Cell fate determination, the process of transforming a unicellular embryonic cell into lineage-restricted specific tissues of a multicellular organism, is fundamental to the process of development. Following the division of a single zygote, how can seemingly similar neighboring cells ultimately differentiate into disparate cell fates, and maintain their differences? An understanding of this complex and intricate process is important for stem cell-based therapies and treatment of cancer. To provide the necessary conceptual background, we review two complementary perspectives that aid our understanding of the differentiation process -- a systems dynamics level view and a molecular mechanism level view. We introduce the experimental systems, the diverse types of data collected for this work, and computational methods to integrate them to arrive at a coherent model. From a systems dynamics perspective, cell fates can be thought of as attractors in the high dimensional gene regulatory networks. With this view, we designed experiments that identified a class of genes that are "divergent" in their expression during the differentiation process. These genes are associated with neutrophil differentiation and cell cycle progression. Further promoter-based transcription factor binding site analyses reveal enrichment of factors functionally linked to cancer progression and neutrophil differentiation, suggesting a systems dynamics view has the potential to elucidate mechanistic level details. From a molecular mechanistic perspective, we investigate how T-bet, a Th1 lineage defining transcription factor, functionally regulates its target genes. We experimentally determine genome-wide binding locations of T-bet and target genes that it regulates. We find distinct genomic signal patterns for genes that are differentially regulated compared to those that are not. We find that the chromatin-modifying and N-terminal domains of the T-bet protein are necessary for the regulation of T-bet targets. Further, T-bet targets are also differentially regulated in other T helper subtypes. Both perspectives offer unique insights into the differentiation process. Future direction would include methods to combine both perspectives by modeling mechanistic details while keeping track of the larger dynamic "emergent" attractor properties of the network.