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Bioinformatics
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Bioinformatics
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Bioinformatics
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https://dx.doi.org/10.48550/ar...
Article . 2016
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Simulation-based estimation of branching models for LTR retrotransposons

Authors: Serge Moulin; Nicolas Seux; Stéphane Chrétien; Christophe Guyeux; Emmanuelle Lerat;

Simulation-based estimation of branching models for LTR retrotransposons

Abstract

Abstract Motivation LTR retrotransposons are mobile elements that are able, like retroviruses, to copy and move inside eukaryotic genomes. In the present work, we propose a branching model for studying the propagation of LTR retrotransposons in these genomes. This model allows us to take into account both the positions and the degradation level of LTR retrotransposons copies. In our model, the duplication rate is also allowed to vary with the degradation level. Results Various functions have been implemented in order to simulate their spread and visualization tools are proposed. Based on these simulation tools, we have developed a first method to evaluate the parameters of this propagation model. We applied this method to the study of the spread of the transposable elements ROO, GYPSY and DM412 on a chromosome of Drosophila melanogaster. Availability and Implementation Our proposal has been implemented using Python software. Source code is freely available on the web at https://github.com/SergeMOULIN/retrotransposons-spread. Supplementary information are available at Bioinformatics online.

Country
France
Keywords

570, Retroelements, 610, [INFO.INFO-SE]Computer Science [cs]/Software Engineering [cs.SE], Chromosomes, [INFO.INFO-IU]Computer Science [cs]/Ubiquitous Computing, [INFO.INFO-CR]Computer Science [cs]/Cryptography and Security [cs.CR], Cell Behavior (q-bio.CB), Animals, Quantitative Biology - Genomics, Computer Simulation, Genomics (q-bio.GN), [INFO.INFO-DC]Computer Science [cs]/Distributed, Genome, Models, Genetic, [SDV.BID.EVO]Life Sciences [q-bio]/Biodiversity/Populations and Evolution [q-bio.PE], Parallel, [INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation, [SDV.BIBS]Life Sciences [q-bio]/Quantitative Methods [q-bio.QM], Drosophila melanogaster, and Cluster Computing [cs.DC], [INFO.INFO-MA]Computer Science [cs]/Multiagent Systems [cs.MA], FOS: Biological sciences, Quantitative Biology - Cell Behavior, [INFO.INFO-ET]Computer Science [cs]/Emerging Technologies [cs.ET], Programming Languages, Software

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average
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gold