The past decade has seen an explosion in the use of the Internet and in the amount of information available to its users. Amongst the wealth of information is a vast amount of biological data being generated by the various genome projects around the world. The distribution of this data, via the Internet into the public domain, has brought with it the need to find more sophisticated techniques for biological data management, analysis, and modelling. While the physical sequencing and collection of biological data is important, the analysis of this data is also important. Biological data can be analysed and modelled in many different ways and with various methods.
This thesis discusses issues involved with the storage, analysis, and modelling of biological data. The Evolving Fuzzy Neural Network (EFuNN) is shown to be a suitable connectionist based model for use in this application area. With the use of the EFuNN, a proposal is made for an online analysis and modelling system for biological data. The implementation of this model, a system called GenIn, is described and made available for public access via the
Internet.
