Meta Analysis of Microarray Data Using Gene Regulation Pathways

Using microarray technology for genetic analysis in biological experiments requires computationally intensive tools to interpret results. The main objective here is to develop a “meta-analysis” tool that enables researchers to “spray” microarray data over a network of relevant gene regulation relationships, extracted from a database of published gene regulatory pathway models. The consistency of the data from a microarray experiment is evaluated to determine if it agrees or contradicts with previous findings. The database is limited to “activate” and “inhibit” gene regulatory relationships at this point and a heuristic graph based approach is developed for consistency checking. Predictions are made for the regulation of genes that were not a part of the microarray experiment, but are related to the experiment through regulatory relationships. This meta-analysis will not only highlight consistent findings but also pinpoint genes that were missed in earlier experiments a...

• Type: Conference
• Year: 2008
• Where: BIBM
• Authors: Saira Ali Kazmi, Yoo-Ah Kim, Baikang Pei, Ravi Nori, David W. Rowe, Hsin-Wei Wang, Alan Wong, Dong-Guk Shin
• Keywords: BIBM 2008, Bioinformatics, Gene Regulation Relationships, Gene Regulatory Pathway, Regulatory Relationships