Quantifying spatial structure in experimental observations and agent-based simulations using pair-correlation functions.
about
Reconciling diverse mammalian pigmentation patterns with a fundamental mathematical modelSpectral analysis of pair-correlation bandwidth: application to cell biology imagesQuantifying two-dimensional filamentous and invasive growth spatial patterns in yeast coloniesUsing approximate Bayesian computation to quantify cell-cell adhesion parameters in a cell migratory process.Assessing the role of spatial correlations during collective cell spreading.Spatial moment dynamics for collective cell movement incorporating a neighbour-dependent directional bias.Identifying the necrotic zone boundary in tumour spheroids with pair-correlation functionsInterpreting scratch assays using pair density dynamics and approximate Bayesian computation.Variable species densities are induced by volume exclusion interactions upon domain growth.Quantifying the dominant growth mechanisms of dimorphic yeast using a lattice-based model.How domain growth is implemented determines the long-term behavior of a cell population through its effect on spatial correlations.
P2860
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P2860
Quantifying spatial structure in experimental observations and agent-based simulations using pair-correlation functions.
description
2013 nî lūn-bûn
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2013年の論文
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2013年学术文章
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2013年学术文章
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2013年学术文章
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name
Quantifying spatial structure ...... ng pair-correlation functions.
@en
Quantifying spatial structure ...... ng pair-correlation functions.
@nl
type
label
Quantifying spatial structure ...... ng pair-correlation functions.
@en
Quantifying spatial structure ...... ng pair-correlation functions.
@nl
prefLabel
Quantifying spatial structure ...... ng pair-correlation functions.
@en
Quantifying spatial structure ...... ng pair-correlation functions.
@nl
P2860
P1433
P1476
Quantifying spatial structure ...... ng pair-correlation functions.
@en
P2093
Benjamin J Binder
P2860
P304
P356
10.1103/PHYSREVE.88.022705
P407
P577
2013-08-12T00:00:00Z