Living cells respond to their environment by means of an interconnected network of receptors, second messengers, protein kinases and other signalling molecules. This article suggests that the performance of cell signalling pathways taken as a whole has similarities to that of the parallel distributed process networks (PDP networks) used in computer-based pattern recognition. Using the response of hepatocytes to glucagon as an example, a procedure is described by which a PDP network could simulate a cell signalling pathway. This procedure involves the following steps: (a) a bounded set of molecules is defined that carry the signals of interest; (b) each of these molecules is represented by a PDP-type of unit, with input and output functions and connection weights corresponding to specific biochemical parameters; (c) a "learning algorithm" is applied in which small random changes are made in the parameters of the cell signalling units and the new network is then tested by a selection procedure in favour of a specific input-output relationship. The analogy with PDP networks shows how living cells can recognize combinations of environmental influences, how cell responses can be stabilized and made resistant to damage, and how novel cell signalling pathways might appear during evolution.