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X-WR-CALDESC:Events for Institute for Quantitative and Computational Biosciences
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DTSTART;TZID=America/Los_Angeles:20211110T120000
DTEND;TZID=America/Los_Angeles:20211110T123000
DTSTAMP:20260518T005157
CREATED:20211027T205511Z
LAST-MODIFIED:20211027T205554Z
UID:19913-1636545600-1636547400@qcb.ucla.edu
SUMMARY:QCBio Research Seminar: Mariana Harris Heredia (Garud)\, Grad student in Biomathematics
DESCRIPTION:TITLE: “Differences in the Signatures of Selection Between the Autosomes and the X Chromosome in Drosophila melanogaster.” \nABSTRACT: Sex chromosomes in Drosophila are found in a hemizygous state in males. Thus\, deleterious mutations may be purged more rapidly on the X chromosome than on the autosomes. This purging can result in less available standing variation that can seed adaptation on the X chromosome. Here\, we investigate how differences in the recessivity of alleles on the X chromosome versus autosomes impact the mode and tempo of adaptation. Specifically\, we test the hypothesis that hard sweeps\, in which a single adaptive mutation rises to high frequency\, are more common on the X chromosome\, while soft sweeps\, in which multiple haplotypes rise to high frequency simultaneously\, are more common on the autosomes. We analyze D. melanogaster genomic data from two populations\, North Carolina\, and Zambia\, and find evidence that suggests that indeed\, hard sweeps are more prevalent on the X chromosome and soft sweeps are more common on the autosomes. \nFor lunch at 12:30pm with the speaker\, please RSVP at qcboffice@lifesci.ucla.edu
URL:https://qcb.ucla.edu/event/qcbio-research-seminar-mariana-harris-heredia-garud-grad-student-in-biomathematics/
LOCATION:Boyer 159\, 611 Charles E. Young Dr. E.\, Los Angeles\, CA\, 90095\, United States
CATEGORIES:Research Seminars
ATTACH;FMTTYPE=image/jpeg:https://wp-misc.lifesci.ucla.edu/qcb/wp-content/uploads/sites/14/2021/10/Mariana-Harris-Heredia.jpeg
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DTSTART;TZID=America/Los_Angeles:20211110T130000
DTEND;TZID=America/Los_Angeles:20211110T133000
DTSTAMP:20260518T005157
CREATED:20211026T011133Z
LAST-MODIFIED:20211027T205757Z
UID:19880-1636549200-1636551000@qcb.ucla.edu
SUMMARY:QCBio Research Seminar: Guo Xiaohui (Pinter-Wollman)\, Postdoc in Ecology & Evolutionary Biology
DESCRIPTION:TITLE: “Decoding alarm signal propagation of seed-harvester ants\, Pogonomyrmex californicus.” \nABSTRACT: Alarm signal propagation through social-insect colonies provides an empirically tractable context for analyzing information flow through a natural system\, with useful insights for network dynamics in other social groups\, including human social networks. Here\, I develop a methodological approach to track alarm spread within the group of harvester ants\, Pogonomyrmex californicus. I alarmed initial 3 individuals and tracked subsequent signal transmission through the group. Because there was no actual threat\, the alarm was false\, allowing us to assess amplification and adaptive damping of collective alarm response. I trained a Random-Forest machine learning regression model to quantify alarm behavior of individual workers from multiple movement features associated with alarm behavior in this species. This approach provides reliable continuous assessments of an individual’s behavioral state at much finer temporal scales and more consistently than can be achieved visually. I combined the ML alarm state assessments with proximity data from tracking software (ABCTracker) to construct a propagation network of alarm spread. Using this system\, alarm propagation can be manipulated and assessed to ask and answer a wide range of questions on information and misinformation flow in social networks. \nFor lunch at 12:30pm with the speaker\, please RSVP at qcboffice@lifesci.ucla.edu
URL:https://qcb.ucla.edu/event/qcbio-research-seminar-guo-xiaohui-pinter-wollman-postdoc-in-ecology-evolutionary-biology/
LOCATION:Boyer 159\, 611 Charles E. Young Dr. E.\, Los Angeles\, CA\, 90095\, United States
CATEGORIES:Research Seminars
ATTACH;FMTTYPE=image/png:https://wp-misc.lifesci.ucla.edu/qcb/wp-content/uploads/sites/14/2021/10/Guo-Xiaohui.png
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