Identifying a piecewise affine signal from its nonlinear observation -application to DNA replication analysis
Résumé
DNA replication stands as one of the fundamental biological processes crucial for cellular
functioning. Recent experimental developments enable the study of replication dynamics at
the single-molecule level for complete genomes, facilitating a deeper understanding of its main
parameters. In these new data, replication dynamics is reported by the incorporation of an
exogenous chemical, whose intra-cellular concentration follows a nonlinear function. The analysis
of replication traces thus gives rise to a nonlinear inverse problem, presenting a nonconvex
optimization challenge. We demonstrate that under noiseless conditions, the replication dynamics
can be uniquely identified by the proposed model. Computing a global solution to this
optimization problem is specially challenging because of its multiple local minima. We present
the DNA-inverse optimization method that is capable of finding this global solution even in
the presence of noise. Comparative analysis against state-of-the-art optimization methods highlights
the superior computational efficiency of our approach. DNA-inverse enables the automatic
recovery of all configurations of the replication dynamics, which was not possible with previous methods
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preprint.pdf (2.22 Mo)
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RepResults.png (127.96 Ko)
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biofigure.png (114.16 Ko)
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comp_execution_time.png (13.23 Ko)
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comp_solution_2.png (79.35 Ko)
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constraints.png (67.71 Ko)
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diagram.png (47.06 Ko)
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exampledefwieghts.png (1.22 Mo)
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lemma_fig_2.png (77.89 Ko)
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linear_fork.png (77.26 Ko)
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preprint.synctex.gz (263.26 Ko)
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simulated_read_results.png (47.74 Ko)
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solution_valk_Inverse.png (108.03 Ko)
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