Neural-network contributions in biotechnology.

In the mid-1980s, widespread interest in research into artificial neural networks re-emerged following a period of reduced research funding. The much wider availability and the increased power of computing systems, together with new areas of research, is expanding the range of potential 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 contribution of various network methodologies to bioprocess modelling, control and pattern recognition. Industrial processes can benefit from the application of feedforward networks with sigmoidal activation functions, radial basis function networks and autoassociative networks. The contribution that neural networks can make to biochemical and microbiological scientific research is also reviewed briefly.