro models that recapitulate features of PD along with sequencing assays have fueled studies aiming to obtain an unbiased and global

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Biancalani, Tommaso, Gabriele Scalia, Lorenzo Buffoni, et al. "Deep learning and alignment of spatially resolved single-cell transcriptomes with Tangram." Nature Methods 18, no. 11 (2021): 1352–62. http://dx.doi.org/10.1038/s41592-021-01264-7.

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AbstractCharting an organs’ biological atlas requires us to spatially resolve the entire single-cell transcriptome, and to relate such cellular features to the anatomical scale. Single-cell and single-nucleus RNA-seq (sc/snRNA-seq) can profile cells comprehensively, but lose spatial information. Spatial transcriptomics allows for spatial measurements, but at lower resolution and with limited sensitivity. Targeted in situ technologies solve both issues, but are limited in gene throughput. To overcome these limitations we present Tangram, a method that aligns sc/snRNA-seq data to various forms o

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Li, Chunbao, Mingyang An, Yang He, and Zhongyuan Zhao. "FP3.3 Single-cell RNA-seq analysis reveals a new mechanism of cartilage formation from the synovium in synovial chondromatosis." Journal of Hip Preservation Surgery 12, Supplement_1 (2025): i7. https://doi.org/10.1093/jhps/hnaf011.021.

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Abstract Objective: Cartilage repair remains a challenging medical issue with a lack of effective solutions to date. Synovial chondromatosis (SC) is a rare benign tumor caused by synovial metaplasia. A characteristic feature of SC is the synovium’s spontaneous ability to form translucent cartilage nodules. Currently, the molecular mechanisms behind spontaneous cartilage formation in vivo are poorly understood. Our study aims to investigate the mechanisms of chondrogenesis in SC and the dynamic changes between cell subpopulations at the cellular level using single-cell sequencing technology. Me

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Ajani, Jaffer A., Yan Xu, Longfei Huo, et al. "YAP1 mediates gastric adenocarcinoma peritoneal metastases that are attenuated by YAP1 inhibition." Gut 70, no. 1 (2020): 55–66. http://dx.doi.org/10.1136/gutjnl-2019-319748.

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ObjectivePeritoneal carcinomatosis (PC; malignant ascites or implants) occurs in approximately 45% of advanced gastric adenocarcinoma (GAC) patients and associated with a poor survival. The molecular events leading to PC are unknown. The yes-associated protein 1 (YAP1) oncogene has emerged in many tumour types, but its clinical significance in PC is unclear. Here, we investigated the role of YAP1 in PC and its potential as a therapeutic target.MethodsPatient-derived PC cells, patient-derived xenograft (PDX) and patient-derived orthotopic (PDO) models were used to study the function of YAP1 in

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Si, Tong, Zackary Hopkins, John Yanev, Jie Hou, and Haijun Gong. "A novel f-divergence based generative adversarial imputation method for scRNA-seq data analysis." PLOS ONE 18, no. 11 (2023): e0292792. http://dx.doi.org/10.1371/journal.pone.0292792.

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Comprehensive analysis of single-cell RNA sequencing (scRNA-seq) data can enhance our understanding of cellular diversity and aid in the development of personalized therapies for individuals. The abundance of missing values, known as dropouts, makes the analysis of scRNA-seq data a challenging task. Most traditional methods made assumptions about specific distributions for missing values, which limit their capability to capture the intricacy of high-dimensional scRNA-seq data. Moreover, the imputation performance of traditional methods decreases with higher missing rates. We propose a novel f-

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Li, Shenghao, Hui Guo, Simai Zhang, Yizhou Li, and Menglong Li. "Attention-based deep clustering method for scRNA-seq cell type identification." PLOS Computational Biology 19, no. 11 (2023): e1011641. http://dx.doi.org/10.1371/journal.pcbi.1011641.

