Argumentation in an experimental life science paper consists of a main claim being supported with reasoned argumentative steps based on the data garnered from the experiments that were carried out. In this paper we report on an investigation of the large scale argumentation structure found when examining five biochemistry journal publications. One outcome of this investigation of biochemistry articles suggests that argumentation schemes originally designed for genetic research articles may transfer to experimental biomedical literature in general. Our use of these argumentation schemes shows that claims depend not only on experimental data but also on other claims. The tendency for claims to use other claims as their supporting evidence in addition to the experimental data led to two novel models that have provided a better understanding of the large scale argumentation structure of a complete biochemistry paper. First, the claim graph displays the claims within a paper, their interactions, and their evidence. Second, another aspect of this argumentation network is further illustrated by the Model of Informational Hierarchy (MIH) which visualizes at a meta-level the flow of reasoning provided by the authors of the paper and also connects the main claim to the paper’s title. Together, these models, which have been produced by a manual examination of the biochemistry articles, would be likely candidates for a computational method that analyzes the large scale argumentation structure.