Title page for ETD etd-01242006-084630

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
Advisor Name Title
Prof E Barnard
  • Artificial Neural Network application
  • automated promoter detection
  • Polymerase II
Date 2005-09-06
Availability unrestricted
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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