The fact that lung cancer is a heterogeneous disease suggests that there is a high likelihood that effective lung cancer biomarkers will need to address patient-specific molecular defects, clinical characters, and aspects of the tumor microenvironment. In this transition, clinical bioinformatics tools and resources are the most appropriate means to improve the analysis, as major biological databases are now containing clinical data alongside genomics, proteomics, and other biological data. Clinical bioinformatics comprises a series of concepts and approaches that have been used successfully both to delineate novel biological mechanisms and to drive translational advances in individualized healthcare. In this article, we outline several of emerging clinical bioinformatics-based strategies as they apply specifically to lung cancer.