A computational study of density-dependent individual movement and the formation of population clusters in two-dimensional spatial domains.
Sign Up to like & getrecommendations! Published in 2020 at "Journal of theoretical biology"
DOI: 10.1016/j.jtbi.2020.110421
Abstract: The patterns of collective behaviour in a population emerging from individual animal movement has long been of interest to ecologists, as has the emergence of heterogeneous patterns among a population. In this paper we will… read more here.
Keywords: density dependent; movement; spatial domains; formation ... See more keywords
Deciphering spatial domains from spatially resolved transcriptomics with an adaptive graph attention auto-encoder.
Sign Up to like & getrecommendations! Published in 2022 at "Nature communications"
DOI: 10.1038/s41467-022-29439-6
Abstract: Recent advances in spatially resolved transcriptomics have enabled comprehensive measurements of gene expression patterns while retaining the spatial context of the tissue microenvironment. Deciphering the spatial context of spots in a tissue needs to use… read more here.
Keywords: spatially resolved; resolved transcriptomics; spatial domains; attention ... See more keywords
Graph deep learning enabled spatial domains identification for spatial transcriptomics.
Sign Up to like & getrecommendations! Published in 2023 at "Briefings in bioinformatics"
DOI: 10.1093/bib/bbad146
Abstract: Advancing spatially resolved transcriptomics (ST) technologies help biologists comprehensively understand organ function and tissue microenvironment. Accurate spatial domain identification is the foundation for delineating genome heterogeneity and cellular interaction. Motivated by this perspective, a graph… read more here.
Keywords: learning enabled; enabled spatial; deep learning; graph deep ... See more keywords