  Metabonomics, the measure of the fingerprint of biochemical perturbations
caused by disease, drugs or toxins, recently has become a major focus of
research in various areas especially indications of drug toxicity. Two types of
technology (known by the initials NMR and MS) are employed and both produce
massive data in form of spectra. Sophisticated statistical models, known as
pattern recognition techniques, are commonly applied for summarizing and
analyzing these multidimensional data. However, strong signals from compounds
that are administered during toxicological trials interfere with these models.
So called 'spectral replacement' is a method to eliminate these signals by
replacing them with the signals in their corresponding regions in control
spectrum. The replaced regions are subsequently scaled. However, this scaling
is not accurately measured and often results in overestimation of integrated
intensity of the replaced signals. Here, a novel protocol is proposed which
provides an accurate estimation of the replaced regions.
