Bayesian matching of unlabeled marked point sets using random fields, with an application to molecular alignment

DOI10.1214/11-AOAS486zbMath1234.62141arXiv1203.0098WikidataQ58419229 ScholiaQ58419229MaRDI QIDQ766002

Ian L. Dryden, Irina Czogiel, Christopher J. Brignell

Publication date: 22 March 2012

Published in: The Annals of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1203.0098

zbMATH Keywords

shapespatialMarkov chain Monte Carlosizebioinformaticsreproducing kernel Hilbert spaceKrigingchemoinformaticsProcrustessteroids

Mathematics Subject Classification ID

Inference from spatial processes (62M30) Random fields; image analysis (62M40) Applications of statistics to biology and medical sciences; meta analysis (62P10) Bayesian inference (62F15) Biochemistry, molecular biology (92C40) Numerical analysis or methods applied to Markov chains (65C40) Applications of functional analysis in probability theory and statistics (46N30)

Related Items (7)

Bayesian comparison of protein structures using partial Procrustes distance ⋮ Bayesian size-and-shape regression modelling ⋮ Multinomial principal component logistic regression on shape data ⋮ Bayesian alignment of proteins via Delaunay tetrahedralization ⋮ Bayesian registration of functions and curves ⋮ Matching markers and unlabeled configurations in protein gels ⋮ Bayesian matching of unlabeled marked point sets using random fields, with an application to molecular alignment

Uses Software

• R

Cites Work

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• An Approach to Statistical Spatial-Temporal Modeling of Meteorological Fields
• Statistical Analysis of Unlabeled Point Sets: Comparing Molecules in Chemoinformatics
• Bayesian alignment using hierarchical models, with applications in protein bioinformatics
• Theory of Reproducing Kernels

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