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X-WR-CALNAME:Institute for Quantitative and Computational Biosciences
X-ORIGINAL-URL:https://qcb.ucla.edu
X-WR-CALDESC:Events for Institute for Quantitative and Computational Biosciences
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DTSTART;TZID=America/Los_Angeles:20210514T110000
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DTSTAMP:20260518T040842
CREATED:20210331T001923Z
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UID:17706-1620990000-1620991800@qcb.ucla.edu
SUMMARY:QCBio Research Seminar: Brian Orcutt-Jahns (Meyer)
DESCRIPTION:TITLE: “A simple\, two-step\, multivalent binding model predicts IL-2 mutein cell signaling profiles.” \nABSTRACT: The common γ-chain cytokines are promising immune therapies\, but have been limited in their efficacy due to their induction of non-specific immune activation. Here\, we visualized immune cell response to both mono- and multivalent γ-chain muteins using a structured dimensionality reduction scheme. We then used a simple multivalent binding model to predict cell type-specific signaling with high accuracy. Finally\, we use this model to generate guidelines for engineering more effective γ-chain therapeutics. \n\nhttps://qcb.ucla.edu/wp-content/uploads/sites/14/2021/03/Brian-Orcutt-Jahns-edited.mp4
URL:https://qcb.ucla.edu/event/qcbio-research-seminar-brian-orcutt-jahns-meyer/
LOCATION:ZOOM\, CA\, United States
CATEGORIES:Research Seminars
ATTACH;FMTTYPE=image/jpeg:https://wp-misc.lifesci.ucla.edu/qcb/wp-content/uploads/sites/14/2021/03/Brian-Orcutt-Jahns.jpg
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DTSTART;TZID=America/Los_Angeles:20210514T110000
DTEND;TZID=America/Los_Angeles:20210514T120000
DTSTAMP:20260518T040842
CREATED:20210503T185337Z
LAST-MODIFIED:20210514T193804Z
UID:18011-1620990000-1620993600@qcb.ucla.edu
SUMMARY:QCBio Research Seminar: Rina Ding (Hsu)
DESCRIPTION:TITLE: “Multimodal radiomic analysis of biparametric MRI to predict biochemical recurrence after radical prostatectomy.” \nABSTRACT: Integration of information across multiple modalities and biological scales has the potential to improve the prediction of disease outcomes and response to treatments. In this talk\, I will discuss our ongoing work to predict prostate cancer aggressiveness by combining information from biparametric MRI. We predict biochemical recurrence (BCR) in 343 men post radical prostatectomy by fusing quantitative image features extracted from T2- and diffusion-weighted scans. We found the fused features improved the prediction of BCR when compared to various baseline models and clinical assessments. In the future\, we intend to incorporate genomic data\, relating imaging phenotypes to underlying tumor biology.\nhttps://qcb.ucla.edu/wp-content/uploads/sites/14/2021/05/Rina-Ding-edited.mp4
URL:https://qcb.ucla.edu/event/qcbio-research-seminar-rina-ding-hsu/
LOCATION:ZOOM\, CA\, United States
CATEGORIES:Research Seminars
ATTACH;FMTTYPE=image/jpeg:https://wp-misc.lifesci.ucla.edu/qcb/wp-content/uploads/sites/14/2021/05/Rina-Ding-1-scaled.jpg
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