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The k-Robinson-Foulds Dissimilarity Measures for Comparison of Labeled Trees.
Khayatian, Elahe; Valiente, Gabriel; Zhang, Louxin.
Afiliação
  • Khayatian E; Department of Mathematics, National University of Singapore, Singapore, Singapore.
  • Valiente G; Department of Computer Science, Technical University of Catalonia, Barcelona, Spain.
  • Zhang L; Department of Mathematics, National University of Singapore, Singapore, Singapore.
J Comput Biol ; 31(4): 328-344, 2024 04.
Article em En | MEDLINE | ID: mdl-38271573
ABSTRACT
Understanding the mutational history of tumor cells is a critical endeavor in unraveling the mechanisms that drive the onset and progression of cancer. Modeling tumor cell evolution with labeled trees motivates researchers to develop different measures to compare labeled trees. Although the Robinson-Foulds (RF) distance is widely used for comparing species trees, its applicability to labeled trees reveals certain limitations. This study introduces the k-RF dissimilarity measures, tailored to address the challenges of labeled tree comparison. The RF distance is succinctly expressed as n-RF in the space of labeled trees with n nodes. Like the RF distance, the k-RF is a pseudometric for multiset-labeled trees and becomes a metric in the space of 1-labeled trees. By setting k to a small value, the k-RF dissimilarity can capture analogous local regions in two labeled trees with different size or different labels.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Algoritmos Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Algoritmos Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Ano de publicação: 2024 Tipo de documento: Article