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X-WR-CALDESC:Events for Institute for Quantitative and Computational Biosciences
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DTSTART;TZID=America/Los_Angeles:20231201T130000
DTEND;TZID=America/Los_Angeles:20231201T133000
DTSTAMP:20231201T222154Z
CREATED:20231030T181641Z
LAST-MODIFIED:20231201T222154Z
UID:25976-1701435600-1701437400@qcb.ucla.edu
SUMMARY:Research-in-Progress (RIP) Seminar: Kaija Gahm (Pinter-Wollman)\, Graduate Student in Ecology & Evolutionary Biology
DESCRIPTION:TITLE: “An updated movement path randomization method to distinguish social and spatial drivers of animal interactions.” \nABSTRACT: Studying the spatial-social interface requires tools that distinguish between social and spatial drivers of interactions. Testing hypotheses regarding the factors determining animal interactions often involves comparing observed interactions with reference or ’null’ models. One approach to constructing reference models that account for spatial drivers of social interactions is randomizing animal movement paths to decouple their spatial and social phenotypes while maintaining environmental effects on movements. Here we propose a new randomization approach. Using agent-based simulations\, we explore the utility of the new approach for different types of animal movements and compare its performance to existing approaches. We show that our method provides reference models that are more similar to the original tracking data\, while still distinguishing between social and spatial drivers. Furthermore\, the new approach results in fewer false-positives than other approaches\, especially when animals do not return to the same place each night but change movement foci\, either locally or directionally. Finally\, we show that interactions among GPStracked griffon vultures (Gyps fulvus) emerge from social attraction rather than from their movement patterns alone. We conclude by highlighting the biological situations in which the new method might be most suitable for testing hypotheses about the underlying causes of social interactions. \n\nhttps://wp-misc.lifesci.ucla.edu/qcb/wp-content/uploads/sites/14/2023/10/Kaija-Gahm.mp4
URL:https://qcb.ucla.edu/event/research-in-progress-rip-seminar-kaija-gahm-pinter-wollman-graduate-student-in-ecology-evolutionary-biology/
LOCATION:ZOOM\, CA\, United States
CATEGORIES:QCBio Seminar Series
ATTACH;FMTTYPE=image/jpeg:https://qcb.ucla.edu/wp-content/uploads/sites/14/2023/10/Kaija_Headshot_Final-3.jpg
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DTSTART;TZID=America/Los_Angeles:20231201T133000
DTEND;TZID=America/Los_Angeles:20231201T140000
DTSTAMP:20231201T221917Z
CREATED:20231018T093230Z
LAST-MODIFIED:20231201T221917Z
UID:25893-1701437400-1701439200@qcb.ucla.edu
SUMMARY:Research-in-Progress (RIP) Seminar: Samir Akre (Bui)\, Graduate Student in Medical Informatics
DESCRIPTION:TITLE: “Detection of Symptoms of Depression Using Data From the iPhone and Apple Watch.” \nABSTRACT: Digital health data from consumer wearable devices and smartphones have the potential to improve our understanding of mental illness. However\, in conditions like depression\, there is not yet a consistent uniform measurement tool whose result can be reliably used as a gold standard measure of depression severity. This work seeks to specify what symptoms and dimensions of depression can be detected using vitals\, activity\, and sleep monitored by consumer wearable devices. Machine learning models are fit to digital health data and used to detect responses to individual questions from self-reports as well as summary scores. Data is analyzed from an ongoing study with data from the Apple Watch\, iPhone\, and validated self-reports. The digital health data investigated was found to detect depression severity and specific symptoms like poor appetite\, aspects of anhedonia\, and sleep timings (ROC AUC 0.63 to 0.72). \nhttps://wp-misc.lifesci.ucla.edu/qcb/wp-content/uploads/sites/14/2023/10/Samir-Akre.mp4
URL:https://qcb.ucla.edu/event/research-in-progress-rip-seminar-samir-akre-bui-graduate-student-in-medical-informatics/
LOCATION:ZOOM\, CA\, United States
CATEGORIES:QCBio Seminar Series
ATTACH;FMTTYPE=image/jpeg:https://qcb.ucla.edu/wp-content/uploads/sites/14/2023/10/Akre-Samir-AMIA2022_crop.jpg
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