Nearest Neighbors
Nearest Neighbors - Related Videos
09:18
Identification of Intracellular Signaling Events Induced in Viable Cells by Interaction with Neighboring Cells Undergoing Apoptotic Cell Death
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Cited by 5 •
2016
Here, we present a protocol for the determination of intracellular signaling events induced in viable cells by physical interaction with adjacent dead or dying cells. The protocol focuses on signaling events induced by receptor-mediated recognition of the dead cells, as opposed to their phagocytic uptake or release of soluble mediators.
02:33
Lattice Centering and Coordination Number
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2020
The structure of a crystalline solid, whether a metal or not, is best described by considering its simplest repeating unit, which is referred to as its unit cell. The unit cell consists of lattice points that represent the locations of atoms or ions. The entire structure then consists of this unit cell repeating in three dimensions. The three different types of unit cells present in the cubic lattice are illustrated in Figure 1. Types of Unit Cells Imagine taking a large number of identical...
06:44
Age-dependent Dynamics of Locomotion in Caenorhabditis elegans: A Lyapunov Exponent Analysis
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2025
This study examines the effect of age on locomotion in C. elegans by measuring the largest Lyapunov exponent (LLE). As they age, C. elegans show an increase and subsequent decline in motor control. Results show a peak LLE at five days, followed by a decline as the worms age.
08:04
Conditions Affecting Social Space in Drosophila melanogaster
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Cited by 27 •
2015
The effect of genes and environment on social space of Drosophila melanogaster can be quantified through a powerful but straightforward analytical paradigm. We show here different factors that can affect this social space, and thus need to be taken into consideration when designing experiments in this paradigm.
13:26
Measuring Connectivity in the Primary Visual Pathway in Human Albinism Using Diffusion Tensor Imaging and Tractography
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Cited by 5 •
2016
This manuscript describes deterministic and probabilistic algorithms for white matter (WM) reconstruction, used to examine differences in optic radiation (OR) connectivity between albinism and controls. Although probabilistic tractography follows the true course of nerve fibers more closely, deterministic tractography was run to compare the reliability and reproducibility of both techniques.
FAQs
Distance provides the primary spatial criterion, but the identity of the surrounding particles determines how that proximity is interpreted chemically. Counting the relevant nearby atoms or particles gives the coordination number, while their arrangement helps reveal bond connectivity, intermolecular forces, or crystal packing. Thus, two reference particles with similar neighbor counts can still have different local chemical environments.
Changes in local geometry alter the arrangement around a reference particle, even when the same kinds of particles remain nearby. Such rearrangements can modify the local environment enough to influence stability and reactivity. Examining neighbor distances together with spatial arrangement therefore connects structural observations to differences in chemical behavior without relying only on the overall molecular or solid-state structure.
Neighbor relationships can be interpreted through more than one structural feature. In a molecule, nearby atoms help describe bond connectivity, whereas in a solid, the surrounding arrangement contributes to crystal packing; nearby particles can also reflect intermolecular forces. Considering these aspects together helps distinguish information about local chemical structure from the broader organization of a material.
Start with a chosen reference particle, identify the particles closest to it, and record their identities and relative distances. Next, examine their spatial arrangement to determine coordination number, connectivity, or packing relationships. The resulting local description can then be compared across structures or sites, allowing researchers to relate local differences to stability, reactivity, or physical properties.
In crystallographic data, local neighbor relationships provide a way to interpret how atoms are arranged within a solid. Distances and surrounding geometry help describe coordination and crystal packing, making it possible to compare local environments across a structure. These comparisons can clarify how atomic organization relates to the physical properties of materials and reveal local structural variation.
Computational models can use local neighbor relationships to compare structures and examine how short-range interactions may influence behavior. A model can evaluate which particles surround a reference site and how their arrangement differs between structures. This local comparison supports predictions about behavior while retaining structural information that may be missed by considering only a whole-molecule or bulk description.