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DTSTART;TZID=America/Los_Angeles:20250807T103000
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DTSTAMP:20260423T211731
CREATED:20250805T070000Z
LAST-MODIFIED:20250925T231625Z
UID:10000091-1754562600-1754562600@events.ucsc.edu
SUMMARY:Rose\, N. (BMEB) - MACHINE LEARNING MODELS FOR T CELL RECEPTOR TARGET DISCOVERY AND AFFINITY ENGINEERING
DESCRIPTION:T cell receptors (TCRs) mediate antigen-specific immune responses through recognition of peptides presented by major histocompatibility complex (pMHC) molecules. Accurately predicting TCR–pMHC interactions remains a major barrier to TCR-based immunotherapy\, due to limitations in current models that fail to generalize beyond common viral epitopes and well-characterized HLA alleles. In this PhD proposal\, I outline a computational framework that integrates deep learning\, structural modeling\, and molecular simulation to improve TCR–pMHC prediction and discovery. I first introduce TRIOPS\, a convolutional neural network trained on harmonized\, experimentally validated data to predict MHC restriction from TCR sequence alone. TRIOPS outperforms state-of-the-art models in both held-out evaluation and independent patient datasets\, demonstrating improved accuracy in assigning TCRs to their correct restricting MHC alleles. I then propose TRILOBITE\, a two-part structure-based model combining atomic-resolution graph representations and dynamics-derived biophysical features to classify TCR–pMHC binding and estimate affinity. Finally\, I propose an end-to-end pipeline to identify tumor-reactive TCRs from patient-derived sequencing data by integrating HLA typing\, antigen prediction\, structure generation\, and binding assessment. Applied to a pan-cancer atlas of over 1.2 million T cells\, this framework will enable high-throughput\, structure-informed TCR discovery across diverse HLA backgrounds. Together\, these aims address a critical need for scalable\, mechanistically grounded methods for mapping T cell specificity to accelerate cancer immunotherapy discovery. \nEvent Host: Nicholas Rose\, PhD student\, Biomolecular Engineering & Bioinformatics \nAdvisor: Vanessa Jonsson
URL:https://events.ucsc.edu/event/rose-n-bmeb-machine-learning-models-for-t-cell-receptor-target-discovery-and-affinity-engineering/
LOCATION:Jack Baskin Engineering\, Baskin Engineering 1156 High Street\, Santa Cruz\, CA\, 95064
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DTSTART;TZID=America/Los_Angeles:20250807T173000
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CREATED:20250702T070000Z
LAST-MODIFIED:20250925T231620Z
UID:10000055-1754587800-1754587800@events.ucsc.edu
SUMMARY:Slugs at Sundown - The Art of the Career Pivot
DESCRIPTION:Thinking about making a career change? Join fellow Banana Slugs for an evening of connection and guidance from professional career coaches. Learn how to navigate transitions with confidence\, gain practical strategies\, and get inspired to take the next step in your journey—whether you’re pivoting by choice or by chance. \nBonus: Come early for a 15-minute\, one-on-one resume review—available from 4:30 to 5:30 PM.
URL:https://events.ucsc.edu/event/slugs-at-sundown-the-art-of-the-career-pivot/
LOCATION:Silicon Valley Campus\, 3175 Bowers Avenue\, Santa Clara\, CA\, 95054\, United States
CATEGORIES:Meetings & Conferences
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