Discretization of Time Course Data

Data discretization, also known as binning, is a frequently used technique in computer science, statistics, and their applications to biological data analysis. We present a new method for the discretization of real-valued time courses of data into a finite number of discrete values. It is specifically designed for discrete modeling methods using such data. Novel aspects are the incorporation of an informationtheoretic criterion and a criterion to determine the optimal number of values. While the method can be used on other types of data, the motivation for its development is the need for a discretization algorithm for several short multivariate time courses of heterogeneous data, such as transcript, protein, and metabolite concentration measurements. Furthermore, the method needs to preserve the dynamic features of the time courses as well as to be robust to noise in the experimental data. A C++ implementation of the algorithm is available at http://polymath.vbi.vt.edu/discretization.