Spatial Property Mapping
Spatial Property Mapping - Related Videos
11:52
Temporal Ordering of Dynamic Expression Data from Detailed Spatial Expression Maps
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2017
The segmentation clock drives oscillatory gene expression across the pre-somitic mesoderm (PSM). Dynamic Notch activity is key to this process. We use imaging and computational analyses to extract temporal dynamics from spatial expression data to demonstrate that Delta ligand and Notch receptor expression oscillate in the vertebrate PSM.
10:26
AFM-based Mapping of the Elastic Properties of Cell Walls: at Tissue, Cellular, and Subcellular Resolutions
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Cited by 39 •
2014
We describe a method to map mechanical properties of plant tissues using an atomic force microscope (AFM). We focus on how to record mechanical changes that take place in cell walls during plant development at wide-field mesoscale, enabling these changes to be correlated with growth and morphogenesis.
12:58
In Situ Mapping of the Mechanical Properties of Biofilms by Particle-tracking Microrheology
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Cited by 11 •
2015
Particle-tracking microrheology investigates the viscoelasticity of materials. Here, the technique is used to determine the viscoelasticity, creep compliance and effective crosslinking roles of different matrix components of a bacterial biofilm. The matrix consists of polymeric substances secreted by the bacteria and its components determine biofilm structure and mechanical properties.
14:42
Remote Magnetic Actuation of Micrometric Probes for in situ 3D Mapping of Bacterial Biofilm Physical Properties
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Cited by 6 •
2014
This paper shows an original methodology based on the remote actuation of magnetic particles seeded in a bacterial biofilm and the development of dedicated magnetic tweezers to measure in situ the local mechanical properties of the complex living material built by micro-organisms at interfaces.
08:52
Spatial Molecular Imaging of the Glycome Using Mass Spectrometry
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Cited by 1 •
2025
This protocol details the key steps to enable rigorous and reproducible measurement of both glycogen and N-linked glycans using mass spectrometry imaging.
FAQs
Spatial coordinates preserve the connection between a measured biological value and the location where it was observed. This allows gene expression, protein abundance, cell type, or physiological condition to be compared across defined regions while retaining anatomical or environmental reference information. The result is a location-aware analysis that distinguishes regional variation from an overall sample value.
Gradients show that a biological feature changes progressively across locations, whereas boundaries indicate a sharper transition between regions. Localized interactions add information about where features coincide or differ. Together, these patterns help connect spatial variation with structure and function, allowing investigators to examine organization within tissues, organisms, or environments instead of treating measurements as context-free.
Bulk analysis summarizes measurements across a larger sample, which can obscure differences among locations. Spatial property mapping retains location-specific values, so a high overall measurement can be examined for regional concentration, separation, or variation. This distinction matters when biological meaning depends on where a gene, protein, cell type, or physiological condition occurs, not only on its average abundance.
These maps can show associations between anatomical or environmental position and measured biological properties. Mapped values may expose localized interactions, boundaries between regions, or gradients that follow tissue organization. Comparing such patterns helps investigators relate structure to function and recognize spatial arrangements that would be difficult to interpret from isolated measurements without their positional context.
An investigator first defines the locations to compare and selects the biological property to measure, such as gene expression, protein abundance, cell type, or physiological condition. Each result is then linked to spatial coordinates and displayed with anatomical or environmental reference information. The completed map can be compared across regions to identify gradients, boundaries, localized interactions, and other patterns.
It is useful when location may influence how a biological feature should be interpreted. The approach supports studies of development, disease, ecology, and tissue organization by showing where properties occur and how they vary across a system. In each setting, the map adds spatial context that can clarify relationships among biological features, anatomical regions, and environmental positions.
Within a tissue, mapping can place cell types, gene expression, protein abundance, or physiological conditions alongside anatomical reference data. This makes it possible to compare neighboring or distinct regions and examine whether measured properties form gradients, boundaries, or localized associations. Such spatial comparisons help researchers investigate how tissue structure relates to biological function without relying only on averaged measurements.