Statistical Analysis of Unlabeled Point Sets: Comparing Molecules in Chemoinformatics

DOI10.1111/j.1541-0420.2006.00622.xzbMath1122.62090OpenAlexW2140259073WikidataQ51916807 ScholiaQ51916807MaRDI QIDQ5427424

Ian L. Dryden, J. Hirst, James L. Melville

Publication date: 20 November 2007

Published in: Biometrics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1111/j.1541-0420.2006.00622.x

Mathematics Subject Classification ID

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) Paired and multiple comparisons; multiple testing (62J15)

Related Items (11)

Detection, classification and estimation of individual shapes in 2D and 3D point clouds ⋮ Bayesian comparison of protein structures using partial Procrustes distance ⋮ Multinomial principal component logistic regression on shape data ⋮ Unlabelled landmark matching via Bayesian data selection, and application to cell matching across imaging modalities ⋮ Bayesian alignment of similarity shapes ⋮ Bayesian alignment of proteins via Delaunay tetrahedralization ⋮ Analysis of AneuRisk65 data: internal carotid artery shape analysis ⋮ Hierarchical Bayesian Modeling of Pharmacophores in Bioinformatics ⋮ Bayesian protein structure alignment ⋮ 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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• Generalized Procrustes analysis
• The Riemannian structure of Euclidean shape spaces: A novel environment for statistics
• Shape, Procrustes tangent projections and bilateral symmetry
• Shape Manifolds, Procrustean Metrics, and Complex Projective Spaces
• Size and shape analysis of landmark data
• A new point matching algorithm for non-rigid registration
• Bayesian alignment using hierarchical models, with applications in protein bioinformatics

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