Boosting the speed and accuracy of protein quantification algorithms in mass spectrometry-based proteomics

Current methods for protein level quantification in mass spectrometry-based proteomics do not scale with the increasing number of samples because of limited system memory and algorithmic complexities. Here we propose a new data structure that supports parsing of input as data stream, improve state of the art quantitation methods in performance by orders of magnitudes, and provide a generic method to boost the precision and accuracy by fragment weighting.