An application of topological graph clustering to protein function   prediction
  We use a semisupervised learning algorithm based on a topological data analysis approach to assign functional categories to yeast proteins using similarity graphs. This new approach to analyzing biological networks yields results that are as good as or better than state of the art existing approaches. 
R. Sean Bowman and Douglas Heisterkamp and Jesse Johnson and Danielle   O'Donnol
cs.CE cs.LG q-bio.QM stat.ML