60 Copyright © 2015, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited. Chapter 4 Large-Scale Regulatory Network Analysis from Microarray Data: Application to Seed Biology ABSTRACT The inference of gene networks from gene expression data is known as “reverse engineering.” Elucidating genetic networks from high-throughput microarray data in seed maturation and embryo formation in plants is crucial for storage and production of cereals for human beings. Delayed seed maturation and abnormal embryo formation during storage of cereal crops degrade the quality and quantity of food grains. In this chapter, the authors perform comparative gene analysis of results of different microar- ray experiments in different stages of embryogenesis in Arabidopsis thaliana, and to reconstruct Gene Networks (GNs) related to various stages of plant seed maturation using reverse engineering technique. They also biologically validate the results for developing embryogenesis network on Arabidopsis thali- ana with GO and pathway enrichment analysis. The biological analysis shows that different genes are over-expressed during embryogenesis related with several KEGG metabolic pathways. The large-scale microarray datasets of Arabidopsis thaliana for these genes involved in embryogenesis have been ana- lysed in seed biology. The chapter also reveals new insight into the gene functional modules obtained from the Arabidopsis gene correlation networks in this dataset. INTRODUCTION Recent advances in microarray technologies have made it possible to routinely measure the expres- sion levels of tens or even hundreds of thousands of genes simultaneously. Such high-throughput experimental data have initiated much recent re- search on large-scale gene expression data analysis. Various data mining techniques (e.g., clustering and classification) have been employed to uncover the biological functions of genes from microarray data. Recently, these techniques have included a Anamika Basu Gurudas College, India Anasua Sarkar SMIEEE Government College of Engineering and Leather Technology, India DOI: 10.4018/978-1-4666-6611-5.ch004