CGIL Seminar F2021- Dr. Francisco Peñagaricano
Date and Time
Location
Online via Microsoft Teams
Details
We are very pleased to have Dr. Peñagaricano, an assistant professor of quantitative genomics at the University of Wisconsin Madison, presenting a CGIL Seminar on Friday September 24th, 2021. The seminar will begin at 1:30 PM EDT/EST on the virtual platform Microsoft Teams. The title of the presentation is: “Deciphering the genetic basis of dairy cattle fertility”.
To join this seminar, please ensure you have downloaded the Microsoft Teams application to your computer, or join the meeting online by using the web browser version of Microsoft Teams. Please join the meeting with your microphone on mute and camera turned off. After the presentation, you can unmute the microphone, and optionally turn on the camera, if you wish to ask a question. Alternatively, should you wish to pose your question in the chat function, it will be monitored and asked to the presenter.
Connection information for the meeting has been sent via a Calendar invitation, additionally the link of the meeting can be found at the bottom of this email.
Speaker Biography:
Francisco Peñagaricano is originally from Uruguay, where he earned his BS (2005) in Biology and Biochemistry and his MS (2010) in Animal Science, all from Universidad de la República. He continued his graduate studies at the University of Wisconsin where he earned his MS (2014) in Statistics and Ph.D. (2014) in Animal Science. Before joining UW, Francisco was a faculty member (2015-2020) in the Department of Animal Sciences at the University of Florida. His research interests are in quantitative genomics and computational biology. His research program focuses on the development and application of methods to dissect the genetic architecture of economically relevant traits in livestock. He typically combines large, nationwide phenotypic datasets or field experiments, with high–throughput genomic technologies, and advanced statistical and computational methods in order to elucidate the connection between genome and phenotype. His research involves gene mapping, gene-set analysis, genomic prediction, methylome and transcriptome analysis, multi-omics data integration, and network modeling.