From the Ising Model to Biological Sequence Analysis

The life sciences accumulate an enormous amount of biological
sequence information. E.g., GenBank, the central repository,
currently holds about 95 billion bases and is growing exponentially
with a doubling time shorter than the doubling time of computer
power in Moore's law. In the talk, I will use a concrete
biological phenomenon, namely RNA editing, to showcase how
methods from Statistical Physics are exquisitely suited to
analyze and make sense of this plethora of sequence information.