Then, given a set of spectra, simply look up each peak to find fragment explanations and intersect the sets. This intersection can be analyzed in a probabilistic framework that predicts how likely it is that the intersection will be able to resolve all ambiguities. Following is a set of figures giving the intuition. The heights of the bars are representative of the respective probabilities. Correctness is a function of the biological ground truth.
Appearance is a function of our observations.
We can eliminate a fragment unless it appears in all experiments. Finally, a set of labelings is interpretable if all fragments are either correct or eliminatable. It is therefore attractive for high-throughput functional genomics studies. However, the information extracted is rather minimalist compared to NMR or Xray crystallography, so a large burden is placed on the algorithmic problems of experiment planning and data analysis. We have explored the problem of eliminating mass degeneracy in SAR by MS, developing an experiment planning framework that seeks to maximize the information content of an SAR by MS experiment, and an efficient data analysis algorithm that interprets the resulting data.