Protein Domain Boundary Predictions: A Structural Biology Perspective

Kirillova, Svetlana; Kumar, Suresh; Carugo, Oliviero

To compare the accuracy of different methods with a random prediction we estimated numerically the probability density functions of the indices used to measure the classification validity. This approach is based on idea that the problem of domain boundary prediction using the amino acid sequence is a classification problem. Each residue is in fact predicted to belong to a certain class and it cannot belong to two different clusters at the same time. In other words, a residue can be predicted to belong to a certain domain, to another domain, or to a linker segment. The comparison between a prediction and the reality or between two predictions can thus be performed by using statistical tools that are routinely employed to compare alternative classifications [67] and that are briefly described below.