NEURAL-NETWORK CONTRIBUTIONS IN BIOTECHNOLOGY

In the mid-1980s, widespread interest in research into artificial neur al networks re-emerged following a period of reduced research funding. The much wider availability and the increased power of computing syst ems, together with new areas of research, is expanding the range of po tential application. The main reason for this is that the potential to describe the characteristics of extremely complex systems accurately has been attributed to this methodology. This article examines the con tribution of various network methodologies to bioprocess modelling, co ntrol and pattern recognition. Industrial processes can benefit from t he application of feedforward networks with sigmoidal activation funct ions, radial basis function networks and autoassociative networks. The contribution that neural networks can make to biochemical and microbi ological scientific research is also reviewed briefly.