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Single-cell sequencing (scRNA-seq) technology provides higher resolution of cellular differences than bulk RNA sequencing and reveals the heterogeneity in biological research. The analysis of scRNA-seq datasets is premised on the subpopulation assignment. When an appropriate reference is not available, such as specific marker genes and single-cell reference atlas, unsupervised clustering approaches become the predominant option. However, the inherent sparsity and high-dimensionality of scRNA-seq datasets pose specific analytical challenges to traditional clustering methods. Therefore, a variou

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Lall, Snehalika, Sumanta Ray, and Sanghamitra Bandyopadhyay. "A copula based topology preserving graph convolution network for clustering of single-cell RNA-seq data." PLOS Computational Biology 18, no. 3 (2022): e1009600. http://dx.doi.org/10.1371/journal.pcbi.1009600.

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Annotation of cells in single-cell clustering requires a homogeneous grouping of cell populations. There are various issues in single cell sequencing that effect homogeneous grouping (clustering) of cells, such as small amount of starting RNA, limited per-cell sequenced reads, cell-to-cell variability due to cell-cycle, cellular morphology, and variable reagent concentrations. Moreover, single cell data is susceptible to technical noise, which affects the quality of genes (or features) selected/extracted prior to clustering. Here we introduce sc-CGconv (copula based graph convolution network f

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Hanamsagar, Richa, Robert Marcus, Mathew Chamberlain, Emanuele de Rinaldis, and Virginia Savova. "Optimum processing conditions for single cell RNA sequencing on frozen human PBMCs." Journal of Immunology 202, no. 1_Supplement (2019): 131.15. http://dx.doi.org/10.4049/jimmunol.202.supp.131.15.

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Abstract The field of single cell RNA sequencing (sc-SEQ) has exploded in the past few years. From picking up single cells manually under a microscope, to droplet-based encapsulation of cells using microfluidics – this technology has improved in leaps and bounds. Common droplet-based technologies include inDrop, Drop-seq and 10X Genomics Chromium. All three technologies utilize microfluidics for encapsulating single cells & uniquely barcoded beads within an oil droplet. They differ in their bead material/manufacturing, barcode design and the range to which their operation can be customized

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Hagemann, Tobias, Paul Czechowski, Adhideb Ghosh та ін. "Laminin α4 Expression in Human Adipose Tissue Depots and Its Association with Obesity and Obesity Related Traits". Biomedicines 11, № 10 (2023): 2806. http://dx.doi.org/10.3390/biomedicines11102806.

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Laminin α4 (LAMA4) is one of the main structural adipocyte basement membrane (BM) components that is upregulated during adipogenesis and related to obesity in mice and humans. We conducted RNA-seq-based gene expression analysis of LAMA4 in abdominal subcutaneous (SC) and visceral (VIS) adipose tissue (AT) depots across three human sub-cohorts of the Leipzig Obesity BioBank (LOBB) to explore the relationship between LAMA4 expression and obesity (N = 1479) in the context of weight loss (N = 65) and metabolic health (N = 42). We found significant associations of LAMA4 with body fat mass (p < 0

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Rozprawy doktorskie na temat "Sc-RNA seq"

Salloum, Yazan. "Innate lymphoid cell-produced interleukin-26 modulates proliferation and DNA damage in intestinal epithelial cells." Electronic Thesis or Diss., Université Paris sciences et lettres, 2024. http://www.theses.fr/2024UPSLS015.

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L'interleukine-26 (IL-26) a été identifiée comme un facteur de risque pour les maladies inflammatoires chroniques de l'intestin (MICI). Cependant, les fonctions de l'IL-26 ne sont pas bien comprises en raison de son absence chez les rongeurs. Comme le poisson zèbre possède un orthologue de cette cytokine, nous utilisons ce modèle pour étudier son rôle dans l'homéostasie intestinale.Nous avons généré le premier mutant de cette cytokine in vivo, et nous avons découvert que le microbiote intestinal module l'expression de l'IL-26 dans l'intestin. Nous avons révélé que l'IL-26 module la cycle cellu

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Streszczenia konferencji na temat "Sc-RNA seq"

Zhang, Tim, Amirali Amirsoleimani, Jason K. Eshraghian, Mostafa Rahimi Azghadi, Roman Genov, and Yu Xia. "SSCAE: A Neuromorphic SNN Autoencoder for sc-RNA-seq Dimensionality Reduction." In 2023 IEEE International Symposium on Circuits and Systems (ISCAS). IEEE, 2023. http://dx.doi.org/10.1109/iscas46773.2023.10181994.

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