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Figure 2 | BMC Bioinformatics

Figure 2

From: Interpolative multidimensional scaling techniques for the identification of clusters in very large sequence sets

Figure 2

Interpolative Multidimensional Scaling (MDS). Interpolative MDS begins with a raw sequence file, which is then divided into in-sample and out-of-sample sets. The in-sample data is then subjected to full NW distance and MDS calculations, resulting in a subset of genetic distances. This trained data is then used to interpolate the distances for the remaining, out-of-sample sequences. The computational complexity of the interpolation step is O((N-M)*M), where N is the size of the original sequence set and M is the size of the in-sample data.

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