The rapid increase in genomic information requires new techniques to infer protein function and predict protein-protein interactions.Bioinformatics identifies modular signaling domains within protein sequences with a high degree of accuracy.We have successfully predicted numerous short linear sequence motifs within proteins targeted by these domains to form complex signaling networks.A peptide library-baseds earching program was created to identify sequence motifs likely to bind to specific protein domains such as 14-3-3,SH2,and SH3 domains,or likely to be phosphorylated by specific protein kinases such as Src and AKT.Predictions from database searches for proteins containing motifs matching two different domains in a common signaling pathway provides a much higher success rate.This technology facilitates prediction of cell signaling networks within proteomes,and could aid in the identification of drug targets for the treatment of human diseases.