A novel bioinformatics approach for classifying proteins according to similarity of function, rather than of sequence, is described in the April 12 PNAS. Albert Y. Lau and Daniel I. Chasman of Variagenics say that that their approach could be used to construct a database that would allow experimental confirmation of genomic sequences with unknown function. But other researchers questioned the practical applications of the work and suggested it was merely an extension of techniques currently used.

Standard methods of prediction of protein function from sequence rely on either an arbitrary standard—such as a cutoff point at a particular percentage sequence identity—or on analysis of annotations assigned by other experimentalists, Chasman told The Scientist.

“[Here], the idea is that if you have a bunch of sequences that you know are functionally related, but they have a few amino acids different, the operational definition tells you that you can substitute...

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