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. Author manuscript; available in PMC: 2017 Dec 8.
Published in final edited form as: IEEE/ACM Trans Comput Biol Bioinform. 2016 Jul 7;14(6):1434–1445. doi: 10.1109/TCBB.2016.2586065

Figure 7. Strategic guidelines for the algorithmic inference of biochemical mechanisms from metabolomics data.

Figure 7

The flow chart shows recommendations for designing an algorithm for the inference of biochemical mechanisms underlying a disease from metabolomics data. Preferred metrics are Minkowski distance, Euclidean distance, Manhattan distance, Jeffreys & Matusita distance, Dice’s coefficient, and Jaccard similarity coefficient. These metrics have similar performance. The outputs from the sequential strategy and multi-phase strategy can be compared and provide further targets for experimental investigations.