Liana Lareau works to decipher the layers of information encoded in the genome that specify cellular form and function. She uses machine learning and high throughput experiments to model how sequence determines the output of the genome as it is transcribed into RNA then translated into protein. She is an assistant professor of Bioengineering at Berkeley and a Chan Zuckerberg Biohub investigator. Previously, she was supported by a Damon Runyon postdoctoral fellowship at Stanford, where she used new methods to understand mRNA translation. She earned her PhD from Berkeley after undergraduate degrees in mathematics and biology from MIT.
Liana Lareau works to decipher the layers of information encoded in the genome that specify cellular form and function. She uses machine learning and high throughput experiments to model how sequence determines the output of the genome as it is transcribed into RNA then translated into protein. She is an assistant professor of Bioengineering at Berkeley and a Chan Zuckerberg Biohub investigator. Previously, she was supported by a Damon Runyon postdoctoral fellowship at Stanford, where she used new methods to understand mRNA translation. She earned her PhD from Berkeley after undergraduate degrees in mathematics and biology from MIT.
Liana Lareau works to decipher the layers of information encoded in the genome that specify cellular form and function. She uses machine learning and high throughput experiments to model how sequence determines the output of the genome as it is transcribed into RNA then translated into protein. She is an assistant professor of Bioengineering at Berkeley and a Chan Zuckerberg Biohub investigator. Previously, she was supported by a Damon Runyon postdoctoral fellowship at Stanford, where she used new methods to understand mRNA translation. She earned her PhD from Berkeley after undergraduate degrees in mathematics and biology from MIT.