Results 1 to 10 of about 71,340 (293)

Spatial transcriptomics in neuroscience

Experimental and Molecular Medicine, 2023
The brain is one of the most complex living tissue types and is composed of an exceptional diversity of cell types displaying unique functional connectivity.
Namyoung Jung, Tae-Kyung Kim
doaj   +3 more sources

Multiscale Cell–Cell Interactive Spatial Transcriptomics Analysis [PDF]

Advanced Science
Spatial transcriptomics data analysis integrates gene expression profiles with their corresponding spatial locations to identify spatial domains, infer cell‐type dynamics, and detect gene expression patterns within tissues.
Sean Cottrell, Guo‐Wei Wei
doaj   +2 more sources

Unsupervised spatially embedded deep representation of spatial transcriptomics

Genome Medicine
Optimal integration of transcriptomics data and associated spatial information is essential towards fully exploiting spatial transcriptomics to dissect tissue heterogeneity and map out inter-cellular communications.
Hang Xu, Huazhu Fu, Yahui Long, Kok Siong Ang, Raman Sethi, Kelvin Chong, Mengwei Li, Rom Uddamvathanak, Hong Kai Lee, Jingjing Ling, Ao Chen, Ling Shao, Longqi Liu, Jinmiao Chen   +13 more
doaj   +3 more sources

Museum of Spatial Transcriptomics [PDF]

Nature Methods, 2020
AbstractThe function of many biological systems, such as embryos, liver lobules, intestinal villi, and tumors depends on the spatial organization of their cells. In the past decade high-throughput technologies have been developed to quantify gene expression in space, and computational methods have been developed that leverage spatial gene expression ...
Lambda Moses, Lior Pachter
openaire   +3 more sources

Spatially Aware Dimension Reduction for Spatial Transcriptomics [PDF]

Nature Communications, 2022
AbstractSpatial transcriptomics are a collection of genomic technologies that have enabled transcriptomic profiling on tissues with spatial localization information. Analyzing spatial transcriptomic data is computationally challenging, as the data collected from various spatial transcriptomic technologies are often noisy and display substantial spatial
Lulu Shang, Xiang Zhou
openaire   +3 more sources

Spatial Transcriptomic Technologies

Cells, 2023
Spatial transcriptomic technologies enable measurement of expression levels of genes systematically throughout tissue space, deepening our understanding of cellular organizations and interactions within tissues as well as illuminating biological insights in neuroscience, developmental biology and a range of diseases, including cancer.
Tsai-Ying Chen, Li You, Jose Angelito U. Hardillo, Miao-Ping Chien   +3 more
openaire   +3 more sources

Clustering spatial transcriptomics data

Bioinformatics, 2021
AbstractMotivationRecent advancements in fluorescence in situ hybridization (FISH) techniques enable them to concurrently obtain information on the location and gene expression of single cells. A key question in the initial analysis of such spatial transcriptomics data is the assignment of cell types.
Haotian Teng, Ye Yuan, Ziv Bar-Joseph
openaire   +2 more sources

Modeling zero inflation is not necessary for spatial transcriptomics

Genome Biology, 2022
Background Spatial transcriptomics are a set of new technologies that profile gene expression on tissues with spatial localization information. With technological advances, recent spatial transcriptomics data are often in the form of sparse counts with ...
Peiyao Zhao, Jiaqiang Zhu, Ying Ma, Xiang Zhou   +3 more
doaj   +1 more source

High atomic weight, high-energy radiation (HZE) induces transcriptional responses shared with conventional stresses in addition to a core "DSB" response specific to clastogenic treatments. [PDF]

, 2014
Plants exhibit a robust transcriptional response to gamma radiation which includes the induction of transcripts required for homologous recombination and the suppression of transcripts that promote cell cycle progression.
Britt, Anne B, Conklin, Phillip A, Culligan, Kevin M, Huefner, Neil D, Missirian, Victor   +4 more
core   +5 more sources

Single-cell spatial explorer: easy exploration of spatial and multimodal transcriptomics

BMC Bioinformatics, 2023
Background: The development of single-cell technologies yields large datasets of information as diverse and multimodal as transcriptomes, immunophenotypes, and spatial position from tissue sections in the so-called ’spatial transcriptomics’.
Frédéric Pont, Juan Pablo Cerapio, Pauline Gravelle, Laetitia Ligat, Carine Valle, Emeline Sarot, Marion Perrier, Frédéric Lopez, Camille Laurent, Jean Jacques Fournié, Marie Tosolini   +10 more
doaj   +1 more source