Elucidation of molecular mechanisms involved in the regulation of flowering and seed development reveals that they are processes controlled by an intricate network of genes. These processes are affected as part of interaction between the plant’s genotype and its growth environment which itself displays plasticity in day length, temperature, moisture and nutrition in addition to various biotic and abiotic stresses that involves interaction with growth hormones. Further, transient events such as pollination, fertilization and daily physiological adjustments within the tissue are tied to diurnal variations in temperature and moisture status. Conceptualizing the interplay of a group of genes or their products to create interaction networks helps in understanding the biological context and significance of each of these components. Discerning the rhythmic expression pattern of key genes involved in these developmental processes enables dissection of their function and interactions with other genes. Comparative analysis in different species allows separation of commonalities and uniqueness of interactions and the underlying differences between species with different growth habit. By curating known gene to gene interactions and their co-expression networks from published literature, we have developed a network of metabolic and regulatory pathways representing flowering time and seed development in Arabidopsis and rice, the two model plant species. The computational analysis involving gene orthologies, co-expression and functional annotations was also developed to project similar networks for sequenced plant genomes of Brachypodium, maize, sorghum, soybean and poplar. We will present the comparative analysis of gene networks and transcriptome profiles. In particular, we will compare the rhythmic expression of genes regulating flowering and seed development in Arabidopsis and rice with that of Brachypodium, which is emerging as a new model species to study other grasses. This work is supported by the Oregon State University startup funds to PJ and is a collaboration between the NSF funded projects on Plant Ontology (IOS: 0703908) and the Gramene database (IOS: 0822201).