Searching for the Emergence of Life-like Behaviors in Chemical Networks - Stephanie Colón-Santos - AAAS Annual Meeting

This course explores the emergence of life-like behaviors in chemical networks through untargeted analysis methods. The learning outcomes include understanding complex chemical networks with life-like properties, such as environmental responsiveness, auto-catalysis, self-sustenance, and evolvability. The course teaches skills in conducting UPLC-DDA-MS/MS analysis, using bespoke data analysis tools, and designing algorithms to explore chemical persistence over generations. The teaching method involves a combination of theoretical concepts, experimental setups, objective analysis, and discussions. The intended audience for this course includes researchers, scientists, and individuals interested in prebiotic chemistry and the origins of life.