Membrane proteins do not reveal their structures easily. Because they are particularly hard to crystallize, such proteins make X-ray crystallography expensive and time-consuming. So, many investigators turn to theoretical, mathematical methods to predict transmembrane protein topologies. This Hot Paper was among the first to report the application of the hidden Markov model (HMM) to such a task.
All the information and material exchange of the cell goes through transmembrane proteins. The stakes are potentially high in the hunt for transmembrane topologies. "People are doing data mining to find interesting proteins," says Hot Paper lead author Anders Krogh, a professor of bioinformatics at the University of Copenhagen. "And membrane proteins, for instance, are very important to the drug industry because receptors on the cell are membrane proteins."
Named after Russian mathematician Andrei A. Markov, whose work initiated the theory of stochastic processes, HMMs are commonly used to identify members of protein ...
