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Multifactorial Comparative Study of Spatial Point Pattern Analysis Methods by France Wallet; Christophe Dussert is a Biochemistry, Genetics and Molecular Biology article available to read on EtoBox.

What is Multifactorial Comparative Study of Spatial Point Pattern Analysis Methods about?

A way of studying cooperative behaviour of biological entities (proteins, cells, etc.) is by using topographical analysis: the quantification of the spatial patterns formed by the entities considered as points. Five methods of topographical analysis were compared in terms of discriminant power, stability of parameters, methodological bias and algorithms. We tested five methods (nearest neighbour distribution, radial distribution, Voronoï paving, quadrat count, minimal spanning tree graph) which generated nine parameters on four simulated models (random point process, hardcore model and two cluster models) and on experimental cellular models. The method which offers the best discrimination power and stability seems to be the minimal spanning tree graph edge length distribution.

Who reads Multifactorial Comparative Study of Spatial Point Pattern Analysis Methods?

Author

France Wallet; Christophe Dussert

Publisher

Elsevier Science; Elsevier ; Elsevier Inc.; Elsevier BV (ISSN 0022-5193)

Published

1997

Language

EN

Field

Biochemistry, Genetics and Molecular Biology (Life Sciences)