A general algorithm for peak-tracking in multi-dimensional NMR experiments.

We present an algorithmic method allowing automatic tracking of NMR peaks in a series of spectra. It consists in a two phase analysis. The first phase is a local modeling of the peak displacement between two consecutive experiments using distance matrices. Then, from the coefficients of these matrices, a value graph containing the a priori set of possible paths used by these peaks is generated. On this set, the minimization under constraint of the target function by a heuristic approach provides a solution to the peak-tracking problem. This approach has been named GAPT, standing for General Algorithm for NMR Peak Tracking. It has been validated in numerous simulations resembling those encountered in NMR spectroscopy. We show the robustness and limits of the method for situations with many peak-picking errors, and presenting a high local density of peaks. It is then applied to the case of a temperature study of the NMR spectrum of the Lipid Transfer Protein (LTP).