Document Type	Master's Dissertation
Author	Myburgh, Gerbert
Email	gerbert.myburgh@kentron.co.za
URN	etd-01242006-084630
Document Title	Eukaryotic RNA Polymerase II start site detection using artificial neural networks
Degree	MEng (Computer Engineering)
Department	Electrical, Electronic and Computer Engineering
Supervisor	Advisor Name Title Prof E Barnard
Keywords	Artificial Neural Network application automated promoter detection Polymerase II
Date	2005-09-06
Availability	unrestricted
Abstract An automated detection process for Eukaryotic ribonucleic acid (RNA) Polymerase II Promoter is presented in this dissertation. We employ an artificial neural network (ANN) in conjunction with features that were selected using an information-theoretic approach. Firstly an introduction is given where the problem is described briefly. Some background is given about the biological and genetic principles involved in DNA, RNA and Promoter detection. The automation process is described with each step given in detail. This includes the data information gathering, feature generation, and the full ANN process. The ANN section of the project is split up in a generation process, a training section as well as a testing section. Lastly the final detection program was tested and compared to other promoter detection systems. An improvement of at least 10% in positive prediction value (PPV) in comparison with current state-of-the-art solutions was obtained. Note: A Companion CD should accompany this report that contains all the program code and some of the source data that was used in this project. All the references to “Companion CD”, reference number [18] are references to these programs.acquisition process, how the different samples were split into different sets and statistical.
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