Motivation: Peptide detection is a crucial step in mass spectrometry (MS) based proteomics. Most existing algorithms are based upon greedy isotope template matching and thus may be prone to error propagation and ineffective to detect overlapping peptides. In addition, existing algorithms usually work at different charge states separately, isolating useful information that can be drawn from other charge states, which may lead to poor detection of low abundance
['Youting Sun', 'Jianqiu Zhang', 'Ulisses Braga-Neto', 'Edward R. Dougherty']
BPDA2d—a 2D global optimization-based Bayesian peptide detection algorithm for liquid chromatograph–mass spectrometry