In this study, we developed and applied Netsci -a fast implementation k-nearestneighbor-based algorithm that utilizes GPU acceleration for the estimation of MI within sets of data. We also present the use of the "local alignment", which was useful for reducing spurious correlations in large or flexible biomolecular systems. We validated Netsci by estimating the MI of a 2D Gaussian distribution -a situation for which results may be directly compared to the analytic solution. We also repeated a MI and GC analysis on the B1 domain of protein G.