<html><head><meta http-equiv="Content-Type" content="text/html; charset=utf-8"></head><body style="word-wrap: break-word; -webkit-nbsp-mode: space; line-break: after-white-space;" class=""><div class="">Caros,</div><div class="">Dando continuidade ao ciclo de seminários conjunto UFSCar/ICMC-USP, gostaríamos de convidar a todos para o próximo evento, dia <b class="">19/03</b>, <b class="">às 14h</b>. Seguem informações abaixo. <b class="">Devido a problemas de invasões que têm ocorrido em alguns eventos online, o link do evento será divulgado apenas no dia.</b></div><div class="">Sintam-se à vontade para divulgar (arquivo em anexo) entre eventuais interessados.</div><div class="">Saudações,</div><div class="">Michel</div><div class=""><br class=""></div><div class=""><strong style="margin: 0px; padding: 0px; list-style: none; vertical-align: baseline; font-family: Roboto, sans-serif; font-size: 13.97760009765625px;" class="">Streaming:</strong></div><div class=""><span style="background-color: rgb(255, 255, 255);" class=""><font face="Roboto, sans-serif" size="2" class="">Google Meet (link will be available on the day of the event at </font></span><a href="http://www.pipges.ufscar.br/seminarios/26-03-2021-scalable-coalescent-inference-by-sampling-tajima2019s-trees-speaker-lorenzo-cappello" class="">www.pipges.ufscar.br</a><span style="font-family: Roboto, sans-serif; font-size: 13.97760009765625px; background-color: rgb(255, 255, 255);" class="">)</span><br style="margin: 0px; padding: 0px; list-style: none; vertical-align: baseline; font-family: Roboto, sans-serif; font-size: 13.97760009765625px;" class=""><br style="margin: 0px; padding: 0px; list-style: none; vertical-align: baseline; font-family: Roboto, sans-serif; font-size: 13.97760009765625px;" class=""><strong style="margin: 0px; padding: 0px; list-style: none; vertical-align: baseline; font-family: Roboto, sans-serif; font-size: 13.97760009765625px;" class="">Title:</strong><br style="margin: 0px; padding: 0px; list-style: none; vertical-align: baseline; font-family: Roboto, sans-serif; font-size: 13.97760009765625px;" class=""><span style="font-family: Roboto, sans-serif; font-size: 13.97760009765625px; background-color: rgb(255, 255, 255);" class="">Scalable coalescent inference by sampling Tajima’s trees</span><br style="margin: 0px; padding: 0px; list-style: none; vertical-align: baseline; font-family: Roboto, sans-serif; font-size: 13.97760009765625px;" class=""><br style="margin: 0px; padding: 0px; list-style: none; vertical-align: baseline; font-family: Roboto, sans-serif; font-size: 13.97760009765625px;" class=""><strong style="margin: 0px; padding: 0px; list-style: none; vertical-align: baseline; font-family: Roboto, sans-serif; font-size: 13.97760009765625px;" class="">Speaker:</strong><br style="margin: 0px; padding: 0px; list-style: none; vertical-align: baseline; font-family: Roboto, sans-serif; font-size: 13.97760009765625px;" class=""><span style="font-family: Roboto, sans-serif; font-size: 13.97760009765625px; background-color: rgb(255, 255, 255);" class="">Lorenzo Cappello (Stanford University)</span><br style="margin: 0px; padding: 0px; list-style: none; vertical-align: baseline; font-family: Roboto, sans-serif; font-size: 13.97760009765625px;" class=""><br style="margin: 0px; padding: 0px; list-style: none; vertical-align: baseline; font-family: Roboto, sans-serif; font-size: 13.97760009765625px;" class=""><strong style="margin: 0px; padding: 0px; list-style: none; vertical-align: baseline; font-family: Roboto, sans-serif; font-size: 13.97760009765625px;" class="">Abstract:</strong><br style="margin: 0px; padding: 0px; list-style: none; vertical-align: baseline; font-family: Roboto, sans-serif; font-size: 13.97760009765625px;" class=""><span style="font-family: Roboto, sans-serif; font-size: 13.97760009765625px; background-color: rgb(255, 255, 255);" class="">The observed sequence variation at a locus informs about the evolutionary history of the sample and past population size dynamics. The standard Kingman coalescent model on genealogies – timed trees that represent the ancestry of the sample – is used in a genera- tive model of molecular sequence variation to infer evolutionary parameters. However, it is computationally challenging to use this inference when sample size grows. We will discuss a lower-resolution coalescent model, called Tajima heterochronous n-coalescent, as a computationally efficient alternative to the Kingman coalescent. We will study how to quantify the size of the underlying state space, compute the likelihood, employ it in a Bayesian nonparametric model, and use it in applications.</span></div><div class=""><br class=""></div><div class=""></div></body></html>