A cellular pathway can be defined briefly as a human readable abstraction of events happening in the cell. With the PATIKA project, our aim was to model and store vast amount of cellular pathway data in a centralized database. A common problem of every scientific database is the risk of loosing highly valuable hidden relations in the data. If appropriate query tools cannot be provided to users for analyzing pathway data, these hidden relations cannot be detected, which may infer new information. For that reason form-based visual query tools are built to provide querying facility that will be needed by PATIKA users. However, queries made with visual tools are not flexible enough to let users modify the existing queries or define new queries to execute on PATIKA database. Also lack of powerful expression with these tools restricts the users while defining queries. In this thesis we propose an advanced query framework, NEON, which is developed for the PATIKA project for querying cellular pathways by using and extending a scripting language. It utilizes a novel integration of the well-known Jython scripting language with the PATIKA project to provide a software environment where systems can be developed in a seamless mixture of Java and Jython. The framework is designed flexible enough to enable users analyze any part of the PATIKA database by writing their own query scripts. According to the tests done on PATIKA system, querying through scripting methodology works fine on our pathway database and the analysis of cellular pathways through PATIKA seems to improve very much.

DATE: January 17, 2002, Friday @ 10:00
PLACE: EA-502