Fig. 5

Flowchart of this work. Four major steps are involved: data preparation, feature investigation, model construction and evaluation, and comparison with existing tools. In the first step, data preparation, two datasets are constructed, which are then separated into training and testing data after CD-HIT. Then four features are investigated: amino acid composition, N5C5, k-space and position-specific scoring matrix. The third step involves model learning, cross-validation, parameter optimization and evaluation. Finally, two models proposed are compared with other existing tools