This reminds me of the sequence alignment algorithms we use in bioinformatics to find scores to rank nucleic acid or amino acid sequences by similarity[ex. 1].

This reminds me of the sequence alignment algorithms we use in bioinformatics to find scores to rank nucleic acid or amino acid sequences by similarity[ex. 1]. It's cool to see it extended to data beyond discrete base/aa values. The "time warping" aspect also kinda reminds me of the methods used in remote sensing for comparing spectral signatures (SCM/SAM) [ex. 2]. I'd be interested in learning where/how this is being used for problems in finance or economics. 1. http://en.wikipedia.org/wiki/Smith%E2%80%93Waterman_algorithm http://en.wikipedia.org/wiki/Smith%E2%80%93Waterman_algorith... 2. ftp://geo.arc.nasa.gov/pub/stevek/Spectral%20Correlation/Osmar_1_carvalho__web.pdf