Adam Siepel



My laboratory’s research is at the intersection of computer science, statistics, evolutionary biology, and genomics. We use comparative genomics, statistical models of molecular evolution, and novel algorithms both to identify previously unannotated “functional elements” in mammalian genomes – that is, sequences that encode proteins or structural RNAs, regulate transcription and translation, and otherwise directly control important cellular tasks – and to characterize the functions and evolutionary histories of such elements. A major theme in our work is to model the evolution and the function of genomic sequences simultaneously, so that evolution sheds light on function, and function sheds light on evolution. Our interest in mathematical models of genome evolution extends beyond genome annotation and evolutionary inference to the development of a more solid theoretical foundation for computational genomics

Record last modified Oct 13, 2018 9:50:12 AM