Browse Items (445 total)

https://davku.lnx.warwick.ac.uk/files/original/4f6b4565d061176bb69b8e53a0459654.pdf

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poster.pdf

https://davku.lnx.warwick.ac.uk/files/original/61cfe7e06aef41eb7cfffa54f08ee1c2.pdf

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Evaluating Synthetic CTs - Kacper Babiarz.pdf

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https://davku.lnx.warwick.ac.uk/files/original/2af1d21417697b48c6e6224b5ed83bc7.pdf

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https://davku.lnx.warwick.ac.uk/files/original/59156df4d661d7d7bba1db9a52377201.pdf

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https://davku.lnx.warwick.ac.uk/files/original/56db86284feaab5d33989263016c253b.pdf

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https://davku.lnx.warwick.ac.uk/files/original/2790e911d382bb63d35e4d1190c88dfc.pdf

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https://davku.lnx.warwick.ac.uk/files/original/5b3acb1759425524d651ecca75da9fb5.pdf

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https://davku.lnx.warwick.ac.uk/files/original/54e7234a2352da8d321b1d7ed04408e1.pdf
In this project we use the Approximate Bayesian Computation - Markov Chain Monte Carlo algorithm to identify parameters of a SLiM model to explain our data
set of the observed site-frequency spectrum.

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Output Formats

atom, dcmes-xml, json, omeka-xml, rss2