PIssGA: An ultra fast meta-heuristic approach to solve protein inference problem

The protein inference problem represents a major challenge in proteomics research. In this paper, we propose a novel meta-heuristic approach i.e. PIssGA to infer proteins from a given peptide sequence identified from tandem mass spectrometry in shotgun proteomics. Although most of the works available in the literature mainly adopts parsimonious pressure i.e. prefer least number of inferred proteins, our model is neither strictly parsimonious nor strictly optimistic, rather a tunable model that provides the flexibility to infer proteins either parsimoniously or optimistically or somewhere in between. Another important feature of PIssGA is its efficiency in search that makes the approach ultra first. We used Sigma49 dataset to test our method and found the proposed algorithm extremely fast and moderately accurate.