S E M I N A R
MS Thesis Presentation
Supervisor: Asst. Prof. Uğur Doğrusöz
The enhancements in genomic studies have given birth to the necessity of advanced techniques for storing, integrating and analyzing the accumulated data regarding molecular level cellular processes. Since this data is huge and complex, advanced visualization and complexity management techniques need to be developed to improve its understandability. In this thesis, we present a single subject - multiple view framework for manipulating complex pathway data, which is in the form of a directed graph. The framework facilitates visualization of potentially huge pathway data in possibly varying forms and sizes. While maintaining the subject data (i.e. pathway graph) and its views, the presented framework coordinates all the views using an observer software pattern. It ensures the validity and consistency of subject data across all views. Support for replication of biological data, which is desired to reduce complexity (i.e., high degree ubique pathway objects), is another benefit of our framework. Being a neatly modularized, isolated component of a functional pathway editor, this framework is distinguished from any other single subject - multiple view graph editing environment by addressing the domain specific needs of pathway informatics.