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SUMMARY:Synthetic Biology 2.0: the Dawn of a New Era - Huimin Zhao\, Unive
 rsity of Illinois at Urbana-Champaign\, Urbana\, IL 61801\, USA
DTSTART:20260112T110000Z
DTEND:20260112T120000Z
UID:TALK242443@talks.cam.ac.uk
CONTACT:Lorenzo Di Michele
DESCRIPTION:\nSynthetic biology aims to design novel or improved biologica
 l systems using engineering principles\, which has broad applications in m
 edical\, chemical\, food\, and agricultural industries. Thanks to rapid ad
 vances in DNA sequencing and synthesis\, genome editing\, artificial intel
 ligence/machine learning (AI/ML)\, and laboratory automation\, synthetic b
 iology has entered a new phase of exponential growth. In this talk\, I wil
 l highlight our recent work on the development of a self-driving biofoundr
 y\, AI/ML tools\, non-model organisms\, and novel enzymes for synthetic bi
 ology applications. Examples include but are not limited to: (a) BioAutoma
 ta: a self-driving biofoundry for pathway engineering and protein engineer
 ing\, (b) CLEAN: an AI tool for enzyme function prediction\, (c) EZSpecifi
 city: an AI tool for enzyme substrate specificity prediction\, (d) enginee
 red low-pH tolerant yeasts for cost-effective production of organic acids\
 , and (e) repurposed enzymes with new-to-nature reactivity for asymmetric 
 synthesis. \n\nReferences\n[1]. M. HamediRad\, et al. (2019) Nature Commun
 ications\,10: 5150 \n[2]. T. Yu\, et al. (2023) Science\, 379\, 1358–136
 3 \n[3]. V. Tran\, et al. (2023) Nature Communications\, 14:6152 \n[4]. X.
  Huang\, et al. (2020) Nature\, 584\, 69–74 \n[5]. M. Li\, et al. (2024)
  Science\, 385\, 416–421\n[6]. N. Singh\, et al. (2025) Nature Communica
 tions\, 16: 5648\n[7]. H. Cui\, et al. (2025) Nature\, 647\, 639–647
LOCATION:LT2\, Department of Chemical Engineering and Biotechnology
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