Optimization and Analysis of Seriation Algorithm for Ordering Protein Networks

Analysis by Transcriptogram was developed as a solution to reduce the noise in the micro array measuring technique of the Transcriptome, and has demonstrated potential to be applied as a method of disease diagnostics. The noise reduction in the measurement is achieved by ordering the proteins of a given protein interaction network in a linear way, allowing gene expression analysis in whole genome scale. The ordering process uses a seriation technique, which models a protein-protein association network into an undirected graph. So far, the viability of the diagnosis method was hindered by the high runtime of the ordering algorithm, since the Homo sapiens network can have around 30 thousand proteins. This paper presents some optimizations applied to the seriation problem, which lead to a significant reduction of execution time and the problem complexity analysed. Results show that the algorithm produces good results in reasonable time, e.g. Order an undirected network of 9684 nodes in about 35 minutes, which is faster if compared with other seriation techniques evaluated.