EDoP distance between sets of incomplete permutations: Application to bacteria classification based on gene order

Xinrui Zhou; Amihood Amir; Concettina Guerra; Gadi Landau; Jarek Rossignac

doi:10.1089/cmb.2018.0063

EDoP distance between sets of incomplete permutations: Application to bacteria classification based on gene order

Xinrui Zhou, Amihood Amir, Concettina Guerra, Gadi Landau, Jarek Rossignac

Department of Computer Science

Research output: Contribution to journal › Article › peer-review

2 Scopus citations

Abstract

In this work, we extend measures of distance between permutations to support incomplete permutations. Modeling and comparing incomplete permutations are a challenging computational problem of practical importance in many applications in bioinformatics and social science. We show that the proposed distance measure admits a closed-form expression and can be efficiently computed on sets of permutations involving several missing elements. We demonstrate the proposed method on the classification of bacteria from different phyla based on gene order.

Original language	English
Pages (from-to)	1193-1202
Number of pages	10
Journal	Journal of Computational Biology
Volume	25
Issue number	11
DOIs	https://doi.org/10.1089/cmb.2018.0063
State	Published - Nov 2018

Bibliographical note

Publisher Copyright:
© Copyright 2018, Mary Ann Liebert, Inc., publishers 2018.

Funding

Amir, Guerra, Landau, and X. Zhao were, in part, supported by the U. S.–Israel Binational Science Foundation (BSF) grant 2014028. Amir and Landau were, in part, supported by the Israel Science Foundation 571-14.

Funders	Funder number
U. S.–Israel Binational Science Foundation
Bloom's Syndrome Foundation	2014028
Israel Science Foundation	571-14

Keywords

classification
distance
gene order
permutations

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10.1089/cmb.2018.0063

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EDoP distance between sets of incomplete permutations: Application to bacteria classification based on gene order

Abstract

Bibliographical note

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Keywords

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