1. A data clustering method performed with an electronic processor comprising: providing access to a dataset stored electronically in a dataset structure on a memory, the dataset having at least a few thousand aligned sequences in at least one set, each sequence having exactly B values, where 3≦B≦20, the value sequences representing changes in observed values as a function of a variable subject to noise; computing an order preserving abbreviated characterization of each of the value sequences, such that two value sequences will only have the same abbreviated characterization if they exhibit equivalent trends under any sequence reordering; and associating value sequences characterized the same to respective clusters by annotating a record containing the value sequence to identify the characterization, and/or by adding an identifier of the associated value sequence to a record created for the class.