Systems literature analysis (SLA) is the literature-driven version of systems biology. It treats collections of scientific literature as a system of millions of interconnections between research parameters, such as genes, diseases, tissues, cell events, model organisms, experiment types, and reagents. SLA aims to replace the traditional keyword-based querying of literature databases, which return sorted lists of papers, with a systems-based approach that returns integrated networks of relationships. Major applications include literature-based discovery of novel targets that link, for example, previously unlinked diseases and phenotypes to common genes and cellular events, and experiment design.