The information content of biopolymers is usually thought of in terms of the amount of information required to specify a unique sequence or structure. This viewpoint derives from classical information theory, which does not consider the meaning of a message, defining the information content of a string of symbols as simply that required to specify, store or transmit the string. Thus, the unannotated human genome sequence can be encoded in a 750-megabyte file, but this could be greatly reduced in size by the application of standard data-compression techniques to account for internal repetitions.

Approaches such as algorithmic complexity further define the amount of information needed to specify sequences with internal order or structure, but fail to account for the redundancy inherent in the fact that many related sequences are structurally and functionally equivalent. This objection is dealt with by physical complexity, a rigorously defined measure of the information content of such degenerate sequences, which is based on functional criteria and is measured by comparing alignable sequences that encode functionally equivalent structures. But different molecular structures may be functionally equivalent. A new measure of information — functional information — is required to account for all possible sequences that could potentially carry out an equivalent biochemical function, independent of the structure or mechanism used.

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