A comparison of simple algorithms for gamma-ray spectrometers in radioactive source search applications.

Large variation in ambient gamma-ray backgrounds challenges the search for radiation sources. Raising detection thresholds is a common response, but one that comes at the price of reduced detection sensitivity. In response to this challenge, we explore several trip-wire detection algorithms for gamma-ray spectrometers.

Comparison of probability and likelihood models for peptide identification from tandem mass spectrometry data.

We evaluate statistical models used in two-hypothesis tests for identifying peptides from tandem mass spectrometry data. The null hypothesis H(0), that a peptide matches a spectrum by chance, requires information on the probability of by-chance matches between peptide fragments and peaks in the spectrum. Likewise, the alternate hypothesis H(A), that the spectrum is due to a particular peptide, requires probabilities that the peptide fragments would indeed be observed if it was the causative agent.

Sequence optimization as an alternative to de novo analysis of tandem mass spectrometry data.

Motivation: Peptide identification following tandem mass spectrometry (MS/MS) is usually achieved by searching for the best match between the mass spectrum of an unidentified peptide and model spectra generated from peptides in a sequence database. This methodology will be successful only if the peptide under investigation belongs to an available database. Our objective is to develop and test the performance of a heuristic optimization algorithm capable of dealing with some features commonly found in actual MS/MS spectra that tend to stop simpler deterministic solution approaches.

Improved peptide sequencing using isotope information inherent in tandem mass spectra.

We demonstrate here the use of natural isotopic 'labels' in peptides to aid in the identification of peptides with a de novo algorithm. Using data from ion trap tandem mass spectrometric (MS/MS) analysis of 102 tryptic peptides, we have analyzed multiple series of peaks within LCQ MS/MS spectra that 'spell' peptide sequences. Isotopic peaks from naturally abundant isotopes are particularly prominent even after peak centroiding on y- and b-series ions and lead to increased confidence in the identification of the precursor peptides.