@article{Yang2023,
title        = {{Spatial transcriptomics of a lycophyte root sheds light on root evolution}},
author       = {X. Yang and W. Poelmans and C. Grones and A. Lakehal and J. Pevernagie and M. Van Bel and M. Njo and L. Xu and H. Nelissen and B. De Rybel and others},
journal      = {Curr. Biol.},
year         = {2023},
publisher    = {Elsevier}
}
@article{Joyner2013,
title        = {{Distance to the border in spatial point patterns}},
author       = {M. Joyner and C. Ross and E. Seier},
journal      = {Spat. Stat.},
pages        = {24 - 40},
volume       = {6},
year         = {2013},
abstract     = {The analysis of spatial point patterns is commonly focused on the distances to the nearest neighbor. The distance of organisms to the edge of the enclosure is also of interest in some biological studies performed in the laboratory. We define the B (border) function and derive its shape assuming complete spatial randomness (CSR) for square, rectangular, circular, and some three-dimensional arenas. The idea is then extended outside the laboratory setting to work with maps and points located in geographical regions. Commands in R (R Core Team, 2012) to calculate and plot the empirical Bˆ function are included. The B function, based on distances to the nearest edge, in addition to the G function, based on distances to the nearest neighbor, contributes to the understanding of the spatial distribution of the points.},
keywords     = {distance to nearest edge, nearest neighbor, maps, experimental enclosures},
issn         = {2211-6753},
doi          = {10.1016/j.spasta.2013.05.002},
url          = {https://www.sciencedirect.com/science/article/pii/S2211675313000341}
}
@article{Eng2019,
title        = {{Transcriptome-scale super-resolved imaging in tissues by RNA seqFISH+}},
author       = {C.-H. L. Eng and M. Lawson and Q. Zhu and R. Dries and N. Koulena and Y. Takei and J. Yun and C. Cronin and C. Karp and G.-C. Yuan and L. Cai},
journal      = {Nature},
pages        = {235 - 239},
volume       = {568},
number       = {7751},
month        = {4},
year         = {2019},
abstract     = {Imaging the transcriptome in situ with high accuracy has been a major challenge in single-cell biology, which is particularly hindered by the limits of optical resolution and the density of transcripts in single cells1--5. Here we demonstrate an evolution of sequential fluorescence in situ hybridization (seqFISH+). We show that seqFISH+ can image mRNAs for 10,000 genes in single cells---with high accuracy and sub-diffraction-limit resolution---in the cortex, subventricular zone and olfactory bulb of mouse brain, using a standard confocal microscope. The transcriptome-level profiling of seqFISH+ allows unbiased identification of cell classes and their spatial organization in tissues. In addition, seqFISH+ reveals subcellular mRNA localization patterns in cells and ligand--receptor pairs across neighbouring cells. This technology demonstrates the ability to generate spatial cell atlases and to perform discovery-driven studies of biological processes in situ.},
issn         = {1476-4687},
doi          = {10.1038/s41586-019-1049-y}
}

