Figure 1. Schematic of motif-finding approach.

FIRE-pro seeks to identify protein motifs whose pattern of presence and absence across all amino acid sequences is highly informative about the behavior profile for the corresponding proteins. The algorithm takes as input a user-specified protein behavior profile listing a quantitative measurement or discrete attribute of every protein (e.g., half-life or nuclear localization). Presented is a schematic example using discrete localization data. Here, knowing whether the motif is present or absent in the amino acid sequence provides significant information regarding the behavior of the protein. For each candidate motif (e.g., “KRK”), FIRE-pro calculates the correlation between the motif profile and the protein behavior profile using mutual information. Motifs that maximize the mutual information are ultimately selected for further characterization.