title: Integrating omics technologies to study pulmonary physiology and pathology at the systems level.
abstract: Assimilation and integration of "omics" technologies, including genomics, epigenomics, proteomics, and metabolomics has readily altered the landscape of medical research in the last decade. The vast and complex nature of omics data can only be interpreted by linking molecular information at the organismic level, forming the foundation of systems biology. Research in pulmonary biology/medicine has necessitated integration of omics, network, systems and computational biology data to differentially diagnose, interpret, and prognosticate pulmonary diseases, facilitating improvement in therapy and treatment modalities. This review describes how to leverage this emerging technology in understanding pulmonary diseases at the systems level -called a "systomic" approach. Considering the operational wholeness of cellular and organ systems, diseased genome, proteome, and the metabolome needs to be conceptualized at the systems level to understand disease pathogenesis and progression. Currently available omics technology and resources require a certain degree of training and proficiency in addition to dedicated hardware and applications, making them relatively less user friendly for the pulmonary biologist and clinicians. Herein, we discuss the various strategies, computational tools and approaches required to study pulmonary diseases at the systems level for biomedical scientists and clinical researchers.
authors.affiliation: Morsani College of Medicine, Department of Pathology and Cell Biology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA.
authors.forename: Ravi Ramesh
authors.initials: RR
authors.lastname: Pathak
authors.forename: Vrushank
authors.initials: V
authors.lastname: Davé
mesh_terms: D023281:Genomics; D006801:Humans; D008168:Lung / Q000502:physiology*; D008171:Lung Diseases / Q000235:genetics / Q000378:metabolism / Q000473:pathology* / Q000503:physiopathology*; D055432:Metabolomics; D040901:Proteomics