Metabolomics and Dereplication by Two-Dimensional Experiments (MADByTE; coordinated by Dr. Joseph M. Egan at Simon Fraser University) is a program that allows performing a comparative analysis of experimental HSQC and TOCSY spectra of a set of samples simultaneously. Thus, it allows the visualization of common profile peaks for prioritization of samples and rationalization based on the presented substructures. Specifically, these common features are spin systems identified in the TOCSY data and their respective C chemical shifts obtained via the HSQC data indexed by the 1 H chemical shift. Then, MADByTE identifies spin systems between different samples and assembles a network composed of nodes, which represent each sample, and edges related to the occurrence of certain spin system in each sample or shared between different samples. In fact, this visualization mode becomes more interesting when different samples are submitted to NMR analysis and to biological activity assays, when it is possible to call attention to the nodes with a promising biological response and observe the spin systems that characterize them. Another interesting application is demonstrated with the use of a database or reference spectra of compounds similar to those expected to be found in the samples to facilitate the identification of shared substructures. The use of MADByTE is limited by the need to acquire both HSQC and TOCSY data for multiple samples (or fractions) of a study. This effort is not routine for natural products chemists due to the cost of long periods of NMR use. The advances of NMR by Ordered Acquisition using 1 H detection (NOAH supersequences) , which combine different 1 H detection 2D NMR experiment into a "supersequence" eliminating the individual relaxation period (d1) of each combined unit, will overcome this limitation. In fact, the experiment time of a combined HSQC and TOCSY under the same NOAH supersequence is comparable to the acquisition of HSQC or TOCSY data alone, considering the same sequence parameters. This approach was demonstrated using the COLMAR platform where HSQC and HSQC-TOCSY data had been acquired in a single pulse sequence indicating a time savings of around 40%. Due to the limitation in collection HSQC and TOCSY data for a batch of samples for this demonstration, an example made available by Egan's research group was used. The output network is shown at