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Hamiltonian Monte Carlo with strict convergence criteria reduces run-to-run variability in forensic DNA mixture deconvolution
Mateusz Susik, Holger Schönborn, Ivo F. Sbalzarini
doi: https://doi.org/10.1101/2022.02.15.480571
Mateusz Susik
1Biotype GmbH, Dresden, 01109, Germany
2Technische Universität Dresden, Faculty of Computer Science, Dresden, 01187, Germany
Holger Schönborn
3qualitype GmbH, Dresden, 01109, Germany
Ivo F. Sbalzarini
2Technische Universität Dresden, Faculty of Computer Science, Dresden, 01187, Germany
4Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, 01307, Germany
5Center for Systems Biology Dresden, Dresden, 01307, Germany
Posted March 23, 2022.
Hamiltonian Monte Carlo with strict convergence criteria reduces run-to-run variability in forensic DNA mixture deconvolution
Mateusz Susik, Holger Schönborn, Ivo F. Sbalzarini
bioRxiv 2022.02.15.480571; doi: https://doi.org/10.1101/2022.02.15.480571
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