R: Comparing dissimilarity between metabolic models with discrete wavelet transformation
Take a look at the TSclust package. Here how you would apply it to your sample data. 

require(TSclust)

#read in the data
model_a &lt;- read.csv("~/Desktop/Model A.csv", header = TRUE, stringsAsFactors = FALSE)
model_b &lt;- read.csv("~/Desktop/Model B.csv", header = TRUE, stringsAsFactors = FALSE)

#data must be in rows rather than columns
model_a &lt;- as.data.frame(t(model_a))

model_b &lt;- as.data.frame(t(model_b))

#calculate dissimlarities between metabolites in models 1 and 2
met1_DWT.diss &lt;- as.numeric(diss.DWT(rbind(model_a['Met1', ], model_b['Met1', ])))
met1_DWT.diss
[1] 90.80332

met2_DWT.diss &lt;- as.numeric(diss.DWT(rbind(model_a['Met2', ], model_b['Met2', ])))
met2_DWT.diss
[1] 1.499241