Sharon Aviran

Markov models of SHAPE data improve secondary structure prediction

It is shown that discretized SHAPE data display context dependence within loop regions and within stem regions and Markov models are used to formally capture such dependencies and demonstrates that finer modeling of SHAPE data has the potential to push the limits of data-guided secondary structure prediction.