Diseases and infections elicit a multilayered immune response which consists of molecular and cellular interaction cascades. Recent advances in high-throughput technologies have facilitated multiparameter investigation of immune cells involved in human immune responses. These multiparameter investigations generate large-scale datasets and advanced computational techniques are required to gain useful information from them. Networks or graphs offer a practical way to represent complex information and develop advanced algorithms to unveil the underlying mechanisms. Here we discuss ways to assemble and analyze networks using genome-wide transcriptional profiles. Additionally, we discuss ways to integrate information available in primary literature and databases with the networks assembled using large-scale datasets. Finally, we describe ways in which network analysis offers insights into human immune responses.
Keywords: Clustering; Correlation; Gene co-expression; Immunology; Mutual information; Network; Transcriptomics.