Virtual Seminar: "Machine learning methods for cellular engineering at different biological scales"
Event Type:
IBBR Seminar Series
Contact Person:
Nicole Tenly
Event Info
Date:
Tuesday, April 18 2023 - 11:00am to 12:00pm
Location:
Virtual
Event Details
Speaker:
Sara Capponi
Affiliation:
IBM, Almaden Research Center, CA (USA)
Description:
During the past decade artificial intelligence (AI) and machine learning (ML) approaches
have been widely used due to advances in algorithm development and computer
hardware. ML models are deeply rooted in statistical methods and their applications
represents a data-driven strategy to solve complex and often mathematically intractable
scientific problems. The success of ML approaches is due to the ability of learning
patterns and complex interactions inherently hidden in the data. These models have
been successfully applied in physical sciences. Here I will discuss two applications in the
main field of cellular engineering. The first application is related to predictions of binding
affinity trends between two molecules; the second concerns the intrinsic rules that define
the different phenotypes of genetically engineered T cells.