Search Results - Comprehensive Integration of Single-Cell Transcriptomic Data

Comprehensive integration of single-cell transcriptomic data illuminates the regulatory network architecture of plant cell fate specification by Cao, Shanni, Zhao, Xue, Li, Zhuojin, Yu, Ranran, Li, Yuqi, Zhou, Xinkai, Yan, Wenhao, Chen, Dijun, He, Chao

“…) in intricate regulatory networks in a cell-type specific manner. Here we introduced a comprehensive single-cell transcriptomic atlas of Arabidopsis seedlings…”
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Comprehensive integration of single-cell transcriptomic data illuminates the regulatory network architecture of plant cell fate specification by Cao, Shanni, He, Chao, Zhao, Xue, Yu, Ranran, Li, Yuqi, Fang, Wen, Chen-Yu, Zhang, Yan, Wenhao, Chen, Dijun

“…) in intricate regulatory networks at a cell-type specific manner. Here we presented a reference single-cell transcriptomic atlas of Arabidopsis seedlings by integration…”
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Multi-Omics Uncover Neonatal Cecal Cell Development Potentials by Liang Chen, Qingshi Meng, Li Shen, Yue Jiang, Cong Zhang, Shouwei Tang, Ruqing Zhong, Xiangfang Tang, Sheng Zhang, Xiaohui Feng, Yong Zhao, Hongfu Zhang

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Comprehensive Integration of Multiple Single-Cell Transcriptomic Data Sets Defines Distinct Cell Populations and Their Phenotypic Changes in Murine Atherosclerosis by Sharma, Disha, Worssam, Matthew D, Pedroza, Albert J, Dalal, Alex R, Alemany, Haizea, Kim, Hyun-Jung, Kundu, Ramendra, Fischbein, Michael P, Cheng, Paul, Wirka, Robert, Quertermous, Thomas

“…The application of single-cell transcriptomic (single-cell RNA sequencing) analysis to the study of atherosclerosis has provided unique insights into the molecular and genetic mechanisms that mediate disease risk and pathophysiology…”
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A pillar-based microfluidic chip for T-cells and B-cells isolation and detection with machine learning algorithm by Bilal Turan, Taisuke Masuda, Lei Wu, Anas Mohd Noor, Koji Horio, Toshiki Saito, Yasuyuki Miyata, Fumihito Arai

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A unified computational framework for single-cell data integration with optimal transport by Cao, Kai, Gong, Qiyu, Hong, Yiguang, Wan, Lin

“…Single-cell data integration can provide a comprehensive molecular view of cells…”
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Benchmarking spatial and single-cell transcriptomics integration methods for transcript distribution prediction and cell type deconvolution by Li, Bin, Zhang, Wen, Guo, Chuang, Xu, Hao, Li, Longfei, Fang, Minghao, Hu, Yinlei, Zhang, Xinye, Yao, Xinfeng, Tang, Meifang, Liu, Ke, Zhao, Xuetong, Lin, Jun, Cheng, Linzhao, Chen, Falai, Xue, Tian, Qu, Kun

“…-transcriptome-level data for single cells in space. Addressing this need, researchers have developed integration methods to combine spatial transcriptomic data with single-cell RNA-seq data to predict the spatial distribution of undetected transcripts…”
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Principled and interpretable alignability testing and integration of single-cell data by Ma, Rong, Sun, Eric D, Donoho, David, Zou, James

“…Single-cell data integration can provide a comprehensive molecular view of cells, and many algorithms have been developed to remove unwanted technical or biological variations and integrate…”
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Unraveling Alzheimer’s disease: insights from single-cell sequencing and spatial transcriptomic by He, Yibo, Lu, Wenqiang, Zhou, Xiao, Mu, Jie, Shen, Wei

“… This review highlights recent advancements in single-cell sequencing and spatial transcriptomics, which provide detailed insights into the cellular heterogeneity and neuroimmune mechanisms of AD…”
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Identification of immunogenic cell death signature genes in hepatocellular carcinoma: from single-cell transcriptomics to in vitro mechanistic validation and comprehensive prognostic modeling with hundreds of machine learning algorithms by Liu, Hongliang, Sun, Zhenni, Wang, Xi, Zhou, Bin, Cha, Lichao

“… We performed multi-omics integration of single-cell RNA sequencing data from 7 HCC samples (GSE112271, 44,461 cells…”
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Comprehensive Integration of Single-Cell Data by Stuart, Tim, Butler, Andrew, Hoffman, Paul, Hafemeister, Christoph, Papalexi, Efthymia, Mauck, 3rd, William M, Hao, Yuhan, Stoeckius, Marlon, Smibert, Peter, Satija, Rahul

