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learning and adaptation in biological systems
learning and adaptation in biological systems
Biological systems survive by sensing, adapting, navigating, and communicating to make effective decisions in complex environments, and this kind of "cognition" extends well beyond brains and nervous systems. We study how individual cells, from slime molds to immune cells, transform environmental cues through physical and biochemical processes into actions that help them explore and exploit their surroundings, and how these decision rules can change over time to improve performance through learning and adaptation.
Maya Harari, Obinna Ukogu
mapping the immune shape space with physics-inspired machine learning
mapping the immune shape space with physics-inspired machine learning
Immune recognition relies on molecular interactions between immune receptors and pathogens, which in turn is determined by the complementarity of their 3D structures and amino acid compositions (immune shape space). We are developing machine learning methods that leverage physical constraints to learn representations of protein micro-environments in general, and model and design immune-pathogen interactions, in particular.
Ella Carlander, Gian Marco Visani, Jakkub Otwinowski, Kevin Borisiak
design principles of the immune system
design principles of the immune system
The immune system must eliminate a multitude of pathogens while sparing healthy tissue. What are the biophysical and evolutionary principles that govern immune function? How immune responses emerge from the decision rules individual cells use to interpret antigenic and inflammatory signals, and how those rules have been shaped by biophysical limits and evolutionary trade-offs?
Obinna Ukogu
uncovering and steering the dynamic landscape of immune decision making
uncovering and steering the dynamic landscape of immune decision making
Immune responses emerge from interconnected networks of signaling molecules and antigen recognizing cells across the innate and adaptive immune systems, where individual cells make fate decisions in a dynamic landscape shaped by cell-cell interactions and pathogen or inflammatory cues. By building biophysics-informed statistical models grounded in experimental data, we aim to uncover the principles of immune decision making and develop predictive frameworks that can guide control strategies for next generation immunotherapies.
Darin Momayezi, Manali Sawant
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