TY - JOUR AU - Tan, Soon-Heng AU - Hugo, Willy AU - Sung, Wing-Kin AU - Ng, See-Kiong PY - 2006 DA - 2006/11/16 TI - A correlated motif approach for finding short linear motifs from protein interaction networks JO - BMC Bioinformatics SP - 502 VL - 7 IS - 1 AB - An important class of interaction switches for biological circuits and disease pathways are short binding motifs. However, the biological experiments to find these binding motifs are often laborious and expensive. With the availability of protein interaction data, novel binding motifs can be discovered computationally: by applying standard motif extracting algorithms on protein sequence sets each interacting with either a common protein or a protein group with similar properties. The underlying assumption is that proteins with common interacting partners will share some common binding motifs. Although novel binding motifs have been discovered with such approach, it is not applicable if a protein interacts with very few other proteins or when prior knowledge of protein group is not available or erroneous. Experimental noise in input interaction data can further deteriorate the dismal performance of such approaches. SN - 1471-2105 UR - https://doi.org/10.1186/1471-2105-7-502 DO - 10.1186/1471-2105-7-502 ID - Tan2006 ER -