Evaluating mixed HTC/cloud approaches for parameter sweep applications in systems biology

In biology, dynamical models are used to understand and predict the behavior of biochemical systems composed of numerous species and reactions. Model parameters represent aspects of the studied system and, therefore, modifications of model parameters correspond to perturbations of the real system. Several methods of model analysis are based on model perturbation by means of its parameter values. Thus, the execution of parameter sweep applications (PSAs) over large parameter spaces becomes very CPU intensive and time consuming.