ABSTRACT
The aim of this chapter is to review the investigation reported in the book. The main motivation for the investigation was to explore the challenges involved with the analysis of microarray image data such that the analysis system is not only enhanced but automated. The need to address this automated issue becomes particularly important as microarray systems offer huge advancements in medical diagnosis and drug discovery processes. However, current approaches to the analysis of microarray images rely a great deal on the human aspect, critically reducing the high throughput capabilities of these systems. Recognizing the importance of the automation issue (along with the related elements of process repeatability and system robustness) particularly, the study focused on delivering a system that encompassed these concepts throughout. Four areas of investigation were identified as key components of a microar-
ray analysis system and as such important in the creation of an appropriate system. The analysis of these key components produced a set of weaknesses of current analysis systems, be they performance, quality or consistency based. These issues were broadly discussed in Chapter 2 with an example analysis package highlighted to reinforce these issues in an existing and practical sense. Section 11.2 reviews the achievements in respect to the key issues as high-
lighted in Chapter 1. Since the study has presented a process that combines the biological and computer science domains, the subsequent Section 11.3 and Section 11.4 highlight the research contributions made by the book in terms of contributions to technical and practical. The final section, Section 11.5, reflects on possible limitations of the study and sets an agenda for future research.
