Algorithms for the quantitative Lock/Key model of cytoplasmic incompatibility

Cytoplasmic incompatibility (CI) relates to the manipulation by the parasite Wolbachia of its host reproduction. Despite its widespread occurrence, the molecular basis of CI remains unclear and theoretical models have been proposed to understand the phenomenon. We consider in this paper the quantita...

Full description

Saved in:
Bibliographic Details
Published in:Algorithms for molecular biology Vol. 15; no. 1; pp. 1 - 16
Main Authors: Calamoneri, Tiziana, Gastaldello, Mattia, Mary, Arnaud, Sagot, Marie-France, Sinaimeri, Blerina
Format: Journal Article
Language:English
Published: London BioMed Central 22.07.2020
BioMed Central Ltd
Springer Nature B.V
BMC
Subjects:
Algorithms
Analysis
Animal reproduction
Bacteria
Bioinformatics
Biomedical and Life Sciences
Cellular and Medical Topics
Chain subgraph cover problem
Chains
Computational Biology/Bioinformatics
Computational Complexity
Computer Science
Cytoplasmic incompatibility
Data Structures and Algorithms
Datasets
Eggs
Enumeration algorithms
Exact exponential algorithms
Graph theory
Graphs
Incompatibility
Interval order
Life Sciences
Parasites
Physiological
Polynomials
Sperm
Interval order
Exact exponential algorithms
Chain subgraph cover problem
Enumeration algorithms
Cytoplasmic incompatibility
ISSN:1748-7188, 1748-7188
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Cytoplasmic incompatibility (CI) relates to the manipulation by the parasite Wolbachia of its host reproduction. Despite its widespread occurrence, the molecular basis of CI remains unclear and theoretical models have been proposed to understand the phenomenon. We consider in this paper the quantitative Lock-Key model which currently represents a good hypothesis that is consistent with the data available. CI is in this case modelled as the problem of covering the edges of a bipartite graph with the minimum number of chain subgraphs. This problem is already known to be NP-hard, and we provide an exponential algorithm with a non trivial complexity. It is frequent that depending on the dataset, there may be many optimal solutions which can be biologically quite different among them. To rely on a single optimal solution may therefore be problematic. To this purpose, we address the problem of enumerating (listing) all minimal chain subgraph covers of a bipartite graph and show that it can be solved in quasi-polynomial time. Interestingly, in order to solve the above problems, we considered also the problem of enumerating all the maximal chain subgraphs of a bipartite graph and improved on the current results in the literature for the latter. Finally, to demonstrate the usefulness of our methods we show an application on a real dataset.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
content type line 23
ISSN:1748-7188
1748-7188
DOI:10.1186/s13015-020-00174-1