This paper presents work on a method to detect names of proteins in running text. The detection and categorisation of named entities, such as names of people, organisations and places, in classical MUC-style information extraction tasks (Borthwick 1998) might be regarded a solved problem. But names of proteins present a slightly different challenge because of their variant structural characteristics and the specifics of the text domains in which they appear. This certainly holds true for other biological substances, and probably for many other kinds of terminology as well. We will present the different steps involved in our approach to this problem, and show how combinations of them influence recall and precision.