Results 11 to 20 of about 2,352,277 (290)
Single cell transcriptional analysis reveals novel innate immune cell types [PDF]
PeerJ, 2014 Single-cell analysis has the potential to provide us with a host of new knowledge about biological systems, but it comes with the challenge of correctly interpreting the biological information.
Linda E. Kippner +3 more
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Linked optical and gene expression profiling of single cells at high-throughput [PDF]
Genome Biology, 2020 Single-cell RNA sequencing has emerged as a powerful tool for characterizing cells, but not all phenotypes of interest can be observed through changes in gene expression.
Jesse Q. Zhang +5 more
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Single cell gene expression analysis in injury-induced collective cell migration. [PDF]
Integr Biol (Camb), 2014 Collective cell behavior in response to mechanical injury is central to various regenerative and pathological processes. Using a double-stranded locked nucleic acid probe for monitoring real-time intracellular gene expression, we examined the spatiotemporal response of epithelial cells during injury-induced collective migration and compared to the ...
Riahi R +6 more
europepmc +4 more sources
Determining Physical Mechanisms of Gene Expression Regulation from Single Cell Gene Expression Data. [PDF]
PLoS Computational Biology, 2016 Many genes are expressed in bursts, which can contribute to cell-to-cell heterogeneity. It is now possible to measure this heterogeneity with high throughput single cell gene expression assays (single cell qPCR and RNA-seq). These experimental approaches
Daphne Ezer +3 more
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Strategies for aggregating gene expression data: The collapseRows R function [PDF]
BMC Bioinformatics, 2011 Background Genomic and other high dimensional analyses often require one to summarize multiple related variables by a single representative. This task is also variously referred to as collapsing, combining, reducing, or aggregating variables.
Miller Jeremy A +6 more
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Differential variability analysis of single-cell gene expression data [PDF]
Briefings in Bioinformatics, 2023 Abstract The advent of single-cell RNA sequencing (scRNA-seq) technologies has enabled gene expression profiling at the single-cell resolution, thereby enabling the quantification and comparison of transcriptional variability among individual cells.
Jiayi Liu, Anat Kreimer, Wei Vivian Li
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Gene expression program analysis of cancer-testis genes
Shanghai Jiaotong Daxue xuebao. Yixue ban, 2023 Objective·To identify the gene expression program (GEP) of cancer-testis genes (CTGs) during spermatogenesis based on single-cell transcriptome data from the testis and investigate their association with the prognosis of cancer patients.Methods ...
HOU Zongliang +3 more
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Computational and Structural Biotechnology Journal, 2022 Background. Differential expression analysis is a standard approach in molecular biology. For example, genes whose expression levels differ between diseased and non-diseased samples are considered to be associated with that disease.
Daigo Okada, Cheng Zheng, Jian Hao Cheng
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BMC Bioinformatics, 2023 Background High-throughput experiments provide deep insight into the molecular biology of different species, but more tools need to be developed to handle this type of data. At the transcriptomics level, quantitative Polymerase Chain Reaction technology (
Alexis Germán Murillo Carrasco +4 more
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Prediction of single-cell gene expression for transcription factor analysis [PDF]
GigaScience, 2020 Abstract Background Single-cell RNA sequencing is a powerful technology to discover new cell types and study biological processes in complex biological samples. A current challenge is to predict transcription factor (TF) regulation from single-cell RNA data.
Fatemeh Behjati Ardakani +10 more
openaire +4 more sources