A novel algorithm for targeted metabolite profiling using NMR spectrum

Increasing interests in metabolomics have motivated the need for efficient and accurate metabolite profiling method. In this paper, we proposed a new method for targeted metabolite profiling. The approach relies on nonlinear least squares technique and a novel peak assignment algorithm. Peaks from experimental spectra are assigned to a reference compound library with the aid of mixed integer nonlinear optimization technique. Nonlinear least squares method is further applied to improve the concentration and chemical shift estimation. Results on several synthetic data sets demonstrate the good performance of the new method.