An Algorithm to Calculate the p-Value of the Monge-Elkan Distance
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F25%3A00386079" target="_blank" >RIV/68407700:21230/25:00386079 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1089/cmb.2024.0854" target="_blank" >https://doi.org/10.1089/cmb.2024.0854</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1089/cmb.2024.0854" target="_blank" >10.1089/cmb.2024.0854</a>
Alternative languages
Result language
angličtina
Original language name
An Algorithm to Calculate the p-Value of the Monge-Elkan Distance
Original language description
The Monge-Elkan distance is a straightforward yet popular distance measure used to estimate the mutual similarity of two sets of objects. It was initially proposed in the field of databases, and it found broad usage in other fields. Nowadays, it is especially relevant to the analysis of new-generation sequencing data as it represents a measure of dissimilarity between genomes of two distinct organisms, particularly when applied to unassembled reads. This article provides an algorithm to calculate the p-value associated with the Monge-Elkan distance. Given the object-level null distribution, that is, the distribution of distances between independently and identically sampled objects such as reads, the method yields the null distribution of the Monge-Elkan distance, which in turn allows for calculating the p-value. We also demonstrate an application on sequencing data, where individual reads are compared by the Levenshtein distance.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
<a href="/en/project/GA24-11664S" target="_blank" >GA24-11664S: Relational Reinforcement Learning for Science Acceleration</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Journal of Computational Biology
ISSN
1557-8666
e-ISSN
1557-8666
Volume of the periodical
32
Issue of the periodical within the volume
8
Country of publishing house
US - UNITED STATES
Number of pages
16
Pages from-to
797-812
UT code for WoS article
001504133200001
EID of the result in the Scopus database
2-s2.0-105012786864