“…Single-cell transcriptomics has transformed our ability to characterize cell states, but deep biological understanding requires more than a taxonomic listing of clusters…”
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Quantitative analysis of high‐throughput biological data by Juan, Hsueh‐Fen, Huang, Hsuan‐Cheng

“… We first review the quantitative analysis of not only bulk but also single‐cell transcriptomics data, as well as proteomics data…”
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Identification of genomic enhancers through spatial integration of single‐cell transcriptomics and epigenomics by Bravo González‐Blas, Carmen, Quan, Xiao‐Jiang, Duran‐Romaña, Ramon, Taskiran, Ibrahim Ihsan, Koldere, Duygu, Davie, Kristofer, Christiaens, Valerie, Makhzami, Samira, Hulselmans, Gert, de Waegeneer, Maxime, Mauduit, David, Poovathingal, Suresh, Aibar, Sara, Aerts, Stein

“…Single‐cell technologies allow measuring chromatin accessibility and gene expression in each cell, but jointly utilizing both layers to map bona fide gene regulatory networks and enhancers remains challenging…”
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Geometric Sketching Compactly Summarizes the Single-Cell Transcriptomic Landscape by Hie, Brian, Cho, Hyunghoon, DeMeo, Benjamin, Bryson, Bryan, Berger, Bonnie

“… Here, we describe how to enhance and accelerate single-cell data analysis by summarizing the transcriptomic heterogeneity within a dataset using a small subset of cells, which we refer to as a geometric sketch…”
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Panpipes: a pipeline for multiomic single-cell and spatial transcriptomic data analysis by Curion, Fabiola, Rich-Griffin, Charlotte, Agarwal, Devika, Ouologuem, Sarah, Rue-Albrecht, Kevin, May, Lilly, Garcia, Giulia E. L., Heumos, Lukas, Thomas, Tom, Lason, Wojciech, Sims, David, Theis, Fabian J., Dendrou, Calliope A.

“…Single-cell multiomic analysis of the epigenome, transcriptome, and proteome allows for comprehensive characterization of the molecular circuitry that underpins cell identity and state…”
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Resolving single-cell gene expression by pseudo-temporal integration of transcriptomic and proteomic datasets by Barry, Craig P, Talbo, Gert H, Beauglehole, Aiden, Ovchinnikov, Dmitry, Munro, Trent, Mahler, Stephen, Baker, Kym, Nielsen, Lars K, Mercer, Tim R, Marcellin, Esteban

“… We collected longitudinal single-cell samples following hypoxia. By leveraging key markers, we constructed pseudo-temporal trajectories for each data type, revealing transcriptional and translational responses to hypoxia…”
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Comprehensive transcriptional atlas of human adenomyosis deciphered by the integration of single-cell RNA-sequencing and spatial transcriptomics by Chen, Tao, Xu, Yiliang, Xu, Xiaocui, Wang, Jianzhang, Qiu, Zhiruo, Yu, Yayuan, Jiang, Xiaohong, Shao, Wanqi, Bai, Dandan, Wang, Mingzhu, Mei, Shuyan, Cheng, Tao, Wu, Li, Gao, Shaorong, Che, Xuan

“… Using single-cell RNA sequencing and spatial profiling, we mapped transcriptional alterations across eutopic endometrium, lesions, and EMJ…”
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Single-cell transcriptomics: a new frontier in plant biotechnology research by Singh, Shilpy, Praveen, Afsana, Dudha, Namrata, Sharma, Varun Kumar, Bhadrecha, Pooja

“… We present a comprehensive overview of the latest advancements in single-cell transcriptomics, emphasizing their application in elucidating complex cellular processes and developmental pathways in plants…”
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Integration of Pan-Cancer Single-Cell and Spatial Transcriptomics Reveals Stromal Cell Features and Therapeutic Targets in Tumor Microenvironment by Du, Yanhua, Shi, Jintong, Wang, Jiaxin, Xun, Zhenzhen, Yu, Zhuo, Sun, Hongxiang, Bao, Rujuan, Zheng, Junke, Li, Zhigang, Ye, Youqiong

“… cells. Here, we performed a pan-cancer analysis of 214,972 nonimmune stromal cells using single-cell RNA sequencing from 258 patients across 16 cancer types and analyzed spatial transcriptomics from 16…”
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Large-Scale Integration of Single-Cell RNA-Seq Data Reveals Astrocyte Diversity and Transcriptomic Modules across Six Central Nervous System Disorders by Qian, Zhenwei, Qin, Jinglin, Lai, Yiwen, Zhang, Chen, Zhang, Xiannian

“… Here, we demonstrate how large-scale integration of multi-omics data, including single-cell and spatial transcriptomic and proteomic data, overcomes these limitations…”
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